The Media Image of Israel in German Online News

A thesis presented to

the faculty of

the Scripps College of Communication of Ohio University and the Institute for Communication and Media Studies of Leipzig University

In partial fulfillment

of the requirements for the degrees

Master of Science in Journalism (Ohio University),

Master of Arts in Global Mass Communication (Leipzig University)

Thomas C. Roehl

April 2021

© 2021 Thomas C. Roehl. All Rights Reserved.

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This thesis titled

The Media Image of Israel in German Online News

by

THOMAS C. ROEHL

has been approved for

the E.W. Scripps School of Journalism,

the Scripps College of Communication,

and the Institute for Communication and Media Studies by

Alexander H. Godulla

Professor of Empirical Communication and Media Research

Scott Titsworth

Dean, Scripps College of Communication, Ohio University

Patrick Donges

Director, Institute for Communication and Media Studies, Leipzig University ii

Abstract

ROEHL, THOMAS C., M.S., Journalism; M.A., Global Mass Communication,

April 2021

3460865

The Media Image of Israel in German Online News

Director of Thesis: Alexander H. Godulla

Committee Members: Jatin Srivastava, Freya Sukalla

The German relation to Israel is marked by its historic circumstances, namely the

Shoah and the antisemitism which made it possible, but also cooperation between the two countries nowadays. Previous research on the portrayal of Israel in German print media, in particular during times of escalation in the Arab-Israeli conflict, have found a bias against Israel. This study provides an analysis of the media image of Israel in German online news media during a low-escalation period in the Arab-Israeli conflict, accounting for the changes in the media landscape due to digitalization and providing a comparison to traditional media. A sample by five German news outlets – Bild.de, n-tv.de, Spiegel.de, t-online.de and Zeit.de – during a 2019 low escalation-phase was analyzed using a structural objectivity content analysis. A focus was put on the overall evaluation as well as the topics and actors who can be found in the reporting. The findings show an overall balanced depiction with some outliers, in contrast to the portrayal of Israel during periods with high conflict.

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Dedication

Dedicated to my parents, Wolfgang and Brigitte, for their support and encouragement

throughout the process.

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Acknowledgments

I wish to thank my committee members for the time and effort they put into the thesis process and for answering my many questions. Thank you to Dr. Alexander

Godulla for serving as the committee chair and Dr. Jatin Srivastava and Dr. Freya Sukalla for serving as committee members.

A special thanks to the faculty members of the Institute of Communication and

Media Sciences at the University of Leipzig and the E.W. Scripps School of Journalism at

Ohio University for providing this unique opportunity, in particular to Dr. Bernhard

Debatin, Dr. Aimee Edmondson, Dr. Alexander Godulla and to Rosanna Planer.

I am very grateful to have been part of this program.

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Table of Contents

Page

Abstract ...... iii Dedication ...... iv Acknowledgments...... v List of Tables ...... viii List of Figures ...... x 1. Introduction ...... 1 2. The Construction of Media Images ...... 9 3. Israel’s Media Image in the German Press ...... 17 4. Research Design...... 28 4.1 Research Questions ...... 28 4.2 Hypotheses ...... 30 4.3 Methodology ...... 32 4.4 Data Collection ...... 35 4.5 Coding ...... 39 5. Results ...... 42 5.1 Structure of Material ...... 42 5.1.1 Publications and Relevance ...... 44 5.1.2 Sections ...... 45 5.1.3 Types of Text ...... 48 5.1.4 Lengths of Articles ...... 50 5.1.5 Sources ...... 51 5.1.6 Topics in the Reporting ...... 52 5.1.7 Actors in the Reporting ...... 53 5.1.8 Quotes ...... 57 5.1.9 Quoted Actors ...... 58 5.2 Hypothesis Testing...... 59 5.2.1 Israel in the News...... 60 5.2.2 Israelis in the News ...... 75 5.2.3 Israel in Quotes ...... 87 vi

5.2.4 Israel in the Headlines ...... 94 5.2.5 Overall Evaluation of Israel ...... 99 5.2.6 Differences Between the Publications ...... 101 5.3 Additional Findings ...... 104 5.3.1 Evaluations in Opinion Pieces ...... 104 5.3.2 Topics and Evaluation...... 106 5.3.3 Conflict and Evaluation ...... 108 6. Discussion ...... 111 7. Conclusion ...... 121 8. References ...... 126 Appendix A: Tabluar Overview of the Literatur ...... 146 Appendix B: Nullhypotheses and Alternative Hypoytheses ...... 154 Appendix C: Codebook...... 159 Appendix D: Structure of Material ...... 189 Appendix E: Hypothesis Testing ...... 197

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List of Tables

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Table 1 Relevance of Articles in the Sample ...... 43 Table 2 Frequencies of Sections in the Sample ...... 46 Table 3 Frequencies of Sections per Publication...... 47 Table 4 Types of Text per Publication ...... 49 Table 5 Mean Length of Article per Publication...... 50 Table 6 News Agency Credits per Publication...... 52 Table 7 Frequencies of Selected Topics per Publication ...... 53 Table 8 Frequencies of Most Common Actors per Publication ...... 54 Table 9 Average Number of Quotes by Country per Publication ...... 57 Table 10 Frequency of Quoted Actors per Publication ...... 58 Table 11 Frequencies of Developments in the Sample ...... 61 Table 12 Valencies and Distribution of Development per Publication ...... 62 Table 13 Mean Valency of Development per Publication, Not Weighted ...... 63 Table 14 Valency of Development per Simplified Main Topic...... 65 Table 15 Occurrence of the News Factor Conflict in the Reporting ...... 67 Table 16 Occurrence of News Factor Conflict per Publication ...... 68 Table 17 Frequency and Distribution of Responsibility ...... 70 Table 18 Percentages of Responsibility for Development per Country ...... 71 Table 19 Valency of Events (Binary) and Responsibility (Binary) ...... 73 Table 20 Valency of Events (Binary) and Responsibility (Binary) per Publication ...... 74 Table 21 Frequency of Selected Actors in the Reporting ...... 76 Table 22 Frequency of Actors (Reduced) per Publication ...... 78 Table 23 Frequency of Actors (Reduced) ...... 79 Table 24 Mean Evaluation of Selected Actors per Publication ...... 81 Table 25 Mean Evaluation of Israeli and Non-Israeli Actors ...... 82 Table 26 Valency of Israelis (Reduced) per Publication ...... 83 Table 27 Evaluation of Israelis and Non-Israelis per Publication ...... 85 Table 28 Mean Evaluation of Israelis in Conflict and Non-Conflict Reporting ...... 86

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Table 29 Mean Number of Quotes by Israelis and Palestinians During Conflict Between the Two ...... 89 Table 30 Quoted Actors (Reduced) and Their Evaluation of Israel ...... 90 Table 31 Crosstable Israeli (Positive Quotes) and Non-Israeli (Negative Quotes) ...... 92 Table 32 Crosstable All Positive and All Negative Evaluations in Quotes ...... 93 Table 33 Contentual Dissonant and Coherent Articles in the Sample ...... 95 Table 34 Contentual Dissonant and Coherent Articles per Publication ...... 96 Table 35 Contentual Dissonance to the Disadvantage and Advantage of Israel per Publication ...... 97 Table 36 Mean Overall Evaluation of Israel for All Outlets ...... 102 Table 37 Games-Howell Test for Differences in Overall Valency Between Publications ...... 103 Table 38 Mean Evaluation of Israel in Opinion Pieces ...... 105 Table 39 Mean Overall Evaluation per Main Topic (Simplified) ...... 106 Table 40 Mean Overall Evaluation per Topic (Simplified) and Publication ...... 107 Table 41 Mean Evaluation of Israel during Conflict and Non-Conflict per Publication ...... 109

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List of Figures

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Figure 1 Distribution of Israel as a major and minor theme in the articles ...... 44

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1. Introduction

Israel is not a country like any other. Over 70 years after the establishment of the state of Israel, the country is still controversial. Only 149 of the 194 UN member states recognize Israel (United Nations 2020; Jewish Virtual Library 2020), and it has been at war for a good portion of its existence – beginning the day the state was proclaimed and subsequently attacked by its neighbors to this day, as Israel and Syria have not signed a peace deal yet. The conflict with the Palestinian Hamas also still sporadically heats up

(Encyclopædia Britannica, 2019). The Arab-Israeli conflict is also one of the most mediated conflicts in the world. A number of factors play into this – most notably its length as the most prolonged ongoing conflict, its continuous flares up into active conflict, but also antisemitism and religious motivations. Due to this, reporting on Israel has become a tricky matter for journalists.

This is especially true in Germany. Given its history – the German responsibility for the industrial genocide of Jews, the Shoah – this should not come as a surprise. The state of Israel cannot be thought of without its historical circumstances. After the German divide, both West and East Germany had a fractious relationship with the Jewish state. In the West, a late recognition paired with official support from the government, in the East a distanced relation on par with the Soviet Union, which supported the Palestinian cause and as such opposed Israel (Mertens, 1995, p. 89, pp. 94; Pfahl-Traughber, 2002, pp. 142;

Wolffsohn & Grill, 2016, pp. 1592). Both countries, however, were characterized by a continuity of subliminal antisemitism stemming from the Nazi ideology (Bergmann &

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Erb, 1995; Bergmann & Erb, 1997; Pfahl-Traughber, 2002, pp. 135). This lead to an ambivalent character of German-Israeli-relations, with official support on the one hand but still common – although rarely overt – antisemitism in the population, which was – and still is – reflected in the views of Israel (see: Mertens, 1995; Hagemann &

Nathanson, 2015, p. 67; Wolffsohn & Grill, 2016, p. 166; Unabhängiger Expertenkreis

Antisemitimus, 2017, p. 63; and especially Schwarz-Friesel & Reinharz, 2017).

Antisemitism in Germany is a well-researched topic. Numerous studies have been done, and the matter continues to be an object of research.1 Once again, not too surprising given the German history of genocidal antisemitism. The same, however, cannot be said about the German reporting on Israel. While the German media depiction is often discussed in opinion pieces – with alleged bias ranging from a pro-Israeli one to an anti-

Israeli one and everything in between (e.g. Niggemeier, 2014, August 4; Woldin, 2014,

August 4; Weinthal, 2018, July 19; Dachs, 2019, April 8) – there is a distinct lack of recent systematic and empirical approaches. The few studies that have been done on the media image of Israel mostly found an anti-Israeli bias. However, it should be noted that all of these studies draw on material older than a decade. More importantly, the research

1 For example, Decker et al., 2010; Wetzel, 2012; Zick & Klein, 2014; Zick, Küpper & Krause, 2016;

Decker, Kiess & Brähler, 2016; Bergmann 2017; Unabhängiger Expertenkreis Antisemitismus, 2017;

Decker & Brähler, 2018; Glöckner & Jikeli, 2019, to name a few.

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population has always been traditional media, thus not accounting for the media landscape's rapid change since the 2000s.

The most discussed characteristics of many digital news sources have been accessibility and participation. While the latter is not relevant to the thesis at hand here, most, although not all, online news content is available for free to consumers and, due to the improvement of internet infrastructure – especially smartphones – easily accessible.

These characteristics of online news certainly play a role in its displacement of traditional media (Ha & Fang, 2012). However, there are also other, often less discussed characteristics that set digital news apart from traditional (print) news. It's these differences that add to the necessity of researching online news media specifically.

In contrast to traditional media, digital media has (theoretically) no limit to its publication space. Whereas traditional news – be it newspapers or news channels – have a clear limit to how much space they can give a news story or a topic, this is not the case in the digital sphere. The drop of this restriction has led to a more varied news selection in online news (Sjøvaag & Stavelin, 2012, p. 226). On the flip side, however, the lower hurdle for publishing news has also led to decreased editorial procedures and the risk of repetitive news stories, which can hurt the credibility of a source (Sjøvaag & Stavelin,

2012; Choi & Kim, 2016). Automatization has also been implemented in some areas of news reporting, such as financial news and sports (Van Darjen, 2012; Dörr, 2016).

Content testing tools, such as the Bandito implemented by the Washington Post, automatically adjust the presentation of news, e.g. the pictures, headlines, and teaser in

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real-time, in order to increase engagement (Marshall, 2016; The Washington Post unveils new real-time content testing tool Bandito, 2016). The latter in particular highlights a more challenging aspect of online news research – the content is much less manifest than print media; it can be changed or even deleted after publication. While noting corrections are best practice in the field, this is not the case for automated processes, and it is often not possible to see changes unless the authors note them. As discussed by Kautsky and

Widholm (2008), this can be a challenge for the research of online content.

The aim of this study is to provide an analysis of the contemporary reporting on

Israel in the German digital media. This objective is two-folded: For one, it is intended to provide a more recent study on the topic. Currently, most of the studies done on the issues are somewhat outdated. The most recent study draws on material from 2009 (see

Beyer, 2016). Since then, the political developments have led to at least two major public debates on Israel, German-Israeli relations, the Arab-Israeli conflict, and the role of

(German) media in its portrayal.2 It is reasonable to assume that these developments have impacted the media image of Israel one way or another.

2 A major debate sprang from the poem Was gesagt werden muss (What Must Be Said) by the late Günter

Grass (2012). The poem criticized Israel and in particular Israeli nuclear capabilities, which it described as a danger to world peace. The poem and Grass' subsequent interviews sparked a public debate about

German-Israeli relations and antisemitism. In particular, the question of whether one can publicly criticize

Israel without being denounced as an anti-Semite was publicly discussed. Grass, who had been a member of the Waffen-SS in his youth, had denied this and criticized that people would use the accusation as a mean

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Secondly, this research is focused on digital primary media [digitale

Primärmedien]. The studies done so far have solely focused on traditional print media.

The shift towards online news consumption in Germany in the last two decades (Hölig &

Hasebrink, 2020, pp. 22) is therefore currently not accounted for in the research. While most of the established digital news sources in Germany have their roots in traditional print media – including some of the outlets analyzed in this thesis –, it is essential to note here that this shift goes beyond merely the medium through which news are encountered.

The turn towards digital media – especially through mobile devices – has also impacted the way news are produced and consumed (see Antunovic, Parson & Cooke, 2016;

Molyneux, 2018; Nelson, 2020). In particular, the consumption of micro-news – short summaries or teasers of news articles – on social media has led to news organizations adapting to these new habits (Anderson & Caumont, 2014; Wohn & Bowe, 2016). As

to silence criticism (a comprehensive summary of the debate can be found in Detering and Øhrgaard,

2013).

The second major debate was in the summer of 2014, during a confrontation between Israel and

Hamas. During several pro-Palestinian protests in Germany, antisemitic slogans were cried. In some cases, there were also violent attacks on counter-protesters and synagogues. The events sparked a public debate about "traditional European and Muslim antisemitism," as some of these demonstrations had clear religious character such as gender segregation; at the same time, Nazi codes were shown, and organized Neo-Nazis were seen at the protests (Drobinski, 2014, July 21; Iskander & Riebsam, 2014; Sydow, 2014).

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social media has become increasingly important as a means of news aggregation, so have some aspects of text-based news, such as teaser texts and headlines, as those are often the only thing showed in the links-previews if shared on social media (Wohn & Ahmadi,

2019). Furthermore, the omission limitations regarding text character and images have changed production. As the news cycle has increased in speed, the hurdle for publishing has decreased. Less traditionally newsworthy events can be reported on, as the cost – and therefore risk – attached to publishing an article has drastically reduced as the space for publishing has increased essentially infinitely in the digital media sphere.

Another important aspect is the fact that, with a few exceptions, previous studies have primarily focused on times of high escalation in the Israeli-Palestinian conflict. In particular, the reporting during the First and the Second Intifada have been researched extensively. This can be problematic, as a focus on times of high-intensity conflict bears the risk of mudding the lines between characteristics of general conflict reporting – such as a focus on negativity and violence – and the specific characteristics of reporting on

Israel and the Israeli-Palestinian conflict. In this regard, the goal of this study is to provide an additional perspective on the general reporting, detached of phases of military escalation.

This study's objective is not to measure how "good" or "true" the reporting is. As will be explained in chapter 2, these categories are highly problematic as a measurement for the quality of reporting. Rather, the goal is to analyze what image of Israel is conveyed in the German digital media. The aim is to uncover tendencies and measure

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bias; whether these tendencies are just or based in reality or not can and will not be determined here.

As such, the focus is on the media image of Israel – the portrayal of the country and its citizens in the media. While it is impossible to view Israel strictly independent from the Arab-Israeli and, in particular, the Israeli-Palestinian conflict, this will not be the focus of this study and be excluded as good as possible – that is, a comparison between the media image of Israel and Palestine (or rather Palestinians) will not take place.

Similarly, an analysis of antisemitism and in particular antisemitic stereotypes and imagery will not be done here. While interesting and important aspects, these would go far beyond the scope of what is possible in this limited work.

Instead, the work proposed here will focus on the ensemble of portrayals of Israel in German online media. That is, how the country, its institution, and citizens are depicted as a whole. This means that there will be no type or section of news content categorically excluded from the study.

In the following chapter 2 the theory which provides the basis for this work will be laid out. Chapter 3 will provide an overview of the current literature on the matter (a table for quick comparison of the literature can be found in Appendix A, pp. 146). The methodological approach will be discussed in chapter 4, in particular the research questions, the hypotheses derived from them, the choice of material, and the method. The type of content analysis adequate for this kind of research will be laid out there. The results of the analysis of the material will be presented in chapter 5. First, the general

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structure of the material is explained in chapter 5.1, before the hypotheses are tested in chapter 5.2 using statistical methods. Additional findings are also included. The results and their implications are discussed in chapter 6. Finally, the conclusion of the study is presented in chapter 7.

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2. The Construction of Media Images

One of the important achievements of newer journalism research was the turn away from the media-as-mirrors paradigm and towards the constructivist approach.

In the mirror-approach, the news media were expected to “mirror reality,” hence the name. This is based on the assumption that there is an objective and perceivable-as- such reality, which exists independently from the media. The media is expected to replicate this “objective reality” as well as possible. How “good” this replication – the reflection of reality – is, constitutes what the media was judged on. The mirror-approach was superseded by the constructivist approach, based on the realization that such a universally perceivable and replicable reality may not exist (Schulz, 1989).3

The constructivist approach is based on the sociological concept of social constructionism. Social constructionism discusses what is perceived as reality, both for the individual and society as a whole. Its central premise is the assessment that there is no such thing as a universally perceivable reality, but that instead, each and every one constructs their own reality, based on available information, previous experiences, socialization, and beliefs.

3 A comprehensive portrayal of the decade-long paradigm dispute cannot be provided here, but can be found, for example, in Merten, Schmidt, and Weischenberg (1994), Rusch and Schmidt (1999), Weber

(2003), Pörksen (2011), or Scholl (2011).

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Communicative constructivism, then, focuses on the role of communication and media in this construction process. This is in particular important due to the role of mediatization in the modern world, as we increasingly have to rely on second-order observations (mediated through the [news] media) instead of first-hand observations to gather information. Second-order observations are mediated through communication. As such, the importance of analyzing this communication, on which's basis reality is constructed, cannot be underestimated.

The fundamental questions which concern constructivists have always been posed in media sciences – in particular, the question of the relation between “reality” and

“media reality.” Even before the paradigm shift in the 1990s, there had been a long- standing tradition of analyzing this relationship. Dating back to one of the first systematic analysis of mass media – a content analysis by John G. Speed in 1893 – but also including Walter Lippmann's Public Opinion (1922) and later the news value theory, gatekeeper theory, two-step-flow or more recently framing, all of these approaches grapple with the question of what and how (media) reality is (see Scholl 2011, p. 443;

Schulz 1989, p. 135; Rusch 1999, p. 7, Großmann 1999, p. 14).

Before the introduction of constructivism, researchers had already come to the conclusion that neither journalists can provide an exact portrayal of “the world” nor that the relation between media content and recipients is a one-to-one adoption (Großmann,

1999, p. 22). The constructivist approach was introduced into media and communication studies from sociology and further elaborated with a focus on the role of communication

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and media in the construction process. It should be noted that this was not a singular process, but rather that constructivist ideas were introduced at different times and found and find different levels of acceptance. Furthermore, constructivism is not a singular or uniform theory, but rather an umbrella term for different approaches, some of which are similar but others conflicting (Schmidt, 1994, p. 4). Throughout the years of academic discussion, a wide array of positions have been established, ranging from Siegfried J.

Schmidt's radical constructivism to Günter Bentele's moderate reconstructivism (see

Schmidt, 1987; Schmidt, 1992; Merten, 1994; Bentele, 2008).

Since the 1990s, there has been a copious debate about the constructivist and the realist paradigms, from which the constructivist paradigm arguably has emerged as the leading one.4 Although the approaches differ in regards to how far the extend of the constructivism goes – as mentioned above – they all share three basic assumptions (see

Merten, 1994, p. 309; Schmidt, 1994, p. 18):

1. There is no objective reality that humans can cognitively perceive to its full

extend. Instead, reality is subjectively constructed, based on selective

processes, previous experiences, and individual knowledge.

4 A detailed recapitulation of the decade-long dispute cannot and will not be provided here, but can be found, for example, in Merten, Schmidt, and Weischenberg (1994), Pörksen (2011), Rusch and Schmidt

(1999), Scholl (2011), or Weber (2003).

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2. In modern society, the base for these construction processes is increasingly

conveyed through the media, as observations of the second order.

3. As such, in a mass medial society, reality is increasingly constructed on the

basis of the media reality.

Reality – or rather, what the recipients construct as reality – is increasingly based on the information received from the media, as first-order observation cannot cover the full extent of knowledge necessary in the modern globalized world. We (usually) cannot observe all the events in the news first hand, but instead rely on the information provided by the news media to construct reality (see Ruhrmann, 1994, p. 246).

The word “construction” may imply intent. This is not the case. Rather, the construction process is a subconscious one, and, as mentioned above, based on a number of factors, such as previous knowledge, believes, and socialization (Schmidt, 1993, p.

107; Schmidt, 1994, pp. 595; Rusch, 1999, p. 9). Similarly, the notion that reality is constructed individually – and as such, subjectively – may imply a certain randomness if not arbitrariness. After all, if every individual constructs their own reality, how can we know what is real and what is not? It is important to note that the construction processes are not entirely random nor arbitrary. They do follow a logic, based on several factors such as those mentioned previously, as well as, for example, socialization, political and emotional biases, which, while hard to reconstruct, do lead to similar constructed realities on the same basis (Merten, 1995, p. 26).

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However, the question of what is “real” is not of importance for the constructivist approach – because this cannot be measured. Whereas the realist media researcher tries to compare media content against “the objective reality,” constructivists instead shift the focus towards how-questions. The goal cannot be to compare whether media content is

“good” or “objective” – still the measurements for news media – but rather how their reality is constructed and whether this reality is biased.

It is virtually impossible for journalistic content to not be biased in at least some way due to the inherent properties of communication itself. This is particularly true in news reporting.5 Authors D’Alessio and Allen (2000) proposed in their meta-analysis on media bias in US election campaigns three types of bias that commonly occur in news media:

Gatekeeping bias is the selection of stories and topics from the (theoretically infinite) body of possible stories and topics (D'Alessio & Allen, 2000, pp. 135). This type of bias is expected to occur in any kind of reporting, at least to some extent, since it is simply not possible to report on all events that might be newsworthy. While gatekeeping bias has been analyzed with Input-Output-Analyses in the past, this methodology brings

5 The question of whether such bias is intended or rather a result of news media's production logic is a question which the authors did bring up but could not find a conclusion to (see D'Alessio & Allen, 2000, p.

135).

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its own problem, mostly due to the unclear population of "potentially newsworthy events" (D'Alessio & Allen, 2000, p. 136).

Coverage bias is the space different positions or actors on a topic are given

(D'Alessio & Allen, 2000, p. 136). This approach is derived from the limitation of physical space in newspapers but can also be applied to television and radio (airtime) and digital news, e.g. the number of lines and articles. D'Alessio and Allen argue that an equal split between the different positions would be the most balanced and, therefore, least biased (2000, p. 136). However, they do acknowledge that the analysis of coverage bias may be problematic outside of electoral issues, where the participating parties may be less clearly defined (D'Alessio & Allen, 2000, p. 137).

Statement bias is the third type of bias and refers to instances where personal opinions and valuations are inserted into the reporting (D'Alessio & Allen, 2000, p. 136).

This may be in the form of explicit or implicit evaluations. Similar to coverage bias, the goal cannot be to have no statement bias at all but rather to find a balance between different positions and parties (D'Alessio & Allen, 2000, p. 138).

Framing can be seen as a fourth type of bias or as a symbiosis of the three aforementioned types. Either way, it is closely related to them due to its focus on selection and salience. Proposed by Entman in 1993, framing is the selection of "some aspects of a perceived reality and mak[ing] them more salient in a communicating text, in such a way as to promote a particular problem definition, causal interpretation, moral evaluation and/or treatment recommendation for the item described" (Entman, 1993, p.

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52). Framing, in essence, describes how meaning is derived from selecting and highlighting certain aspects of reality as thereby shaping the way it can be interpreted by the audience. Entman himself describes framing theory mainly as a research concept to analyze the unequal treatment of two or more sides of a conflict in the media – such as in political reporting – and to analyze the production side of allegedly biased content

(Entman 2007, p. 163). The latter, in particular, focuses on the “motivations and mindset”

– either consciously or subconsciously – of those who produce the news, but analyze it through the content (Entman 2007, p. 163). In framing, information is made more salient by highlighting them and by associating – or connecting – them with other information, thereby forming a context of meaning (Entman 1993, p. 53).

For the purposes of this study, the focus will be put on coverage and statement bias. This is also in part due to practical reasons. An Input-Output-Analysis has the problem of an impossible-to-define research population, while a framing-analysis would not be feasible due to the necessary mixed-methods approach and the large number of texts in the sample.

The goal of the analysis should be put on the construction process of the media image of Israel and their respective empirical conditions and references (Schmidt, 1994, p. 15, p. 18). In a mediated society, the main base for the construction of reality are the media contents, which means their respective discourses, information brokerage, the topics, and their framing, the linguistic portrayal, argumentation modes, and genres, among others (Schmidt, 1994, pp. 13; Altheide, 2014, p. 42, p. 45). While it may not be

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possible to analyze the media regarding how objective their content is, it is possible to analyze it regarding coverage and statement bias'.

It is important to note that such an analysis does not aim to unmask a “hidden agenda” by the media – an often antisemitic accusation by conspiracy theorists – nor does it aim to criticize individual journalists, but rather the goal is to reveal the base for the constructed reality of the media recipients.

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3. Israel’s Media Image in the German Press

While the scientific examination of antisemitism in the German press has been quite extensive6, this is much less the case for the media image of the state of Israel.

While the question of bias often pops up in essayistic articles, particularly during times of conflict (some examples include Harnasch, 2012, November 21; Niggemeier, 2014,

August 4; Woldin, 2014, August 4; Dachs, 2019, April 8), the same cannot be said about systematic examinations of the media reporting.

The following literature review will focus on studies on journalistic, text-based content and their findings. A tabular overview of relevant studies on the matter can be found in Appendix A (pp. 146). Studies on user-generated content (such as Becker, 2015,

Becker, 2018, or Giesel, 2015) will be excluded. Studies which focus on (audio-)visual content (such as IFEM, 2002, Medien Tenor, 2003a, Medien Tenor, 2003, or Beyer,

2007) will be also not be included, but can be found in the tabular overview in the appendix. Furthermore, only studies from 1990 and onwards – post-reunification in

Germany, due to its impact on the German media landscape – will be covered. Similarly, studies with major methodical flaws or a different primary focus will only be covered briefly or in some grave cases excluded, such as Lewan (2002), Langebucher and Yasin

6 A comprehensive historical analysis of antisemitism in the German press can be found in Nagel and

Zimmermann (2013); recent works on the topic of antisemitism in Germany and the media sphere can, for example, be found in Betzler and Glittenberg (2015), Enzenbach (2018), Grimm and Kahmann (2018),

Mihok (2013), or Schwarz-Friesel and Raynharts (2017).

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(2009), Wetzstein (2011), Hempel, Bähr, and Neumann (2014), Richter (2014) and

Salomon (2015).

Rolf Behrens (2003) analyzed German news magazine Der Spiegel reporting during both the First Intifada and the Second (Al-Aqsa) Intifada. Behrens's focus of analysis was the media image of Israel and, in particular, antisemitic stereotypes in the reporting (Behrens, 2003, p. 1, p. 70).

Behrens found a mostly negative characterization of Israel. The dominating image of Israel was that of a "brutal occupation forces, which indiscriminately uses excessive force and suppresses the Palestinian people" (Behrens, 2003, p. 101). Israel was portrayed as responsible for the Palestinian attacks, which it provoked due to their policies (Behrens, 2003, p. 92). The author also criticized that some authors seize antisemitic narratives – especially the characterization of Jews as bloodthirsty and references to the blood libel canard (Behrens, 2003, p. 86, p. 135). There were also occasional comparisons of Israel to Nazi-Germany, which Behrens highlighted (Behrens,

2003, p.94, pp. 145).

Behrens concluded that the (mostly negative) stereotypes were an integral part of

Der Spiegel’s reporting and that the negative image of Israel was mostly purported by leaving out context and background information (Behrens, 2003, p. 101). Comparing the

First to the Second Intifada, Behrens found that during the First Intifada, Israelis were mostly shown as the perpetrators of violence, while during the Second Intifada, these roles were equally distributed between Israelis and Palestinians (Behrens, 2003, p. 118).

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Siegfried and Margarete Jäger (2003) used a critical discourse analysis of articles published by Frankfurter Allgemeine Zeitung (FAZ), Frankfurter Rundschau (FR), Der

Spiegel, Süddeutsche Zeitung (SZ), Tagesspiegel, taz and Die Welt on four major events during the research period, from September 2000 to August 2001.

S. Jäger and M. Jäger found that both Israelis as well as Palestinians were portrayed negatively. Israel, in particular, was characterized as brutal and cold, at times abstracted from humanity as solely an "overwhelming military force" (S. Jäger & M.

Jäger, 2003, p. 343). Antisemitism mostly played a role in the form of (religious) references. In particular, prime minister Ariel Sharon was characterized with references to antisemitic stereotypes (S. Jäger & M. Jäger, 2003, p. 250, pp. 344). Israelis and

Palestinians were often contrasted against each other, in particular the "weak and emotional Palestinians" against the "brutal and merciless Israelis" (S. Jäger & M. Jäger,

2003, 357?). The authors noted that it was conspicuous that Israeli actions were often reported first, even if they were a reaction to Palestinian aggression, which could imply that the Palestinians were only reacting (S. Jäger & M. Jäger, 2003, p. 351).

Langenbucher and Yasin (2009) focused on the production side of news, the journalists. They conducted qualitative interviews with 17 Israel-correspondents of

German news media in 2006 in order to find out “how balanced the news were” and whether “the logic of journalism produces antisemitism” (Langebucher & Yasin, 2009, p.

259).

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The authors come to an ambivalent conclusion. On one hand, the interviews showed that journalistic standards were held highly, according to the journalists themselves. On the other hand, multiple studies of the reporting on Israel showed bias

(Langebucher & Yasin, 2009, p. 274). The authors concluded that they could not safely answer their initial question. They did, however, tried to show that, at least for the most part, the bias in the reporting is not a conscious one, as at least the reporters in Israel are aware of the pitfalls of conflict reporting (Langebucher & Yasin, 2009, p. 275).

Martin Maier (2011) provided another discourse analysis, focused on the reporting in German left-wing press during the 2008/2009 Gaza conflict. Four selected left-leaning newspapers, Junge Welt, Neues Deutschland, Freitag, and Jungle World were analyzed (Maier, 2011, p. 14).

Maier found that the four newspapers could be divided into two groups regarding their reporting on Israel. The first group, consisting of Junge Welt, Freitag, and Neues

Deutschland, fed into a "critical and at times antizionist, sometimes even with antisemitic" discourse (Maier, 2011, p. 156). This group was marked by the usage of antisemitic imagery and comparisons between Israel and the Nazis (Maier, 2011, pp.

158). The Junge World, on the other hand, adopted pro-Israeli positions. The author saw a tendency to prejudge the Palestinians side – or anyone not clearly in favor of Israel, for that matter (Maier, 2011, p. 160). While the newspaper provided a thorough contention with antisemitism and antizionism, it lacked the same depth regarding anti-Arab and anti-

Muslim positions (Maier, 2011, p. 161).

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Maurer and Kempf (2011) provide a qualitative content analysis of five German newspapers – FAZ, FR, SZ, taz, and Die Welt – and compare their reporting during the

Second Intifada and the 2008/2009 Gaza war.

Maurer and Kempf found negativity to be the defining characteristic in the reporting, which affected both parties similarly, most likely due to its role as a news factor (2011, p. 7). In their reporting on the two time periods analyzed, journalists appeared to strike a balance of criticizing both sides while also giving voice to different opinions from both sides (Maurer & Kempf, 2011, p. 7). Comparing the Second Intifada to the 2008/2009 Gaza War, the authors found that during the latter, cooperation-offers, cooperation, and threatening behavior were shown less often on both sides. Israel was also shown as less confrontational (Maurer & Kempf, 2011, p. 8). Victims were reported on more often on the Palestinian side, which, according to the authors, did not constitute a bias but rather "reflects the reality of the number of victims" (Maurer & Kempf, 2011, p. 6, p. 20). Overall, the authors constituted a slight bias to the advantage of Israel.

Irmgard Wetzstein compared the reporting of four weekly print media, the British

The Guardian Weekly, the Austrian Profil, and the two German outlets Die Zeit and Der

Spiegel (2011, p. 201). Wetzstein used a quantitative approach to determine how often

Israeli and Palestinian perspectives were reported, regardless of evaluation (Wetzstein,

2011, p. 176). She found that Der Spiegel reports were somewhat balanced, giving both sides of the conflict approximately the same room, while Die Zeit had a pro-Palestinian and The Guardian Weekly and Profil have a pro-Israeli bias (Wetzstein, 2011, p. 165).

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Furthermore, Wetzstein concluded that the reporting focuses on negativity and problem instead of solution-focused reporting, which affected both sides (Wetzstein, 2011, p.

233).

Gaisbauer (2012) built his research on victimization and responsibility processes during the Second Intifada and the 2008/2009 Gaza war on the previous work by Maurer and Kempf (2011), analyzing the same material (Gaisbauer, 2012, p. 1). Gaisbauer could not, however, confirm the results of the previous study. Contradicting Maurer and

Kempf, Gaisbauer found a slight pro-Palestinian bias (Gaisbauer, 2012, p. 7). This may be due to the focus of the study, which analyzed primarily victimization and responsibility in violent acts. While Gaisbauer did not find any significant differences between different media outlets, he found an increasing convergence of the depictions of the two sides regarding the responsibility-frame across all newspapers when comparing the reporting during the Second Intifada to 2008/2009 (Gaisbauer, 2012, p. 22). The victim-frame, however, takes a pro-Palestinian bias (Gaisbauer, 2012, p. 10).

Hempel et al. (2014) did another explorative study that aimed to identify media frames in the left-leaning Junge World's opinion pieces and the rather right-leaning Die

Welt. The study's goal was to find both similarities and differences in the positions of the two newspapers, as both have a suspected pro-Israeli position. Hempel et al. found that

Die Welt viewed the conflict mostly through the lenses of conflict solutions and local strategic interests, as well as the question of Islamist threats and terrorism (Hempel et al.,

2014, p. 21). The Jungle World focused more on the diversity of actors in Israel, in

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particular Israeli domestic politics (Hempel et al., 2014, p. 22). Both newspapers brought up antisemitism and German historic responsibility to a similar extend. The work's main finding is that there are significant overlaps regarding the pro-Israeli media frames, despite the different political viewpoints of the two newspapers.

Mareike Witte (2014) analyzed the reporting of two German national newspapers

– Frankfurter Allgemeine Zeitung (FAZ) and taz during the First Gaza war (2008/2009) and the Second Gaza war (2012). The main research interest was to find out whether there were differences between the conservative FAZ and the left-leaning taz, as well as if there were differences in the reporting during the two wars. Witte found that Israel was depicted as the aggressor in most cases across the board during the First Gaza war, but less so during the second one. During both conflicts, the taz portrayed Israel more often as the aggressor than the FAZ, but the reporting did become more balanced over time

(Witte, 2014, p. 77). This development was correspondent with an increase of balanced reporting regarding the other dimensions as well during the second conflict (Witte, 2014, p. 70). While there were small differences between the two newspapers, the main differences could be found between the two wars, indicating a shift in the reporting on the conflict, possibly due to improved PR by the Israeli army (Witte, 2014, p. 72, p. 82).

Hagen Troschke (2015) provided a linguistic analysis of Israel's media image in the FAZ, SZ, taz, Die Welt, Der Spiegel, and Die Zeit, particularly regarding the process of “distorting” Israel's role in the Middle East during the 2012 conflict between Israel and

Hamas (Troschke, 2015, p. 256). The author found that solely critical statements – that is,

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"conceptualizations without de-realizing aspects" – are in the minority of the research material (Troschke, 2015, p. 257). The most common conceptualization was Israeli amorality, such as "Israel waged a war due to upcoming elections" (Troschke, 2015, p.

258), Israel as the (sole) aggressor (Troschke, 2015, p. 260), and that Israel injures and kills innocent people (Troschke, 2015, p. 259). Overall, Troschke found a bias against

Israel, in line with previous research on the same media outlets during the same time frame.

The most comprehensive study on the reporting on Israel in the German press to date is provided by Robert Beyer (2016). He focused on the media image purported in

German "quality newspapers" of actors in the Israeli-Palestinian conflict (Beyer, 2016, p.

201). Beyer employed a qualitative-quantitative content analysis, "aiming to integrate linguistic approaches which so far have stood beside communication and media focused approaches," in particular analyzing explicit and implicit evaluations (Beyer, 2016, p.

16). Mostly national newspapers and newsmagazines were analyzed – Die Welt, SZ, FAZ,

Die Zeit, Focus, Der Spiegel, and the regional Nürnberger Nachrichten (NN) (Beyer,

2016, pp. 203) – during an “escalation-free phase of the conflict” from December 2009 to

March 2010 (Beyer, 2016, p. 195, p. 203).

The quantitative analysis of the articles found that there was a strong focus on negativity. Beyer also found an imbalance regarding "perspectivations"; particular

Palestinian perspectives were portrayed significantly more often than Israeli ones, often with a paternalistic view on the events (Beyer, 2016, p. 430). Across the board, Israelis

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were significantly more often portrayed as the aggressors than Palestinians; consequently, the responsibility for de-escalation was often put into Israeli hands as well (Beyer, 2016, pp. 410). Beyer further found that while both Israelis and Palestinians were mostly portrayed negatively, this was much more pronounced for the Israeli side (Beyer, 2016, pp. 41). No significant difference between the newspapers could be found (Beyer, 2016, p. 427). In contrast to previous research, Beyer found mostly explicit evaluations – the majority of which in opinion pieces (Beyer, 2016, p. 567). Most evaluations were done regarding the actions of actors, less so regarding aims and goals (Beyer, 2016, pp. 432).

Beyer did point out that Israeli actors were often criticized in more exposed text positions, for example, two times as often in the headlines as Palestinians (Beyer, 2016, pp. 466, p. 484).

Overall, while Beyer did find a trend regarding negative evaluations of Israel, he could "not find a distinct one-sided bias" (Beyer, 2016, p. 575). Most articles provided a multi-perspective on the conflict, although the mono-perspective articles that could be found mostly favored the Palestinian side (Beyer, 2016, p. 575). Beyer concludes that the major takeaway is that the German view on the Arab-Israeli conflict is marked by a paternalistic view, mostly negative towards both parties, which the Israeli side is hit by slightly harder.

While the studies cited above do differ regarding research method, research period, and research population, the general academic consensus is that there is a tendency to focus on negativity in the Arab-Israeli conflict, which affects Israel more so

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than the Palestinians. The reporting is focused on reports on violence, conflict, and war, potentially skewing the perception of the region. In particular, there is a focus on Israeli military actions, which are portrayed as a powerful, violent force in opposition to weak

Palestinian civilians and radical Islamists. Often, German media takes a paternalist view on the conflict. Explicit evaluations by journalists are few but mostly negative towards

Israel. Antisemitism was very rare and often found implicitly in the form of (religious) references. During the last conflicts, there was a tendency towards a more balanced portrayal of the conflicts compared to previous phases of escalation, which benefitted

Israel's image in the conflict.

The research has focused solely on traditional print media. The emergence of online news media, which has developed in the last three decades in particular with younger audiences is therefore left out of the current research (Hölig & Hasebrink, 2020, p. 23). While traditional media still plays an essential role in the German media landscape, they do so increasingly less in the digital sphere and current research should keep up with this development (Hölig & Hasebrink, 2020, p. 23). Another shortcoming of the current state of research is the focus on times of high conflict between Israel and

Palestinians. This focus may have skewed the results towards negativity, a characteristic that can generally be found in all conflict reporting due to the matter of the reporting.

The goal of this study is to provide a research perspective that accounts for the digital media landscaped, the changing media consumption habits, and that offers an insight into the reporting apart from times of high-intensity conflict. The main question is

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whether the at least decade-old findings for traditional media hold true for the digital news sphere as well – or what differences can be found.

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4. Research Design

The following chapter will present the proposed research design. This will be done in three steps: First, the research topic is translated into research questions and their respective hypothesis. Second, the methodological approach will be explained. Finally, the selection and collection of the research material is laid out, as well as a short summary of the coding process.

4.1 Research Questions

On the basis of the previous research done on the topic in print media discussed in chapter 3, the following research questions will provide the base for the present study.

RQ1 How is Israel portrayed in German online news?

This is the overarching research interest of this study. As such, the question is broken up into more detailed questions, all related to whether there is a tendency in the reporting.

The main question will be whether the results from the previous studies on print media – which mostly stated a negative bias against Israel – hold true for digital news as well.

RQ2 Which topics are dominant in the reporting on Israel?

As previous studies have shown, Israel is often reported on in the context of (military) conflict. As Beyer (2016, p. 48) has stated, this may skew the public's perception of the country due to its association with only conflict.7 However, this can probably be

7 It should be noted that this holds true for the Arab-Israeli relations in general and is not only the case for

Israel but also for their Arab counterparts.

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attributed at least in part due to the research periods chosen in most of the previous studies, which have focused on the Intifadas. The goal of this study is to determine whether this focus on conflict and related topics can be found during a time period with less active conflict as well.

RQ3 What actors are reported on?

This question aims to investigate what individuals and organizations are portrayed as the main actors in the events reported on and how they are portrayed. As described by Beyer

(2016, p. 392), pp. 567), there was a tendency to focus on a small number of individuals in the reporting. This can lead to a skewed perception of a topic or region, as these individuals are portrayed as the sole embodiment of a region or a topic.

RQ4 What actors are quoted in the reporting?

Which actors are given an audience in the reporting and how do they evaluated Israel and

Israelis? While evaluations in news articles should – apart from types of texts which are explicitly opinionated – lack partisanship, a bias can form if other actors are quoted overwhelmingly with a tendency, either positive or negative.

RQ5 Are the depictions of events in the headline and the text body coherent?

What tendencies can be found?

Beyer found that Israel was depicted particular negatively in the headlines, even if those depictions were contradicted later in the text body (2016, pp. 512). This could lead to a skewed portrayal in particular through social media, especially as headlines and teasers become increasingly important as micro-news consumption increased through social

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media (Lee & Chyi, 2015; Wohn & Ahmadi, 2019). The goal is to determine whether the news reports offer the same portrayal of the events in the headline, the teaser text, and the main body. Additionally, the aim is to analyze the tendencies, if there are any.

RQ6 Which intermedia tendencies can be found across different media outlets?

The interest here lies in whether there are overarching tendencies between the publications in their portrayal of Israel. As most of the studies in the literature review did find some differences between the different newspapers researched, the goal is also to examine whether the same holds for online news and what exactly those tendencies are.

4.2 Hypotheses

The goal of the research proposed here is not only to make descriptive statements about the occurrence of certain features– though this is necessary for some research questions – but also to find representative and statistically valid results on the correlation of properties in the texts. In order to do so, it is necessary to transform the research questions into hypotheses that can be tested empirically. These hypotheses will then be analyzed with the statistical methods of variance analysis and t-tests. The following hypotheses are mostly derived from the results of the previous studies on the portrayal of

Israel in German print media (see chapter 3), with the goal to find out whether the general tendencies can be found in digital news as well.

The null- and alternative hypotheses derived from the hypotheses below can be found in Appendix B (pp. 154).

H1 Israel is mostly mentioned in the news in the context of negative developments.

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H1.1 The predominant theme of the reporting is conflict/military action.

H1.2 If responsibility for negative development is located, it is Israeli

responsibility.

H2 Actors who appear in the reporting are predominantly not Israeli.

H2.1 If Israeli actors appear in the news, they are evaluated negatively.

H2.2 Israeli actors are only evaluated negatively in the context of conflict; if they

appear in another context, they are evaluated positively.

H3 In times of conflict with Palestinians, Israeli actors are quoted more often than their

Palestinian counterparts.

H3.1 If an Israeli actor is quoted to the advantage of Israel, another actor is quoted

to challenge that.

H3.2 If an actor is quoted to the disadvantage of Israel, this is not countered by an

opposed opinion.

H4. The headlines, teaser text, and text body are usually not contentual coherent.

H4.1 If headlines, teaser text, and text body are not contentual coherent, it is to

the disadvantage of Israel.

H4.2 If there is no contextual coherence, the headlines portray Israel more

negatively than the teaser text and text body.

H5 The reporting on Israel has a negative bias.

H6 There are no substantial differences between the different media outlets regarding their reporting on Israel.

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4.3 Methodology

The research questions described in chapter 4.1 can be simplified into three main interests: (1) what the texts are about, (2) how the content is presented, and (3) who is given a voice in the reporting. A content analysis is the most fitting choice in order to answer these questions.

As Merten (1995) has laid out, content analysis is "a method to survey social reality by deducting characteristics of non-manifest context from characteristics of manifest text." (Merten, 1995, p. 15). The research object of a content analysis can mean all manifest communication, from text to audio to visuals and everything in between. As long as the research object can be manifested in some way, it can be analyzed by content analysis. The goal of a content analysis is to interfere from the manifest content on some other, non-manifest context, usually some characteristic of the communicator, the recipients, or the communication situation (Merten, 1995, p. 16, p. 119). The research at hand falls under the former category. While the goal is to provide some insight into the broader German media landscape, the analysis itself is focused on a comparison of the selected media outlets as described above. The aim is to find out if there are underlying tendencies – and thus, potential bias – in the German online media regarding Israel.

Content analysis methods can be broadly categorized into qualitative and quantitative approaches, as well as mixed ones that incorporated aspects of both (Früh,

2017, p. 66). The advantage of qualitative analysis is that it usually provides a more in- depth insight into the individual texts. In contrast, the quantitative approach is better

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suited to analyze larger quantities of text systematically.8 Mixed-methods employ aspects of both methods but at the cost of a more considerable effort, which may not always be feasible (Früh, 2017, p. 66). In practice, the lines are not as clear-cut, and qualitative content analysis usually utilizes aspects of qualitative methods and vice versa. Some degree of quantification is often helpful in qualitative research, just like a certain interpretative flexibility is often necessary when developing codes for a quantitative analysis.

Given the underlying research questions and correspondently the amount of material that is to be analyzed, the work at hand will lean toward a quantitative approach.

Quantitative content analyses have been well established as a method in media analysis in order to quantify large amounts of data, such as texts.

The specific type of content analysis used here will be a structural objectivity analysis [Strukturelle Objektivitätsanalyse] as defined by Merten (1995, pp. 239). This approach includes not only formal factors to analyze media reality but adds the additional dimension of evaluations (Merten, 1995, p. 239).

The goal of the structural objectivity analysis is to measure the objectivity of reporting. As a starting point, however, the approach does not take a perceived “true”

8 Comprehensive discussions about the advantages and disadvantages of qualitative and quantitative approaches can be found, for example in Creswell (2013), Denzin and Lincoln (2017), Döring and Bortz

(2016), Häder (2019), Hammersley (2012), Merten (1995), Neumann (2006), Shepris, Young and Daniels

(2010), or Vanderstoep and Johnson (2009).

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reality (which, as discussed in chapter 2, is problematic; Merten, 1995, p. 240). Instead, the goal is to compare the reporting to itself and other media. This is one of the main advantages of this approach, since the norm is not defined a priori – and therefore potentially subjected to bias itself – but is derived from the material itself (Merten, 1995, p. 242).

According to Merten, there are four types of selection in reporting which can lead to bias (1995, p. 239):

1. Total selection: The suppression of statements and events.

2. Formal selection: Constructing bias through attention by preferable

presentation.

3. Contentual selection: Constructing bias through information selection.

4. Selection through contentual-verbal and contentual-nonverbal evaluations.

These selection processes can only be viewed in comparison to other media. The norm for objectivity is not defined by the researcher but instead constructed from the sample. A total mean score is generated across all media outlets from a representative sample for every variable gathered. This mean score is then used as the default value in order to compare the individual manifestations. Comparisons can be made between different media outlets as well as intra-media, e.g., regarding the valency on specific topics or during different time periods (Merten, 1995, p. 239). Evaluations can be not only coded blanketly regarding subject and valuation but can be coded as closed communicative acts

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and further analyzed, in particular regarding topics and subject (Merten, 1995, p. 240, see also Beyer, 2016, pp. 208).

As such, the structural objectivity analysis provides the appropriate tool to analyze media reality. In accordance with the constructivist approach laid out in chapter 2, the comparison of the media outlets is made on the basis of the media content itself and not a pre-decided truth, and it is, therefore, the appropriate methodology to answer the question posed in this research: How is Israel portrayed across different German digital news media?

4.4 Data Collection

The time frame for this research is September 1st, 2019, to December 31st, 2019.

As the emergence of the COVID-19 pandemic has dominated the news cycle since the beginning of 2020, there is a good reason to believe that including the pandemic – or parts thereof – in the research period would skew the results, as news media focused heavily on the national and international responses to the virus and adjacent topics.

Although a more recent sample would have been preferable, the extraordinary events of the global pandemic make it necessary to choose an earlier sample.

Additionally, the timeframe has to be fairly constricted, as there are practical limitations for the amount of material that can be analyzed. While a more extended research period can provide more reliable results, as singular events do not weigh in as much, a tough decision had to be made. Given this research's scope and its limited resources, a timeframe too small might skew the results, while a timeframe too broad

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would simply not be feasible in a thesis work such as this. A more concise timeframe also allows for more media outlets to be included without including an unrealistic number of cases to be coded. A broader comparison may provide a more comprehensive overview of the German (digital) media landscape, thus aiding to answer the initial research question more thoroughly.

The four-month-long research period is a time of low-escalation in the Arab-

Israeli conflict and was chosen to provide a view on Israel’s media image apart from active military conflict, as discussed in chapter 3. For this purpose, low-conflict was defined as times in which no major military operations by either side took place. Major military operations were defined as actions by military forces are publicly addressed as mid- or long-term engagements, such as the Intifadas, the 2012 or the 2014 Gaza wars.

Five news outlets were chosen for analysis – Bild.de, n-tv.de, Spiegel Online, t- online, and Zeit Online. These outlets were chosen as they have the largest reach among the German population, offer text-based news, and had an approximately similar number of articles on Israel (Hölig & Hasebrink 2020, p. 27).9

9 Tagesschau.de, which scored as the website with the second-highest reach among the German audience, was excluded due to its focus on video formats. While Tagesschau.de also does offer some text news, these are usually only to accompany videos and were overall too few during the research period to offer empirically sound results. Similarly, Focus.de was excluded due to the small number of articles during the research period. Web.de and Gmx.de were also excluded to the similarity to t-online, as all three are (among other services) email provider which primarily use news agencies for their coverage although they do have

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Bild.de (in the following called Bild) is the online format of German tabloid Bild.

The daily print version has the largest circulation in Germany, while the online format is ranked fourth by reach (Milosevic, 2016, p. 58; Hölig & Hasebrink 2020, p. 27). Bild’s style of reporting is characterized by short articles and often a polemic choice of language. Bild offers a premium service, which includes additional articles. The Axel

Springer publishing house, which owns Bild, states its support for “the Jewish people and the right of existence of the State of Israel” as one of its key company principles and values (Axel Springer SE, 2021).

n-tv.de (in the following called n-tv) is the website of German TV news channel n-tv. While originally a visual format, the website features mostly text-based news. It is particularly popular with mobile users. All articles are free to access.

Spiegel Online (in the following called Spiegel) is the website of German weekly news magazine Der Spiegel. The print version and the website had independent editorial teams until September 1st, 2019, when the two merged; the content of both is now managed by the same editorial team. Spiegel has the largest reach of any German news website. Der Spiegel has been criticized in the past for being allegedly biased against

Israel in its reporting.10 Spiegel offers a premium service that includes additional articles.

original reporting). Finally, local news websites were excluded; while these collectively have a larger reach than Zeit Online, the individual publications do not.

10 In one instance in 2018, which sparked research question 5, the website failed to mention in both the headline and the lead that a Palestinian man whom Israeli soldiers killed was in the process of committing a

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t-online.de (in the following called t-online) is a German news and entertainment website which also features an email-service. Originally owned by German telecommunications company Telekom, the news website was sold in 2015. While most of the news content is sourced by news agencies, the website also does offer original journalism. All content on the website is free to access.

Zeit Online (in the following called Zeit) is the online service by German weekly newspaper Die Zeit. The editorial team of the website is independent of the print editorial team, although some articles from the print version are later published online. Zeit is, in particular, focused on political news and background reports. Similar to Bild and Spiegel, the website offers a premium service with additional articles.

Included in the sample were all articles published in the news outlets which mention Israel either in the headlines, the teaser, the main text or keywords where applicable. The goal was also to have at least 100 articles per publication in the sample.

During the research period, a total of 1049 articles from the five news outlets were collected for analysis. The sample includes articles that can be accessed for free on the websites, as well as articles behind a paywall.

terrorist attack when he was shot, implying the man had been attacked for no reason (Weinthal, 2018, June

29).

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4.5 Coding

Articles which met the criterion for collection were download as whole webpages.

Coding was done according to the codebook, which can be found in Appendix C (pp.

159) during a two-week period in January 2021.

The codebook was developed on the basis of the previous studies done on the topic (see chapter 3), using mixed deductive and inductive approach. The study by Beyer provided the foundation for the codebook (2016, pp. 602). From this starting point, a category scheme was developed for the research questions and hypotheses specific to the study at hand. Multiple test codings were then conducted and categories were added inductively were necessary. Additionally, open categories were introduced for each general category to allow for manifestations not accounted for in the development process.

A major challenge for single-researcher content analysis, in particular when the coder is the researcher – such as in this case –, is the question of validity and reliability.

As Potter and Levine-Donnerstein discuss, subjective interpretation always plays a role to some extend when analyzing latent content patterns (1999, p. 260). This can be problematic for single-rater approaches, as it challenges the reliability of the codings.

While detailed coding instructions and tight definitions can limit the impact of the coder subjectivity, they cannot entirely prevent it. On the flip side, the single-rater approach can be advantageous for the validity of the codings, as the coder is very familiar with the definitions and the theoretical background of the categories.

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While it’s not possible to determine an intercoder-reliability in these cases, it is possible to test the intracoder-reliablity via repeated testing with some distance of time.

This was done on 50 articles, which were coded twice with a one-week time lag. A

Krippendorff’s Alpha reliability estimate (see Hayes & Krippendorff, 2007) was then used to compare the first to the second coding. The reliability-coefficient of α = .98 showed an acceptable result, as both tests provided reliably the same codings.

Coding was done using Microsoft Excel 2020 and, where necessary, MAXQDA

2020. Excel was chosen due to its ease of use and compatibility with SPSS, the program used for the statistical analyses. MAXQDA was chosen as it allows to code material in a transparent and replicable way, in particular for complex articles.

The coding process consisted of three reads of the news article: A first read to get a general overview of the article, after which the formal categories were coded directly in

Excel. This read was also used to determine whether MAXQDA should be used for further coding, which was the case when many actors appeared in the article or many different quotes were found. A second, thorough read was then done to code the main contentual variables, going through the article sentence by sentence and then coding the variables in order, cross-referencing the text where necessary. In cases where MAXQDA was used, the text of the article was transferred into a MAXQDA text file, and coding was done using the program's coding system. After coding in MAXQDA, the data was then transferred into the Microsoft Excel coding sheet. In a final step, the coding sheet

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was checked for any missing variables, which may have slipped through in the initial coding.

For the analysis, the Microsoft Excel file, which contained the coding sheets, was imported to IBM SPSS 24. The variables were then defined according to the codebook.

Another check for missing or incorrect variables was then performed, and recoding was done where necessary.

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5. Results

In the upcoming chapter, the results of the analysis are presented. First, the collected material is described, as some of the initial research questions are already answered by descriptive statistics. The hypotheses which were presented in chapter 4.2 will be discussed afterward in subchapters that focus on specific aspects of the analysis.

Additional findings, which were not covered by the hypotheses, can be found in chapter

5.3.

Unless noted otherwise, the testing was done without weighting the cases according to their relevance factor.

5.1 Structure of Material

During the research period, between September 1st, 2019 and December 31st,

2019, a total of 1049 articles were collected according to the criterion that they do involve the word “Israel,” either in the headline, the text, or as a keyword.

A total of 487 articles are excluded due to not being relevant to this research. Out of these, 63 were excluded due to not referencing the state of Israel at all, mostly due to mentioning people with the name “Israel,” referring to people of Jewish belief as the

“People of Israel” or “Israelites,” or simply wrong keywording by the news outlets.

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Further 424 cases were excluded due to only minorly mentioning of Israel or Israelis.11

Table 1 shows the distribution according to the relevance of the article to the media image of Israel.

Table 1

Relevance of Articles in the Sample

All Cases Relevant Cases Relevance n Percent n Percent No Relevance 63 6.0% Minor Mention 424 40.4% Secondary Theme 207 19.7% 207 36.8% Main Theme 355 33.8% 355 63.2% Total 1049 100% 562 100%

This left 562 cases which either had Israel as the main topic of the article (355 cases) or as a secondary theme (207 cases) for the quantitative analysis. In the further description of the material, only these cases defined as relevant will be referred to as the main sample.

11 For example, this was often the case when referring to the state of Israel as an example, when referencing experts from Israel ("Researchers from Israel found…") or when mentioning the schedule for the UEFA

Euro Soccer cup qualification matches.

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5.1.1 Publications and Relevance

The number of articles published during the research period was between 92 and

131 throughout the different outlets. The most articles on Israel and Israelis were published by t-online (131 articles), while the least were published by Bild (92 articles).

This difference becomes even more apparent when comparing the relevance of the articles.

Figure 1

Distribution of Israel as a major and minor theme in the articles

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Bild is also the only publication which published more articles that referenced

Israel as a secondary theme than as the primary theme.

Spiegel and n-tv both clocked in at 119 articles, while Zeit published 101 articles during the research period, all of which with a similar ratio of main theme articles to secondary theme ones.

The goal to have a minimum of 100 articles per news outlet was therefore reached with the exception of Bild. Due to practical reasons, the research period could not be extended further. Since only one of the publications did not meet this requirement, the analysis proceeded as planned.

For the testing of some hypothesis, the cases were weighted according to their relevance, in order to account for the higher impact of articles which focus primarily on

Israel versus articles which only briefly cover Israel. Articles which focused on Israel and

Israelis as the main topic were weighted by the factor 2 to account for their higher impact on the media image. Weighting has an attached risk of skewing the results, but can provide more defined results when done carefully and consciously (see Lavallée &

Beaumont, 2015).

5.1.2 Sections

Regarding the section in which articles were published, the section Politics

("Politik") is dominant with 370 articles published in it, over half of the articles in the sample. Daily summaries, usually in the form of morning or evening briefings, come in second at 49 cases; it should be mentioned that these daily summaries often cross-

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referenced articles in other sections. Surprisingly, the local news section comes in third at

42 articles. Articles in this section were only published by t-online and Bild and can be mostly attributed to local politics, in particular local politicians’ statements as well as antisemitism in reference to Israel. Two articles were not assigned to a section. Table 2 shows the frequencies at which the sections could be found in the sample.

Table 2

Frequencies of Sections in the Sample

Section Frequency Percent Valid Percent Valid Politics 370 65.8% 66.1% Daily Summary 49 8.7% 8.8% Local News 42 7.5% 7.5% Sports 25 4.4% 4.5% Culture 24 4.3% 4.3% Panorama 16 2.8% 2.9% Gesellschaft 8 1.4% 1.4% Economy/Business 7 1.2% 1.3% Science 4 .7% .7% Religion 4 .7% .7% Entertainment 3 .5% .5% Other 8 1.4% 1.4% Total 560 99.6% 100% Missing Not Applicable 2 .4% Total 562 100%

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Table 3 shows the frequencies in which sections articles were published per publication. Zeit is in some aspects an outlier, as they include a lot more sections than the other news outlets, which are often less clear-cut and more general. "Gesellschaft"

(society), for example, combines different aspects of current events, background information, history, and opinion. The section for religion, on the other hand, is much more straightforward but can also only be found in the Zeit. Sections that only appeared once or twice are summarized under "Other." These include sections such as "Leben"

(Life), Work/Career, and Advise.

Table 3

Frequencies of Sections per Publication

Publication Section Bild n-tv Spiegel t-online Zeit Total Politics 65 63 81 85 76 370 Daily Summary 0 41 8 0 0 49 Local News 13 0 0 29 0 42 Sports 9 4 4 7 1 25 Culture 0 0 15 0 9 24 Panorama 0 6 6 4 0 16 Gesellschaft 0 0 1 0 7 8 Economy/Business 0 4 0 0 3 7 Science 0 0 2 0 2 4 Religion 1 0 1 0 2 4 Entertainment 0 0 0 3 0 3 Other 3 1 0 3 1 8 Total 91 119 118 131 101 560

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5.1.3 Types of Text

The most prominent type of text across all news outlets in the sample is the news report. This was somewhat to be expected, as it is the more general type of news article.

Newsflashes – short updates on current developments – were the second biggest group, although highly dependent on the news outlet. Newsflashes were mostly found at n-tv and

Bild, while they were much rarer at Spiegel and t-online; Zeit published only one during the research period. All other types of texts were generally relatively evenly spread out, with mostly low numbers. Table 4 provides an overview of the different outlets, including percentages for the each (see Appendix D, p. 189, for the table with more detailed breakdown). Features were most prominent in Spiegel and Zeit, both of which could draw on material from their weekly print edition. Bild, also offering a daily print version, also published features, although to a much smaller extent, while none could be found in the exclusively online outlets n-tv and t-online.

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Table 4

Types of Text per Publication

Publication Type Bild n-tv Spiegel t-online Zeit Total Newsflash n 11 37 9 6 1 64 % 12% 31.1% 7.6% 4.6% 1% 11.4% News Report n 67 78 88 121 70 424 % 72.8% 65.5% 73.9% 92.4% 69.3% 75.4% Feature n 1 0 5 0 6 12 % 1.1% 0% 4.2% 0% 5.9% 2.1% Opinion n 5 1 2 2 4 14 % 5.4% .8% 1.7% 1.5% 4% 2.5% Interview n 3 2 5 1 3 14 % 3.3% 1.7% 4.2% .8% 3% 2.5% Other n 5 1 10 1 18 34 % 5.5% .8% 8.4% .8% 16.9% 6% Total n 92 119 119 131 101 562 % 100% 100% 100% 100% 100% 100%

t-online in particular stood out with over 90% of the texts published being news reports; this can be attributed to the high number of news agency reports, which were often published with minimal editing (see chapter 5.1.5 for further examination of this).

This may also explain the small variety of types of texts found at t-online.

Bild provided the most opinion pieces on the issue, which is in line with its self- description as an opinion-forming news platform.

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5.1.4 Lengths of Articles

On average, the texts in the sample were 494 words long. The shortest text can be found at n-tv, which had a mean length of 349 words. This is in line with the high number of newsflashes at n-tv. By far the longest articles could be found at Zeit, which had a mean of 810 words per article. It should be noted though while Zeit did generally have longer articles, the mean is also heavily influenced by a few extremely long articles of up to over 7500 words. Subsequently, Zeit has the highest standard deviation at 1100 words.

When comparing the median length of the articles in the publications, the general trend could also be found for the publications, although less pronounced. An overview of the average length and the mean of the articles in the news outlets can be found in table 5.

Table 5

Mean Length of Article per Publication

Publication Mean Median n Std. Deviation Bild 391.03 295.5 92 270.364 n-tv 348.90 285 119 294.543 Spiegel 532.92 387 119 422.369 t-online 419.79 384 131 245.082 Zeit 809.86 426 101 1101.633 Total 494.13 357 562 568.901

Bild, n-tv, and t-online are all relatively similar regarding the length of the articles, with 391 (Bild), 349 (n-tv), and 420 (t-online) words on average per article.

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Spiegel had longer articles on average (533 words), although similarly to Zeit, the standard deviation was also higher.

5.1.5 Sources

Up to three sources could be coded per article and no articles had more than those three; 230 articles did not mention a source.

The most prevalent news agency is dpa, which was used in 291 of the 562 articles. AFP comes second at 98 articles, while Reuters (23) and AP (19 articles) were used much less. Two special-interest agencies, KNA (1 article; Katholische Nachrichten-

Agentur [Catholic news agency]) and sid (3 articles; Sport-Informations-Dienst [sports information service]), were rarely used and only for their respective fields – religion and sports.

Interestingly, there was a strong difference between the news outlets regarding their usage – or mentioning – of sources. Table 6 shows the sources per news outlet. Bild almost exclusively did not use any source in their reporting, with only two cases in which a news agency was credited. It’s unclear whether Bild does not use or does not credit the sources they use. T-online used agency sources in almost all of their reporting. Spiegel and Zeit also had the most extensive variety of sources used, which may be a holdover from their print formats.

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Table 6

News Agency Credits per Publication

Publication Agency Bild n-tv Spiegel t-online Zeit Total AFP n 0 25 26 9 38 98 AP n 0 0 3 0 16 19 dpa n 2 62 52 124 51 291 REUTERS n 0 3 5 4 11 23 KNA n 0 0 0 0 1 1 sid n 0 1 2 0 0 3 Total n 2 74 63 128 65 332 Note. Up to three news agencies were coded per article.

5.1.6 Topics in the Reporting

The most prominent topic in the reporting on Israel in the sample is by far Israeli internal politics. This can in part be attributed to the ongoing political crisis in Israel, which had led to multiple elections in the past four years, of which one election took place during the research period.

Table 7 shows the frequency of selected topics across the different news outlets.

A detailed table can be found in Appendix D (pp. 190). Bild is the news outlet which reported the least on Israeli politics, with 16 cases – half of the second least, Zeit, which published 35 articles on the issues; the other news outlets published between 46 (t-online) and 53 (Spiegel) articles on this issue, with n-tv being in the middle at 47 articles.

Interestingly, Bild reported much less on Israeli settlements than the other news

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outlets, providing only four articles in this regard. In contrast, Zeit and t-online published

9 and 11 articles on the matter, while Spiegel (18 articles) and especially n-tv (25 articles) focused on this topic. Similarly, Bild reported almost two times as much on Palestinian military acts (16 cases) than on Israeli military operations (8 cases), a relation which was usually reversed for the other news outlets, though to a much lesser extent.

Table 7

Frequencies of Selected Topics per Publication

Publication Topic Bild n-tv Spiegel t-online Zeit Total Israeli Internal Politics n 16 47 53 46 35 197 Other Israeli Affairs n 15 22 15 15 17 84 Antisemitism in n 22 5 8 16 16 67 Germany/Holocaust Other German Affairs n 43 11 21 14 7 96 Arab-Israeli Conflict n 10 17 14 15 10 66 Israeli Military Action n 8 16 14 15 13 66 Palestinian Military Action n 16 11 13 12 13 65 Settlements n 4 25 18 11 9 67 Other Topics n 31 33 55 52 37 208 Total n 165 187 211 196 157 916 Note. Up to three topics were coded per article.

5.1.7 Actors in the Reporting

Up to five main actors were coded for each article. An actor was coded only once per article, even if the actor was mentioned multiple times. If more than five actors were

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presented in an article, the five actors which were mentioned the most often or where given the most room in the reporting were coded. Table 8 shows the distribution of the most common actors in the reporting. A detailed breakdown can be found in Appendix D

(pp. 192).

Table 8

Frequencies of Most Common Actors per Publication

Publication Actor Bild n-tv Spiegel t-online Zeit Total Israel/Israeli n 135 219 235 248 203 1040 Germany/German n 109 34 58 67 40 308 Palestine/Palestinian n 48 32 41 45 36 202 Other Arab Actor n 11 23 17 22 18 91 Iran n 10 10 16 14 17 67 European Union n 8 13 9 6 7 43 USA n 8 12 17 16 17 70 International Actor n 14 4 28 19 16 81 Other Actor n 5 12 13 9 7 46 Total n 348 359 434 446 361 1948 Note. Up to five actors were coded per article.

In line with the focus on politics, the most prominent individuals are politicians, particularly prime minister Netanjahu and politicians of the opposition. This finding fits well into the focus on the Israeli election, which did constitute a large portion of political reporting during the research period. The focus on Netanjahu has been found in previous studies as well (Beyer, 2016, pp. 386, p. 566) and should not come as much of a surprise

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during an election. In particular, Netanjahu appears only 27 times more often than politicians of the opposition (although it should be noted that this includes multiple politicians of the opposition), generally giving a relatively balanced impression. The notion that Nethanjahu as an individual is often reported on as the personification of

Israel, as Beyer described it (2016, pp. 504), cannot be confirmed here. While Netanjahu certainly is the prominent figure in the reporting, the multifacetedness of the Israeli political landscape is also represented.

The Israeli army (IDF/IAF) is the third most prominent actor, appearing 95 times in articles. While a research period of low-intensity conflict was chosen, there were still skirmishes between Israeli security forces and Palestinian groups as well as with the

Lebanese Hezbollah and the Syrian army. While the Israeli army is more prominent than the other groups, this can be attributed to the fact that this is one actor opposed to multiple parties in the conflict, sharing the distribution between them. In fact, when combining the different Palestinian groups (Hamas, Islamic Jihad and unspecified groups), these were mentioned more often than the IDF/IAF.

Surprisingly, the USA also played a large role in the reporting, being mentioned in 70 articles. This can in part be attributed to the news factor eliteness, as actions and comments by US politicians and officials are more likely to be reported on. One event in particular which shaped the reporting were comments on the legality of Israeli settlements by US politician Mike Pompeo. These comments sparked some controversy and were commented on by multiple actors not only in the region but internationally.

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Overall, however, the fact that the US is this prominent in the reporting bears witness to its role in the international community and its influence in international politics.

Iran also played a prominent role, appearing only slightly fewer times than the US at 67 times. In fact, Iran is the most prominent actor of the non-Palestinian actors in the region which were reported on. The background of this is at least partly the Joint

Comprehensive Plan of Action, better known as the Iran Deal, an agreement which aimed to create a framework for the Iranian use of civil nuclear power and end its development of nuclear military capabilities, from which the US withdrew in early 2018. While this agreement came to be between the permanent members of the UN Security Council,

Germany and Iran – and as such, not Israel – it did play an important role for Israel due to

Iranian eliminatory rhetoric towards Israel and the Israeli opposition to the agreement. As such, the Iranian-Israeli conflict often played an important role in the reporting on the end of the agreement and Iran's subsequent reaction to the US' withdrawal.

Generally, there were few significant differences between the different news outlets regarding which actors appeared in the reporting. Some worth mentioning is the focus of n-tv on business-topics, which lead to n-tv mentioning Israeli businesses 17 times in its articles, while these were relatively rare in the other news outlets. German local politicians were also mostly found in articles by Bild and t-online, which is supported by the focus of the two outlets on local news (as described in chapter 5.1.2).

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5.1.8 Quotes

Quotes were gathered in four groups – Israelis, Germans, Palestinians, and other actors. The total number of quotes from actors from that group – with quotes being both direct and indirect speech – was then coded into the variable for the respective group. In a second step, the type of actors who were quoted was coded, which will be discussed in chapter 5.1.9. Table 9 shows the mean quotes per article for the different news outlets.

Table 9

Average Number of Quotes by Country per Publication

Publication Quoted Party Bild n-tv Spiegel t-online Zeit Total Israel 1.48 1.42 1.49 1.53 2.20 1.61 Palestine .27 .16 .17 .21 .20 .20 German 1.63 .48 .90 .54 1.23 .91 Other .37 .48 .60 .69 1.04 .64

Overall, no significant differences between the news outlets could be found. Bild is the only outlet in the sample which had more Germans quoted in the articles on Israel, which may relate to their high number of articles with Israel as a secondary topic compared to the other outlets (see chapter 5.1.1). Zeit had the highest number average of quotes by Israelis at 2.2 per article, while the other news outlets had around 1.5 per article. Palestinians were quoted much less in the context of Israeli matters. What does

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become apparent in the sample, though, is that Israelis are indeed the prominent quoted actors in the reporting about Israel – at least with the exception of Bild.

5.1.9 Quoted Actors

When taking a look at what type of actors specifically were quoted, the tendencies found in the actors of the reporting are continued. Table 10 shows the types of the most common quoted actors and how often they were quoted in each news outlet. A detailed breakdown can be found in Appendix D (pp. 195).

Table 10

Frequency of Quoted Actors per Publication

Publication Actor Bild n-tv Spiegel t-online Zeit Total Israeli n 54 98 90 129 87 458 German n 84 22 34 50 30 220 Palestinian n 15 19 14 23 15 86 Other Arab n 6 13 10 16 17 62 European Union n 0 6 5 3 2 16 International Actor n 4 2 12 10 9 37 Other n 7 17 14 22 13 73 Total n 170 177 179 253 173 952 Note. Up to five quoted actors were coded per article.

Interestingly, the total number of quoted actors is similar in all publications but t- online.

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In line with the finding regarding the prominent actors, Israeli politicians were quoted the most overall (see Appendix D, pp. 195). Bild once again stood out compared to the other outlets, as politicians were quoted much less – 14 times – only a third of the numbers which could be found in other outlets (n-tv: 41; Spiegel: 43; t-online: 69: Zeit:

44). On the other side of things, Bild did quote German politicians the most, again in line with the depiction of actors in the reporting. Israeli security forces were quoted second most often at 83 times. This is particularly interesting as Palestinian armed groups and

Hezbollah were quoted much less, indicating that information about conflict was mostly taken from the Israeli official sources. It should be considered, though, that the groups active in the conflict during the research period – Hamas, Islamic Jihad as well as

Hezbollah – were and are designated as terrorist groups in Germany, which may lead to hesitation to source information from them.

5.2 Hypothesis Testing

In the following chapter, the results of the statistical testing of the hypotheses presented in chapter 4.2 are laid out. This is done in order of the hypotheses where possible, although in some cases the underlying research questions overlap. The results found in this chapter as well as additional findings are then discussed in chapter 6. Only the relevant tables will be included in the text, sometimes as summarized or combined tables. The full tables, as put out by SPPS, can be found in Appendix E (pp. 197).

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5.2.1 Israel in the News

The first three hypotheses H1 to H1.2 are concerned with the question of when and in which context Israel appears in German online news. The goal is to answer this question by looking at what kind of developments are reported on, which topics are prevalent in the reporting – or rather, as an overview has already been given in chapter

5.1.6, the respective hypothesis poses the question of whether conflict is as much of a dominant topic during low-conflict periods as a previous study has pointed out (Beyer,

2016, p. 386). Additionally, the question of whether Israel is portrayed as responsible for the developments in the news will be analyzed. The latter had been stated by Gaisbauer

(2012) and Beyer (2016). Gaisbauer had found that during the First Intifada in particular,

Israel was portrayed as overwhelmingly responsible for escalation, while the responsibility-frame became increasingly shared between Israelis and Palestinians during the Second Intifada (2012, pp. 21). Beyer had criticized that in 2009, Israel was portrayed as responsible for negative developments, while other actors were portrayed as responsible for positive developments, providing a one-sided image of the region and

Israel in particular (Beyer, 2016, pp. 410). The hypothesis will be analyzed in order and a summary of the procedure will be provided.

H10 Israel is mentioned evenly in the context of different developments

H1a Israel is mentioned mostly in the context of negative developments

For each article, how the event which is reported on is portrayed was coded. The valency of the development is closely related to the news factors which play into the reporting as

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well as the nature of the event itself – or rather, how it is framed in the reporting. This variable was coded on a three-step Likert-scale and is as such an ordinal scale, ranging from -1 (negative development) to +1 (positive development).

In order to analyze how the developments of the news were portrayed in the sample, a frequency table with percentages per row was utilized, as can be seen in table

11.

Table 11

Frequencies of Developments in the Sample

Type of Development n % Positive 69 12.3 Ambivalent/Stagnation 200 35.6 Negative 293 52.1 Total 562 100

More than half (52.1%) of the articles in the sample period focused on negative developments. This compares to 35.6% of ambivalent and stagnant developments and only 12.3% of positive developments. With over half of the overall events reported on being of the negative kind or at least portrayed as such, it appears that the news outlets in the sample do have a strong focus on negative developments. This finding, however, should be considered with the general nature of news reporting in mind, which often focuses on negative events (Bohle, 1986).

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A comparison between the different news outlets was made using a crosstable, comparing the rows' percentages with a Z-test (p-value adjusted per Bonferroni-method; see table 12). No significant differences between the news outlets could be found (p >

.05). Overall, the portrayals of the developments were evenly spread between the different outlets with similar percentages.

Table 12

Valencies and Distribution of Development per Publication

Publication Development Bild n-tv Spiegel t-online Zeit Total Positive n 14 14 15 14 12 69 % 15.2% 11.8% 12.6% 10.7% 11.9% 12.3% Ambivalent/ n 26 44 41 52 37 200 Stagnation % 28.3% 37% 34.5% 39.7% 36.6% 35.6% Negative n 52 61 63 65 52 293 % 56.5% 51.3% 52.9% 49.6% 51.5% 52.1% Total n 92 119 119 131 101 562 % 100% 100% 100% 100% 100% 100%

Interestingly, Bild both had the highest percentage of negative developments

(56.1%, compared to the overall percentage of 52.1%) they reported on as well as the highest percentage of positive developments (15.2% compared to 12.3%), indicating that

Bild is more likely to provide an evaluation of the events than other outlets. On the other side of the spectrum, t-online focused more on a stagnant and ambivalent portrayal of the

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events, with the highest percentage (39.7%) in this category and the lowest in both positive and negative developments.

It is important to note that despite this difference in the tendency to provide an evaluation of the development of the event which is reported on, the mean development was astonishing similar for all of the news outlets, as can be seen in table 13.

Table 13

Mean Valency of Development per Publication, Not Weighted

Not Weighted Weighted Std. Std. Publication Mean n Deviation Mean n Deviation Bild -.41 92 .744 -.42 132 .731 n-tv -.39 119 .692 -.42 203 .665 Spiegel -.40 119 .705 -.45 204 .675 t-online -.39 131 .675 -.42 212 .652 Zeit -.40 101 .694 -.45 166 .665 Total -.40 562 .697 -.43 917 .673

An ANOVA-test also confirmed no significant differences between the news outlets (F [4, 557] = .018, p = .999).

Additional testing was done with weighted cases, which can also be seen in table

13. Cases that had had the highest relevance – cases in which Israel was the main topic – were weighted by factor two, while cases in which Israel was a minor topic were

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weighted by factor one. Still, no significant differences between the news outlets could be found (F [4, 912] = .091, p = .985).

While the differences between the outlets did not change significantly, it should be noted that the evaluation of the slightly changed towards a more negative evaluation

(from M = -.4 to M = -.43). Spiegel and Zeit also had the strongest focus on negative developments, albeit only very slightly so (both M = -.45).

To compare the valency of the development between different categories of main topics in the reporting, first the main topics were reduced in order to keep the table clear.

The resulting variable differentiates between Israeli internal and external affairs, German-

Israeli affairs, the Arab-Israeli conflict, and Other topics. A crosstable for the simplified main topics and the valency of the development in the reporting was then requested as well as the means for the development, both as-is in the sample and weighted. The results can be seen in table 14.

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Table 14

Valency of Development per Simplified Main Topic

Valency of Development Main Topic Ambivalent/ Mean (Simplified) Negative Stagnant Positive Total Mean (Weighted) Israeli Internal 56 110 22 188 -.18 -.20 Affairs Israeli External 15 12 9 36 -.17 -.28 Affairs German Affairs 52 36 22 110 -.27 -.24 Arab-Israeli 161 31 7 199 -.77 -.79 Conflict Other Topics 9 11 9 29 0 .03 Total 293 200 69 562 -.40 -.43

An ANOVA showed significant differences between the mean valency of development when comparing the different general topics in the reporting (F [4, 557] =

27.683, p < .001 for the non-weighted cases; F [4, 912] = 52.642, p < .001 for the weighted cases). The Arab-Israeli conflict, in particular, stood out from the other general topics with a much more negative mean development evaluation. This could be found for both the general sample as well as weighted cases; the latter slightly defined the difference. Other topics were the only general main topic without a mean negative development, with M = .00 respectively M[weighted] = .03. However, the small number of cases here should be considered (n = 29).

This finding is in line with previous studies which focused on the Arab-Israeli conflict in their sample (Behrens, 2003; Maier 201; Maurer and Kempf, 2011; Gaisbauer, 65

2012) and found a focus on negative developments. While the crosstable shows that this is true for most topics, a significant difference can be seen regarding the Arab-Israeli conflict, which is portrayed much more negatively.

Overall, the hypothesis H1a, that Israel is mostly featured in news articles in the context of negative developments, has to be accepted. Although it should be noted that this holds true for articles on other topics as well, as the news media is generally focused on negative developments in general (Bohle, 1986), it is noteworthy that compared to the previous study by Beyer, a more negative evaluation of developments can be found in the recent digital news (Beyer, 2016, p. 382). The average evaluation of -.4 (resp. -.43 for weighted cases) highlights this focus on negative developments. No significant differences between the news outlets could be found, meaning this finding holds across the sample.

H1.10 Conflict/military action is not the most common theme in the reporting.

H1.1a Conflict/military action is the most common theme in the reporting.

In order to answer the underlying research question, the dichotomous variable for the occurrence of the news factor conflict was analyzed. This was done in order to differentiate between military conflict and other aspects of the conflict between Israel and its adversaries, which might have mudded the results if the variables for the main topic and the minor topics would have been used, as those include other aspects of the conflict

– not solely military actions – as well. Furthermore, the variable for the news factor conflict was also coded when conflict was only one of multiple aspects of the article.

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Table 15 shows that 79.9% of the articles during the research period do not feature military conflict.

Table 15

Occurrence of the News Factor Conflict in the Reporting

Percent News Factor n Percent (Weighted) No Conflict 449 79.9% 77.1% Conflict 113 20.1% 22.9% Total 562 100% 100%

Subsequently, 20.1% of the article did feature some kind of military conflict

(22.9% when weighted according to relevance). No major difference between the weighted and non-weighted cases could be found. The nullhypothesis has therefore to be accepted, as only a minority of the articles report on conflict.

When comparing the different news outlets, no significant difference between the outlets could be found. A crosstable both for non-weighted and for weighted cases was requested, comparing the percentages via a Z-test (p-value adjusted per Bonferroni- method; see table 16).

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Table 16

Occurrence of News Factor Conflict per Publication

Publication News Factor Bild n-tv Spiegel t-online Zeit Total No Conflict n 75 95 93 104 82 449 % 81.5% 79.8% 78.2% 79.4% 81.2% 79.9% % (w) 77.3% 76.8% 77.5% 76.4% 77.7% 77.1% Conflict n 17 24 26 27 19 113 % 18.5% 20.2% 21.8% 20.6% 18.8% 20.1% % (w) 22.7% 23.2% 22.5% 23.6% 22.3% 22.9% Total n 92 119 119 131 101 562 % 100% 100% 100% 100% 100% 100%

The percentages were fairly similarly spread, with only minor differences between the news outlets, both for the sample as-is and when weighted. No significant differences between the news outlets were found (p < .05).

A comparison to previous studies cannot be performed in this regard, as most of the studies done previously have explicitly focused on times of conflict for their research period. As such, none of the works discussed in chapter 3 gather data in this regard, although it seems likely that the percentage of articles on conflict would naturally be higher, simply due to the number of events that would happen during such a time period.

An exception in this regard is the aforementioned study by Beyer (2016), which's sample was conducted during a time of low-intensity conflict. Compared to Beyer's study, the sample drawn during the research period of this study features conflict more prominently, as Beyer found only 2.3% of the articles on Israel and Palestine to be about military 68

conflict (2016, p. 383). While there are differences in how the two studies were conducted, limiting the comparability, it is safe to say that conflict did take a larger portion of the reporting during the time period between September and December 2019.

In total, however, conflict was not the prominent theme in the reporting. While conflict did play a role in many articles, the hypothesis that this is the dominant theme in the news on Israel should be dismissed, at least during times of low-intensity conflict. On the other hand, it is somewhat surprising how large the proportion is – even when no major military operations are conducted by either side of the conflict, which can be seen as a testimony to the constant skirmishes which take place in the Arab-Israeli conflict.

What can be disputed, however, is that Israel only appears in the news when military conflict is happening in the region. While conflict is an important news factor and therefore expected to be relevant in the reporting when it happens, the sample shows that Israel is reported on in plenty of other cases as well. The conclusion that conflict is the dominant factor in the reporting may hold true during times of high-escalation in the

Arab-Israeli conflict, but it certainly does not during times of low-escalation.

H1.20 There is no significant correlation between negative developments and

Israeli responsibility.

H1.2a There is a significant correlation between negative developments and Israeli

responsibility.

Coded was which party was portrayed as responsible for the developments in the news. A responsibility for the development was located in 520 cases (92.5%), while the variable

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was not applicable in 42 cases (7.5%). Table 17 shows the frequency of responsibilities and the percentages, both as-is and weighted.

Table 17

Frequency and Distribution of Responsibility

Valid Percent Responsibility Frequency Percent Valid Percent (Weighted) Israeli 257 45.7% 49.4% 56.5% Palestinian 42 7.5% 8.1% 9.4% German 96 17.1% 18.5% 12% Syrian 9 1.6% 1.7% 2% Shared 42 7.5% 8.1% 8% EU 16 2.8% 3.1% 3.4% Iranian 14 2.5% 2.7% 2% Lebanese 9 1.6% 1.7% 1.4% USA 23 4.1% 4.4% 3.7% Other 12 2.1% 2.3% 1.6% Total 520 92.5% 100% 100% Not Applicable 42 7.5 % Total 562 100%

In the majority of the overall cases, the responsibility was Israeli (49.4%; 56.5% when weighted according to relevance). However, this is somewhat to be expected given that the sample consists of articles on Israel. When weighted, not only does the percentage for Israeli responsibility increase, but also the German responsibility decreases. Apart from this, the percentages are relatively consistent.

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The distribution of responsibility for the developments portrayed as positive and negative is shown in table 18. This testing was done without weighting the cases.

Table 18

Percentages of Responsibility for Development per Country

Development Ambivalent/ Positive Stagnation Negative Responsibility n %(D) %(R) n % (D) %(R) n %(D) %(R) Israeli 35 53% 13.6% 106 64.6% 41.2% 116 40% 45.1% Palestinian 2 3% 4.8% 2 1.2% 4.8% 38 13.1% 90.5% German 14 21.2% 14.6% 28 17.1% 29.2% 54 18.6% 56.3% Syrian 0 .0% .0% 1 .6% 11.1% 8 2.8% 88.9% Shared 11 16.7% 26.2% 7 4.3% 16.7% 24 8.3% 57.1% EU 0 .0% .0% 9 5.5% 56.3% 7 2.4% 43.8% Iranian 0 .0% .0% 0 .0% .0% 14 4.8% 100% Lebanese 4 6.1% 44.4% 2 1.2% 22.2% 3 1% 33.3% USA 0 .0% .0% 2 1.2% 8.7% 21 7.2% 91.3% Other 0 .0% .0% 7 4.3% 58.3% 5 1.7% 41.7% Total 66 100% 12.7% 164 100% 31.5% 290 100% 55.8% Note. %(D) indicates percentage within development. %(R) indicates percentage within responsibility.

Out of the total cases for which Israel was portrayed as responsible, only 13.6% were for positive developments, while ambivalent (42.2%) and negative (45.1%) developments were similar. In total, Palestinians were responsible in 42 articles and were overwhelmingly portrayed as responsible for negative developments (90.5%) in contrast to only 4.8% for each positive and ambivalent/stagnant events. Germany had positive 71

responsibility similar to Israel (14.6%), but less ambivalent (29.2%) and a slightly higher negative responsibility (56.3%). Iran appeared as a strong outlier, only responsible for negative developments (14 cases); however, this can be attributed to the relationship between Israel and Iran, which is marked by confrontation. As such, Iran was mostly mentioned in the context of Israel if the reporting was on this confrontation, and as such, unfavorable of nature. Another outlier is the Lebanese responsibility, particularly the high percentage of responsibility for positive developments (44.4%). However, this can be attributed to a low number of cases (nine with Lebanese responsibility) and due to a singular event, in which a Lebanese businessman donated to an Israeli NGO.

These percentages, however, have to viewed in context, as positive developments were much rarer than ambivalent and negative ones. As such, Israel was responsible for more than half of the positive developments reported on (53%), more than any other party in the reporting.

A Chi²-test confirmed a correlation between the valency of the event and the party responsibility (X² [18, N = 520] = 88.771, p < .001). However, due to the uneven distribution of cases in which the countries were portrayed as responsible, which left a third of the cells with less than 5 cases, the test was not sufficiently sound to determine whether the hypothesis could be confirmed or dismissed.

For further testing, a binary variable was recoded, differentiating between Israeli responsibility and other responsibility. Additionally, a second binary variable was coded which summarizes positive and ambivalent developments in opposition to negative.

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These two variables were then analyzed in a crosstable and a Chi²-test was performed

(see table 19).

Table 19

Valency of Events (Binary) and Responsibility (Binary)

Responsibility Development Israeli Other Total Positive/Ambivalent n 141 89 230 % 61.3% 38.7% 100% Negative n 116 174 290 % 40% 60% 100% Total n 257 263 520 % 49.4% 50.6% 100%

The resulting table shows that other parties (60%) were more likely to be portrayed as responsible for negative developments than Israel (40%). A Chi²-test confirmed a significant correlation (X² [1, N = 520] = 23.29, p < .001).

While Israel was portrayed most often as responsible for negative developments individually in the sample, when compared to all other parties combined, Israel was, in fact, less likely to be portrayed as responsible for negative development than other actors.

Therefore, hypothesis H1.2 must be dismissed, as it is more likely that other parties are reported as responsible for negative developments in the context of the overall reporting on Israel in German online news media. Consequently, the nullhypothesis has to be

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rejected and the alternative hypothesis to be accepted, as other parties are more likely to be portrayed as responsible of negative developments than Israel is.

An additional crosstable (see table 20) which includes the different publications shows an overall somewhat similar spread of Israeli and non-Israeli responsibility in the different outlets – with the exception of Bild. Two additional tables, which includes the number of cases and the weighted percentages, can be found in Appendix E (pp. 214)

Table 20

Valency of Events (Binary) and Responsibility (Binary) per Publication

Responsibility Publication Development Israeli Other Bild Positive/Ambivalent 46.4% 53.6% Negative 6.0% 94.0% n-tv Positive/Ambivalent 64.2% 35.8% Negative 47.5% 52.5% Spiegel Positive/Ambivalent 67.3% 32.7% Negative 48.4% 51.6% t-online Positive/Ambivalent 55.9% 44.1% Negative 49.2% 50.8% Zeit Positive/Ambivalent 68.3% 31.7% Negative 42.3% 57.7% Total Positive/Ambivalent 61.3% 38.7% Negative 40.0% 60.0%

Bild especially stood out, as almost no negative developments are portrayed as

Israeli responsibility. Only 6% of the negative developments were put in Israeli hands,

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while 94% were located in non-Israeli hands (8.6% respectively 91.4% for weighted cases). This is compared to between 50.8% (t-online) and 57.7% (Zeit), respectively 60% overall, for non-Israeli responsibility for negative developments. The difference was slightly lessened when weighted according to relevance (to 8.6% Israeli responsibility and 91.4% for non-Israeli responsibility for negative developments). In fact, all outlets saw an increase in Israeli responsibility – both for positive/ambivalent developments and for negative ones. This increase makes sense when considering that articles that have

Israel as the main topic would naturally focus more on Israeli actions.

A Chi²-test confirmed this difference as significant (X² [1, N = 78] = 17.992, p <

.001). Evidently, it should be noted that in regards to the depiction of Israeli and non-

Israeli responsibility for the developments, there is a highly significant difference between the outlets, as Bild almost solely locates responsibility for negative developments at non-Israelis. The other news outlets appear to provide a depiction much closer to the overall mean, which suggests a distribution close to 50%, with a tendency towards non-Israeli responsibility for negative developments and around a 70% location of Israeli responsibility for positive and ambivalent developments.

5.2.2 Israelis in the News

Hypotheses H2 through H2.2 are concerned with the occurrence and depiction of

Israelis in German online news. Up to five actors were coded per article. At least one actor is present in every article in the sample.

H20 If actors appear in the reporting, they are not Israeli.

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H2a If actors appear in the reporting, they are Israeli.

In order to find out which ones were the most prominent actors in the sample, a multiple- response set was defined from these variables. Table 21 lists all the actors in a simplified version: actors that appeared less than five times were recoded to their more general code. The full table with all coded actors can be found in Appendix E (pp. 223).

Table 21

Frequency of Selected Actors in the Reporting

Responses Percent of Actor n Percent Cases Israel (Generic Reference) 150 7.6% 26.7% Israeli Civilian 133 6.8% 23.7% Israeli Prime Minister 226 11.5% 40.2% Israeli Opposition 199 10.1% 35.4% Israeli President 52 2.6% 9.3% Israeli Military 113 5.8% 20.1% Other Israeli 167 8.5% 29.7% German Civilian 68 3.5% 12.1% German Politician 76 3.9% 13.5% German Government 72 3.7% 12.8% Other German 92 4.7% 16.4% Palestinian 75 3.8% 13.3% Palestinian Armed Group 127 6.5% 22.6% Other Arab 91 4.6% 16.2% Iran 67 3.4% 11.9% USA 85 4.3% 15.1% Other 170 8.7% 30.2% Total 1963 100% Note: Up to five actors were coded per article.

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The most prominent actor is Israeli prime minister Benjamin Netanjahu, appearing in 40.2% of the articles, followed by politicians of the Israeli opposition, particularly Benjamin Gantz, who appeared in 35.4% of the articles.

The focus on the prime minister as an individual has been documented in the past

(Beyer 2016, p. 393). The frequent mention of the opposition can in part be attributed to the ongoing internal political situation in Israel, as the state has undergone four elections since 2015, one of which on September 17, 2019, during the time frame for which the material for this study was collected.

Another prominent actor was the Israeli military (the army – the IDF –and the air force – the IAF). Surprisingly, the USA and Iran were also relatively prominent, appearing in 15.1% (USA) and 11.9% (Iran) of the articles. Palestinians were also frequently mentioned.

For the purpose of making the relation of the actors easier to compare, the variables were coded into new variables, reduced to only the countries they are associated with (see table 22).

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Table 22

Frequency of Actors (Reduced) per Publication

Publication Actor Bild n-tv Spiegel t-online Zeit Total Israel/Israelis n 135 219 235 248 203 1040 Germany/Germans n 109 34 58 67 40 308 Palestine/Palestinians n 48 32 41 45 36 202 Other Arab actors n 11 23 17 22 18 91 Iran n 10 10 16 14 17 67 European Union n 8 13 9 6 7 43 Other countries n 5 12 13 9 7 46 USA n 8 12 17 16 17 70 International actors n 14 4 28 19 16 81 Total n 92 119 119 131 101 1948 Note: Up to five actors were coded per article.

The percentages for the different types of actors were requested in an additional table, both as-is and weighted, as can be seen in table 23.

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Table 23

Frequency of Actors (Reduced)

Percent Actor (Reduced) n Percent (Weighted) Israel/Israelis 1040 53.4% 58.8% Germany/Germans 308 15.8% 11% Palestine/Palestinians 202 10.4% 11.2% Other Arab Actors 91 4.7% 4.7% Iran 67 3.4% 3% European Union 43 2.2% 2.3% USA 70 3.6% 3.2% Other Countries 46 2.4% 2% International Actors 81 4.2% 3.7% Total 1948 100% 100% Note: Up to five actors were coded per article.

Here, Israel and Israelis constitute 53.4% of the actors mentioned in the articles, slightly above half of the total actors coded. When weighted for relevance, this percentage goes slightly up, to 58.8%. Overall, the main difference between weighted and not-weighted is an increased presence of Israeli and Palestinian actors, while the other actors – particularly German ones – decrease. This central tendency can be found in both columns, though: Israelis do constitute the majority of the actors in the reporting.

When comparing the different news outlets, the same holds true for n-tv, Spiegel, t-online, and Zeit (see table 22). Bild, however, is the only news outlet in the sample which featured non-Israelis (213 times) more often than Israelis (135 times). Again this can be attributed to Bild's focus on (local) German news, as described in chapter 5.1.2.

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When weighted, the ratio of Israeli and German actors in Bilds reporting becomes closer to the one which can be found in the other news outlets (the corresponding table can be found in Appendix E, p. 228). Although German actors appear still more often than in the other outlets, the ratio of Israeli to German ones becomes two to one.

The nullhypothesis H20 has to be dismissed, as lightly more actors in the reporting are Israeli than they are not. This is even more so the case in articles which focus mainly on Israel. The alternative hypothesis H2a should instead be accepted.

H2.10 If Israeli actors appear in the news, they are not evaluated negatively than

other actors.

H2.1a If Israeli actors appear in the news, they are evaluated more negatively than

other actors.

As described above, the actors in the articles were coded in five separate variables, one for each actor; up to five actors could be coded. The evaluation of the actors was coded in a similar way. Up to five evaluations – one for each actor which appeared in the text – could be coded.

In order to determine whether this hypothesis can be accepted, the two multi- response sets – the actors and their valency – were split into a new data set, with each actor and their valency being an individual case. The evaluation was recorded on a

Likert-scale from 2 (very positive) to -2 (very negative), with 0 being neutral or ambivalent. Table 24 shows how the actors were evaluated on average and per

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publication (a more detailed table which includes all actors, the number of cases and the standard derivation can be found in Appendix E, pp. 231).

Table 24

Mean Evaluation of Selected Actors per Publication

Publication Actor Bild n-tv Spiegel t-online Zeit Total Israeli Civilian .31 .19 .70 .42 .89 .49 Israeli Settler .33 -.60 -1.00 -1.75 -1.17 -.91 Israeli Prime Minister -.48 -.77 -.82 -.62 -.64 -.69 Israeli Opposition 0.00 -.03 .04 .08 -.08 .01 Israeli Military .50 -.18 -.32 -.32 .10 -.09 German Civilian -.71 .36 -.20 .22 -.21 -.07 German Politician .09 -.10 .15 -.21 .08 .00 German Government -.23 -.44 -.20 -.83 -.78 -.45 Palestinians -.94 .23 -.35 -.11 -.45 -.27 Palestinian Armed Group -1.31 -1.29 -1.12 -1.30 -1.62 -1.31 Total -.28 -.26 -.26 -.25 -.20 -.25

The variable for the actors was then recoded into a binary variable to test the hypothesis, differentiating between Israeli actors and non-Israeli actors. The mean evaluation for Israelis and non-Israelis was then calculated; Israeli actors had a mean evaluation of M = -.06, meaning ever so slightly negative, while non-Israeli actors were evaluated more negatively, with a mean of M = -.46. A t-test for independent samples was then conducted in order to test whether the differences in the mean evaluation of the

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two groups were significant. Table 25 shows the groups statistics; the corresponding tables for the independent sample t-test can be found in Appendix E (p. 238).

Table 25

Mean Evaluation of Israeli and Non-Israeli Actors

Actor (Binary) n Mean Std. Deviation Israeli 1040 -.06 .969 Non-Israeli 908 -.46 1.043

The independent t-test indicates a significant difference between the two means (t

[1885.851] = 8.752, p < .001). Non-Israeli actors (M = -.46, SD = 1.043) are significantly more negatively evaluated in the reporting than Israelis (M = -.06, SD = .969). While all actors – both Israeli and non-Israeli – were generally evaluated negatively, the nullhypothesis H2.10 has to be accepted. If Israeli actors appear in the news, they are evaluated more positively than the non-Israelis in the same context.

In order to compare the different publications regarding their average portrayal of

Israelis, a crosstable was requested in order to compare the means of their evaluation. The variables for the Israeli actors were also reduced to provide a clearer overview. This table

26 only shows the mean evaluation for a reduced number of Israeli actors; a table which includes the number of cases in the sample and the standard deviation can be found in

Appendix E (p. 239).

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Table 26

Valency of Israelis (Reduced) per Publication

Publication Israeli Actor (Reduced) Bild n-tv Spiegel t-online Zeit Total Generic Reference .52 .13 .23 .23 .13 .13 Civilian .31 .19 .42 .42 .49 .49 Settler .33 -.60 -1.75 -1.75 -.91 -.91 Politician .00 .00 -.27 -.27 -.06 -.06 Prime Minister -.48 -.77 -.62 -.62 -.69 -.69 Opposition .00 -.03 .08 .08 .01 .01 Military .50 -.18 -.32 -.32 -.09 -.09 Other State Institution .25 -.13 -.13 -.07 -.07 NGO 1.33 -.33 1.00 1.00 .77 .77 Business/Company 2.00 .56 -.20 -.20 .66 .66 Government .29 .08 -.05 -.05 .12 .12 Total .26 -.13 -.11 -.11 -.06 -.06 Note: If an actor did not appear in the reporting of a publication, the cell is left blank.

Especially Bild stands out, as it is the only news outlet to overall evaluate Israelis positively. While the number of cases was the smallest for Bild, which tends to swing the evaluation, there are still some trends worth pointing out. Settlers, for example, are evaluated slightly positive by Bild in contrast to the other outlets. However, the sample size was too small to determine a clear trend, as settlers appeared only in three articles by

Bild. On the other hand, the Israeli military has a larger sample size (appearing 18 times in articles by Bild) and is also evaluated positively by them while being evaluated negatively by the other outlets. As also evident by the overall mean valency of Israelis,

Bild tends to evaluate Israel and Israeli actors more positively than the outer outlets. Even 83

the prime minister – who is evaluated negatively by Bild – is so to a lesser extent than in the other news sites.

For the other outlets, a tendency can be seen: Israeli civilians and generic references are usually positively evaluated; politicians and in particular the prime minister receives more negative evaluations, while the political opposition is portrayed slightly positively. The military and settlers are distinctly not depicted favorably.

Generally, few strong evaluations can be found, as the valencies mostly gravitate towards a neutral or ambivalent depiction.

In order to compare the depiction of Israeli and non-Israeli actors per news outlet, the mean evaluation of Israelis and non-Israelis per outlet is shown in table 27.

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Table 27

Evaluation of Israelis and Non-Israelis per Publication

Actor Publication Mean n Std. Deviation Non-Israeli Bild -.70 181 1.090 Actors n-tv -.43 175 1.037 Spiegel -.37 188 1.049 t-online -.41 214 .954 Zeit -.42 163 1.076 Total -.46 921 1.043 Israeli Bild .26 141 .959 Actors n-tv -.13 231 1.028 Spiegel -.17 230 .955 t-online -.11 244 .900 Zeit -.02 189 .962 Total -.06 1035 .969 Total Bild -.28 322 1.137 n-tv -.26 406 1.041 Spiegel -.26 418 1.002 t-online -.25 458 .936 Zeit -.20 352 1.034 Total -.25 1956 1.024

Interestingly, Bild is the only publication that evaluates Israelis positively (M =

.26); simultaneously, it is also the publication to evaluate non-Israelis the most negative.

Overall, it becomes clear that the general trend – that non-Israelis were on average evaluated less positively than Israelis, as seen in table 27 – is not caused by an outlier but can be found across the different news websites. Without exception, non-Israelis were evaluated worse than the Israeli actors. While it can generally be expected that actors

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who appear in the news will be evaluated negatively, as there is a reason for the reporting and negativity is an important news factor, it is interesting to see that in the sample on

Israel the valencies favored Israelis.

H2.20 There is no significant correlation between the evaluation of Israeli actors

and conflict.

H2.2a There is a significant correlation between the evaluation of Israeli actors

and conflict.

To test this hypothesis, the same data set as for the previous hypothesis was used. Only the Israeli actors were selected and two groups were defined, Israelis in the reporting of conflict and Israelis in the reporting on non-conflict issues.

The mean evaluation of the two groups shows that both groups were evaluated slightly negatively (see table 28). Israelis in reporting on conflict had a mean of -.04 (SD

= .908), while Israelis in the reporting on other issues had a mean of -.07 (SD = .984).

Table 28

Mean Evaluation of Israelis in Conflict and Non-Conflict Reporting

Israelis n Mean Std. Deviation Std. Error Mean No Conflict 833 -.07 .984 .034 Conflict 202 -.04 .908 .064

A t-test for independent samples which was requested shows no significant differences between the two groups (t [1033] = -.411, p = .667). 86

In accordance with the testing for H2.1, Israelis were generally evaluated slightly negative. The hypothesis that Israelis were evaluated more negatively during conflict, however, could not be confirmed. While the evaluations in non-conflict reporting were more negative, no significant differences could be found. The nullhypothesis H2.20 must therefore be accepted and the alternative hypothesis dismissed, as conflict has no significant impact on how Israelis are evaluated in German online news.

5.2.3 Israel in Quotes

The upcoming hypotheses H3 to H3.2 target the question of how Israel is evaluated in quotes in the reporting. The foundation for this question is a finding by

Beyer, who stated that while Israel is usually portrayed relatively balanced by the authors, evaluations of Israel in German print news are heavily influenced by people who are quoted (2016, p. 399). Often, he found negative evaluations are neither opposed nor put into context, which could skew the public perception of Israel through such texts.

The data for these hypotheses were gathered similar to the actors in the articles: up to five quoted actors were coded per article (if more than five actors were quoted, the only ones which were quoted the most were coded). The coding scheme was slightly less detailed than for the actors, as the research questions mostly aimed towards the question of which general types of actors – Israel and non-Israeli – were quoted. For each quoted actor, the evaluation of Israel in their quotes was coded in a respective variable. The valency was measured on a five-step Likert-scale, ranging from +2 (very positive) to -2

(very negative). Additionally, the total number of quotes in the article by Israelis,

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Palestinians, Germans, and other actors was gathered. Both direct and indirect quotes were counted in this.

H30 There is no significant difference between the amount Israeli and Palestinian

actors are quoted during conflict.

H3a There is a significant difference between the amount Israeli and Palestinian

actors are quoted during conflict.

For the analysis of this hypothesis, a t-test for paired samples was conducted. For this test, only cases that contained conflict between Israel and Palestinians were selected through the variables for the main and minor topics. This was done in order to make sure to only selected articles which focus on this specific conflict, not conflict in general, which would have been the case if using the variable for conflict.

The t-test indicated significant differences between the number of Israeli quotes and Palestinian quotes during conflict: Israelis were on average quoted 2.04 times per article (SD = 1.631), while Palestinians were quoted only .45 times per article on average

(SD = .703; see table 29). This difference is highly significant (t [163] = 12.496, p <

.001).

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Table 29

Mean Number of Quotes by Israelis and Palestinians During Conflict Between the Two . Std. Std. Error Quoted During Conflict Mean n Deviation Mean Israel 2.04 164 1.708 .133 Palestine .45 164 .703 .055

The nullhypothesis H30 has therefore to be rejected and the alternative hypothesis

H3a be accepted, as Israeli actors were quoted more than four times as often as

Palestinian actors during times of conflict between Israel and Palestinians.

H3.10 There is no correlation between the occurrence of Israeli actors who are

quoted to the advantage of Israel and non-Israeli actors who are quoted to the

disadvantage of Israel.

H3.1a There is a correlation between the occurrence of Israeli actors who are

quoted to the advantage of Israel and non-Israeli actors who are quoted to the

disadvantage of Israel.

H3.20 There is no significant correlation between actors who are quoted to the

disadvantage of Israel and actors who are quoted to the advantage of Israel.

H3.2a There is a significant correlation between actors who are quoted to the

disadvantage of Israel and actors who are quoted to the advantage of Israel.

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Hypotheses H3.1 and H3.2 were tested together, as they both target two different sides of the same question: What kind of other evaluations can be found when there are positive evaluations of Israel (H3.1) and negative evaluations (H3.2) of Israel in articles.

A number of recodings had to be done in order to analyze these hypotheses. A multi-response crosstable which shows what kind of actor provided what kind of evaluation can be found in Appendix E (pp. 242). Since that table is relatively unclear, the variables for the quoted actors were reduced into more general categories. This crosstable, which shows their evaluations of Israel, can be seen in table 30.

Table 30

Quoted Actors (Reduced) and Their Evaluation of Israel

Evaluation of Israel Very Neutral/No Very Mean Type of Actor Positive Positive Tendency Negative Negative Eval. Israeli n 74 211 619 137 74 .066 German n 90 133 217 53 51 .290 Palestinian n 25 55 93 55 73 -.319 Other Arab n 9 37 64 26 34 -.229 EU n 9 8 10 13 17 -.368 Other Country n 29 38 67 35 42 -.109 International n 7 25 34 15 23 -.212 Total n 243 507 1104 334 314 .012

The table shows that surprisingly, German actors provide on average more positive evaluations of Israel (M = .29) than Israelis (M = .066), though both are the only

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two types of quoted actors with a positive mean evaluation of Israel. The other actor all have a mean negative evaluation. While this should not come as a surprise for the

Palestinian actors, given the history of conflict between them and Israel, the EU had an even more negative mean evaluation, though a smaller sample size, too. Generally, Israeli and German actors were quoted much more often, though, bringing the overall mean to a slightly positive with M = .012.

In order to test the hypothesis at hand, the goal was to merge the two separate variables – the actor who was quoted and the valency of that quote – into one single variable. The actors were grouped into Israeli and non-Israeli actors; for each actor it was determined whether his evaluation of Israel was negative or positive/ambivalent. The resulting variable has four manifestations, Israeli-positive evaluation, Israeli-negative evaluation, non-Israeli-positive evaluation, and non-Israeli-negative evaluation. As there were still up to five actors per article which may be quoted, these were then recoded into four binary variables, which just tracked the occurrence of each of the four manifestations. Additionally, two variables for the general occurrence of positive and negative evaluations independent from the quoted actor were coded. This was done to test whether the hypothesis applies as is or if the effect – positive evaluations of Israel correlate with negative evaluations of it – could be found independent from the speaker in the general population. The syntax for these recoding operations can be found in

Appendix E (pp. 244).

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The two binary variables relevant to the hypothesis that quotes by Israelis with a positive evaluation are countered by quotes by non-Israelis with a negative evaluation were then tested in a crosstable with Chi².

Table 31 shows this crosstabulation. The Chi²-test indicates a correlation between the two variables (X² [1, N = 562] = 18.921, p < .001), albeit the effect is a relatively small one (Cramér's V = .183). This means that positive evaluations of Israel by Israelis were statistically significantly more likely to occur at the same time as negative evaluations by non-Israelis.

Table 31

Crosstable Israeli (Positive Quotes) and Non-Israeli (Negative Quotes)

Non-Israeli-Negative (Binary) Valency Quoted Actors No Yes Total Israeli-Positive No 376 70 446 (Binary) Yes 77 39 116 Total 453 109 562

A second crosstable was requested for the binary variables for the general occurrence of positive and negative evaluations to test whether the effect described above was also present in the general population (see table 32). For one, this would negate the previous test, as it would confirm that the effect could not only be found depending on

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the speaker but in the general population. The test also tests hypothesis H3.2 – whether there is a significant difference in the occurrence of negative and positive evaluations.

The Chi²-test shows no significant association between the two groups (X² = [1, N = 562]

= 2.865, p = .09).

Table 32

Crosstable All Positive and All Negative Evaluations in Quotes

VQA All-Negative (Binary) Valency Quoted Actors No Yes Total VQA All- No Count 272 90 362 Positive (Binary) Expected Count 263.4 98.6 362 Yes Count 137 63 200 Expected Count 145.6 54.4 200 Total Count 409 153 562 Expected Count 409 153 562

As such, the nullhypothesis H3.10 has to be rejected and the alternative hypothesis

H3.1a should be accepted. There is a statistically significantly above-average likelihood that positive evaluations of Israel by Israelis occur at the same time as negative evaluations by non-Israelis.

On the other hand, the nullhypothesis H3.20 should be accepted and the alternative hypothesis H3.2a be rejected. No statistical significance could be found for the

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occurrence of negative evaluations and positive evaluations (or lack thereof) in the sample.

When comparing the different news outlets in this regard, the Chi²-test showed no significant differences between the publication (with results between X² = .019, p = .889 and X² = 1.242, p = .26; see Appendix E, pp. 248, for the full table). The null hypothesis

H3.20 can therefore be assumed for all the news outlets in the sample.

5.2.4 Israel in the Headlines

The upcoming hypotheses H4 to H4.2 aim to analyze whether there are any differences in the depiction of Israel in the headline, the teaser text, and the main text body of the articles. Again, these hypotheses are based on findings by Beyer, who found that Israel was often criticized in prominent parts of print articles (2016, pp. 512). Even if those negative portrayals were later mitigated in the text, Beyer argued, the prominent display of negative evaluations could skew the perception of Israel. Since Beyer’s finding refer to print, the goal here is to analyze whether the same can be found in online news, especially since there was a public debate about this kind of bias in Germany (see

Weinthal, June 29, 2018; Stafanowitsch, July 14, 2014).

H40 The headlines, teaser text and text body are not contentual coherent in the

majority of articles.

H4a The headlines, teaser text and text body are contentual coherent in the

majority of articles.

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Contentual coherent articles are defined as articles in which the same information can be found across headline, teaser text, and main text body. If information is missing – for example, if a reaction is portrayed as an action in the headline, but the context is explained in the main text – the article was coded as contentual dissonant.

In total, only 23 articles were identified in which the headline, teaser, and text were not contentual coherent, amounting to 4.1% of the relevant cases (see table 33).

Table 33

Contentual Dissonant and Coherent Articles in the Sample

Contentual Coherency Frequency Percent Dissonant 23 4.1 Coherent 539 95.9 Total 562 100

Table 34 shows the distribution per news outlet. The distribution was roughly similar for all outlets, with cases ranging from two (t-online) to six (n-tv and Zeit). A

Fisher's exact test, which was chosen due to the high number of cells in the crosstable with an expected count lower than 5, showed no significant correlation between the news outlets and the number of dissonant articles (p = .427).

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Table 34

Contentual Dissonant and Coherent Articles per Publication

Contentual Coherency Publication Dissonant Coherent Total Bild n 4 88 92 Expected n 3.8 88.2 92 n-tv n 6 113 119 Expected n 4.9 114.1 119 Spiegel n 5 114 119 Expected n 4.9 114.1 119 t-online n 2 129 131 Expected n 5.4 125.6 131 Zeit n 6 95 101 Expected n 4.1 96.9 101 Total n 23 539 562 Expected n 23 539 562

With 95.9% of the articles being contentual coherent, the nullhypothesis H40 has to be rejected. Instead, the alternative hypothesis H4a has to be accepted, as the overwhelming majority of the articles do provide the same evaluation throughout the parts of it.

Hypothesis H4.1 takes a look at the articles which are contentual dissonant and in particular, whether this dissonance is to the advantage or disadvantage of the portrayal of

Israel, meaning whether Israel is painted in a more positive or more negative light by the missing context.

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H4.10 If headlines, teaser text and text body are contentual dissonant, it is not to

the disadvantage of Israel.

H4.1a If headlines, teaser text and text body are contentual dissonant, it is to the

disadvantage of Israel.

Overall, the evaluation of contentual dissonant articles leaned towards the disadvantage of Israel with a mean of M = -.39 on a three-point Likert-scale (ranging from +1, to the advantage of Israel, to -1, to the disadvantage of Israel). Table 35 shows the distribution throughout the different news outlets as well as the mean for each.

Table 35

Contentual Dissonance to the Disadvantage and Advantage of Israel per Publication

Contentual Dissonance Disadvantage Neutral/ Advantage of Publication of Israel Ambivalent Israel Total Mean Bild 0 1 3 4 .75 n-tv 4 1 1 6 -.50 Spiegel 5 0 0 5 -1.00 t-online 1 0 1 2 .00 Zeit 5 0 1 6 -.67 Total 15 2 6 23 -.39

A Fisher’s exact test showed a correlation between the publication and the trend of the dissonant articles (p = .037).

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Bild is the only news outlet in which none of the contentual dissonant articles were to the disadvantage of Israel (see table 35); it was also the outlet that had the most dissonant articles to the advantage of Israel. This trend was also reflected in the overall valency for the contentual dissonant articles, where Bild is the only news outlet with an overall positive mean of .75, meaning to the advantage of Israel. On the other hand, n-tv,

Spiegel, and Zeit all had more articles in this category to the disadvantage of Israel, between 4 (n-tv) and 5 (Spiegel and Zeit). Additionally, Spiegel is the only news publisher which only has contentual dissonant articles to Israel’s disadvantage. As such,

Bild and Spiegel could be found on different sides of the spectrum: while both have the same number of contentual dissonant articles, the ones in Bild portrayed Israel more positively while the ones in Spiegel portrayed it more negatively.

An analysis of variance (ANOVA) shows that a significant difference could be found between the publications (F [4, 18] = 3.707, p = .023). A subsequent Post-Hoc-test

(Games-Howell method, unequal variances assumed in Levene’s test [F = 3.558, p =

.026] showed that the mean evaluation of Bild (M = .75, SD = .5) was significantly different than that of Spiegel (M = -1, SD = 0) at p = .023. No other significant differences could be found (see Appendix E, p. 257, for the full table).

Then nullhypothesis H4.10 should therefore be rejected and the alternative hypothesis H4.1a accepted, as the overall mean of the contentual dissonant articles is negative. It should be noted, though, that significant differences between the publisher can be found. Additionally, the relatively small number of cases should be considered, as

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only 4.1% of the relevant cases show dissonance in their articles. However, if dissonance could be found, it tends to be to the disadvantage of Israel.

H4.20 If there is contentual dissonance, the headlines do not portray Israel more

negatively than other parts of the article.

H4.2a If there is contentual dissonance, the headlines portray Israel more

negatively than other parts of the article.

First, a new variable was coded to test this hypothesis, combining the teaser evaluation and text evaluation into one variable. A t-test for paired samples was then conducted for the headline evaluation variable and the new teaser and text combined variable in order to compare the mean of the two.

The t-test indicated that the mean of the headline (M = -.36, SD = .848) is lower than the mean of the teaser and text evaluation (M = -.227, SD = .667), but not significantly so (t [21] = -1.667, p = .11).

While the headlines in the contentual dissonant articles did evaluate Israel more negatively than the teaser and text evaluations, they did not do so to a statistically significant extend. The nullhypothesis H4.20 should therefore be accepted, and the alternative hypothesis H4.2a be rejected, as no significant difference could be found.

5.2.5 Overall Evaluation of Israel

In regards to the underlying research question which media image of Israel is conveyed in German online news, the overall evaluation of the reporting has to be taken into account. The overall evaluation is the summary of aspects of the article which

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tangent Israel and Israelis, as it is this overarching portrayal which constitutes the basis for the construction of the media image of the country for the audience.

H50 The reporting on Israel does not have a negative bias.

H5a The reporting on Israel does have a negative bias.

Hypothesis H5 draws on the variable for the overall valency towards Israel in the articles.

This variable summarizes the depiction of Israel throughout the text, including evaluations by the author and by other actors, the way information is presented, and the overall framing. The variable was coded in a five-step Likert-scale (ranging from +2 for a very positive depiction of Israel to -2 for a very negative depiction). The goal of this hypothesis is to test whether a bias against Israel, as found in print media by, for example, Jäger and Jäger (2003), Wetzstein (2011), or Troschke (2015), can also be found in the digital media.

In order to analyze the general evaluation of Israel in the media, an overall mean for all news outlets was calculated using the Likert-scale described above. This mean is

M = .18 (SD = .955). As such, the overall evaluation is slightly positive. When adjusted for relevance – Israel as a main topic with the factor 1, Israel as the main topic with the factor 2 – this evaluation is slightly lowered, but still in the positive, with a mean of

M[weighted] = .1 (SD = .953; see table 36).

Nullhypothesis H50 should therefore be accepted as an – albeit only slightly – positive depiction of Israel can be found in the sample and the alternative hypothesis H5a should be rejected.

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5.2.6 Differences Between the Publications

The theoretical ideal mean for the overall evaluation would be 0, which would indicate a balanced and neutral reporting. As discussed in chapter 2, this is however virtually impossible in practice. The mean overall evaluation in the sample is .18 in favor of Israel. This chapter will analyze whether any of the publications deviate in a significant manner from this overall mean in order to determine potential bias’ via the structural objectivity analysis.

H60 There are no significant differences between the different media outlets

regarding their reporting on Israel.

H6a There are significant differences between the different media outlets

regarding their reporting on Israel.

To test hypothesis H6, first the overall mean is compared in order to find out whether there are any significant differences between the news outlets in their average evaluation of Israel. This comparison was made using an analysis of variance (ANOVA) for the mean evaluations of the outlets. Table 36 shows the mean evaluation for each news outlet in the sample, both as-is and weighted. The ANOVA indicated a significant difference between the outlets for both non-weighted (F [4, 557] = 26.83, p < .001) and weighted (F

[4, 912] = 48.533, p < .001) cases.

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Table 36

Mean Overall Evaluation of Israel for All Outlets

Not Weighted Weighted Std. Std. Publication n Mean Deviation Mean Deviation Bild 92 1.04 .913 1.06 .947 n-tv 119 .08 .922 .03 .898 Spiegel 119 -.04 .951 -.14 .933 t-online 131 .02 .673 -.02 .663 Zeit 101 -.01 .933 -.12 .907 Total 562 .18 .955 .10 .953

A subsequent post-hoc test (Games-Howell method, as unequal variances have to be assumed due a Levene’s test [F = 5.228, p < .001) shows a statistically significant difference can be found between Bild (M = 1.04, SD = .913) and all other news outlets (p

< .001 for each). No other significant differences can be found (see table 37).

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Table 37

Games-Howell Test for Differences in Overall Valency Between Publications

Dependent Variable: Overall Valency Games-Howell Mean 95% Confidence Interval (I) (J) Difference Std. Lower Upper Publication Publication (I-J) Error Sig. Bound Bound Bild n-tv 1.026* .104 .000 .74 1.31 Spiegel 1.203* .105 .000 .91 1.49 t-online 1.084* .094 .000 .83 1.34 Zeit 1.181* .108 .000 .88 1.48 n-tv Bild -1.026* .104 .000 -1.31 -.74 Spiegel .177 .091 .295 -.07 .43 t-online .058 .078 .945 -.16 .27 Zeit .155 .094 .472 -.10 .41 Spiegel Bild -1.203* .105 .000 -1.49 -.91 n-tv -.177 .091 .295 -.43 .07 t-online -.119 .080 .571 -.34 .10 Zeit -.022 .096 .999 -.28 .24 t-online Bild -1.084* .094 .000 -1.34 -.83 n-tv -.058 .078 .945 -.27 .16 Spiegel .119 .080 .571 -.10 .34 Zeit .097 .084 .776 -.13 .33 Zeit Bild -1.181* .108 .000 -1.48 -.88 n-tv -.155 .094 .472 -.41 .10 Spiegel .022 .096 .999 -.24 .28 t-online -.097 .084 .776 -.33 .13 Note. *. The mean difference is significant at the .05 level.

The same results can be found when weighting the cases (see Appendix E, pp.

262, for the corresponding tables).

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This is insofar not surprising, as Bild is the only outlet in the sample with a positive depiction of Israel (weighted mean evaluation of M = 1.04, SD = .947), whereas the other news outlets all gravitated towards a mean evaluation of 0, slightly below the average for all publications of M = .18 respectively M[weighted] = .1. Spiegel has the most negative evaluation if Israel (M[weighted] = -.14, SD = .933) closely followed by

Zeit (M[weighted] = -.12, SD = .907), while t-online (M[weighted] = -.02, SD = .663) and n-tv (M[weighted] = .03, SD = .898) were slight below respectively above zero.

The nullhypothesis H60 should subsequently be rejected and the alternative hypothesis H6a be accepted, as significant differences in the reporting could be found.

5.3 Additional Findings

Further analysis was done regarding different aspects of the media image of

Israel across the news outlets.

5.3.1 Evaluations in Opinion Pieces

In order to see how Israel was evaluated in opinion pieces in the sample, only articles of this type of text were selected, a total of 14 articles. The mean evaluation of

Israel in these articles can be seen in table 38.

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Table 38

Mean Evaluation of Israel in Opinion Pieces

Std. Publication Mean n Deviation Bild 1.20 5 .837 n-tv .00 1 .00 Spiegel .00 2 1.414 t-online 1.50 2 .707 Zeit .00 4 1.633 Total .64 14 1.216

While the number of cases is fairly small (n = 14) – n-tv published only one such text during the research period, Spiegel and t-online just two each – it is interesting to note that none of the outlets has a negative mean evaluation of Israel. In particular,

Bild (M = 1.2, SD = .837) has stood out in previous tests as portraying Israel positively, and t-online (M = 1.5, SD = .707; although the small number of cases – n = 2 – dampens the significance of this). This is in stark contrast to the findings of Beyer, who found that opinion pieces showed a clearly negative evaluation of Israel (2016, p. 432). It can be concluded that at least during times of low-conflict, Israel is portrayed either neutrally or positively in German digital news; whether the same hold true for times of high-conflict – as previous studies on print (such as Behrens, 2003; Jäger and Jäger, 2003; Troschke,

2015) suggest cannot be determined here.

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5.3.2 Topics and Evaluation

When comparing the different topics and how Israel is evaluated on average depending on it, some significant differences can be found between the main topics.

Table 39 shows the overall valency of Israel per reduced main topic. A table with a more detailed breakdown can be found in Appendix E (p. 266).

Table 39

Mean Overall Evaluation per Main Topic (Simplified)

Main Topic (Simplified) Mean n Std. Deviation Mean (Weighted) Israeli Internal Affairs -.04 188 .776 -.07 Israeli External Affairs .31 36 .920 .25 German-Israeli Topics .75 110 .826 .78 Arab-Israeli Conflict -.01 199 1.044 -.02 Other Topics .59 29 .867 .55 Total .18 562 .955 .10

Israel and Israelis were portrayed fairly positive in German-Israeli topics, this was significantly less so the case in articles on Israeli internal affair (M = -.04, SD = .776;

M [weighted] = -.07, SD = .746) and on the Arab-Israeli conflict (M = -.01, SD = 1.044;

M [weighted] = -.02, SD = 1.07). This difference is statistically significant (F [4, 557] =

17.714, p < .001). This result could be confirmed for weighted cases as well (F [4, 912] =

24.038, p < .001).

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When comparing the different news outlets, some interesting observations can be made (see table 40; a full table which includes the number of cases and the standard derivation can be found in Appendix E, p. 268).

Table 40

Mean Overall Evaluation per Topic (Simplified) and Publication

Main Topic Publication (Simplified) Bild n-tv Spiegel t-online Zeit Total Israeli Internal Affairs .20 .09 -.14 -.13 -.05 -.04 Israeli External Affairs .25 .27 1.00 -.11 .67 .31 German-Israeli Topics 1.24 .25 .77 .44 .62 .75 Arab-Israeli Conflict 1.38 -.02 -.39 -.21 -.37 -.01 Other Topics 2.00 0 .33 .75 1.20 .59 Total 1.04 .08 -.04 .02 -.01 .18

Bild evaluates Israel more positively than the other outlets, in line with the findings regarding the overall evaluation. In particular, in the Arab-Israeli conflict (M =

1.38, SD = .82) and the German-Israeli issues (M = 1.24, SD = 0.786), Israel is more positively portrayed than in the other outlets (overall M = -.01). For both general topics, this difference is statistically significant in ANOVAs (for the Arab-Israeli conflict with F

[4, 194] = 22.958, p < .001; for the German-Israeli topics with F [4, 105] = 6.904, p <

.001).

Subsequent Post-hoc tests confirm Bild as the outlier. A Post-hoc test for the

Arab-Israeli conflict (Bonferroni method, homogenous variances assumed per Levene’s 107

test, p = .314) confirmed significant differences between Bild and all other outlets (p <

.001 for each cell, see Appendix E, p. 269).

For the German-Israeli topics, another Post-hoc test (Bonferroni method, homogenous variances assumed per Levene’s test, p = .462) showed significant differences between Bild (M = 1.24, SD = 0.786) and n-tv (M = 0.25, SD = .866) at p =

.001 as well as between Bild and t-online (M = .44, SD = .613) at p < .001; the respective table can be found in Appendix E, (pp. 268).

While the mean evaluation for Other Topics in Bild is also much higher (M =

2, SD = 0), only two cases are in this category. No further testing was done in this regard due to this low case number.

5.3.3 Conflict and Evaluation

To make a comparison between the news outlets in their mean evaluation of Israel during times of conflict, a table with the means both for articles on non-conflict and articles on conflict was requested for the outlets (see table 41).

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Table 41

Mean Evaluation of Israel during Conflict and Non-Conflict per Publication

No Conflict Conflict Std. Std. Publication Mean n Deviation Mean n Deviation Bild .92 75 .912 1.59 17 .712 n-tv 0.00 95 .934 .38 24 .824 Spiegel -.02 93 .967 -.12 26 .909 t-online .01 104 .690 .07 27 .616 Zeit .06 82 .960 -.32 19 .749 Total .16 449 .951 .26 113 .971

The means indicate a difference. Bild (M = 1.59, SD = 0.712) as well as n-tv (M =

.38, SD = .934) stand out for their evaluations during conflict. The two publications provide a more positive evaluation of Israel during times of conflict than during times without conflict. This is somewhat surprising, as conflict is generally viewed as a negative thing and previous studies (Gaisbauer, 2012; Beyer, 2016) suggest that German media has a tendency to evaluate all involved parties in the Arab-Israeli conflict negatively when fighting occurs.

A two-way ANOVA confirms significant differences between the publications (F

[4, 552] = 25.191, p < .001) but not for the reporting during conflict or without conflict alone (F [1, 552] = 1.882, p = .171). A significant interaction between the Publication and the variable for conflict could also be detected (F [4, 552] = 3.374, p = .01).

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A subsequent post-hoc test (Bonferroni method, homogenous variances assumed per Levene-test, F = 2.299, p = .015) confirmed that Bild is the outlier (p < .001 for each cell; see Appendix E, p. 275, for the full table).

It is safe to say that there are significant differences between the news outlets;

Bild in particular stood out, as their reporting evaluated Israel more positively during conflict than during times without conflict. While this effect could also be found to a much lesser extend at n-tv and to an even lesser extend at t-online, this difference was not significant. On the other side, Spiegel and Zeit evaluated Israel more negatively in articles on conflict, in line with a previous study by Wetzstein (2011) and Beyer (2016), who found the same effect in their print formats.

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6. Discussion

In regards to the evaluation of the developments which are reported on, the reporting does focus on negative developments. This, of course, should not be too surprising, given the general focus of news reporting on negativity and conflict (Bohle,

1986; Luhmann, 1996) and the findings of Wetzstein, who found a strong focus on negative events in the reporting on Israel in German print media (2011, p. 22). In comparison to the previous study focused on print media by Beyer (2016), however, the reporting appears to have shifted slightly towards more negative developments. Beyer found 39.9% of the developments in his sample of German print media to be of the negative kind compared to 52.1% found here (2016, p. 382). Ambivalent and stagnant developments and events appear to have remained roughly similar, with 35.9% in the sample of 2009 (Beyer, p. 382) and 35.6% in the sample analyzed in this study. On the other hand, positive developments halved, appearing in 24.2% of the articles in Beyer's sample (2016, p. 382) but only 12.3% in the sample analyzed in this study. This comparison, however, should be taken with a grain of salt, as the focus of the studies is to some extent different; Beyer focused on the news on both Israel and Palestinians, while the sample analyzed for the purpose of this study focused solely on the reporting on

Israel. Regardless, the potential shift in the focus should be noted. However, further research – for example, a comparison between the same type of media during the different time frames – would be required to determine whether this difference can be found between print and digital media or represents an overall shift in German media.

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Responsibility for the developments was mostly located in the hands of Israel.

This is somewhat to be expected, as the sample was focused on articles on Israel.

Articles on internal Israeli topics, for example, are naturally more likely to have Israeli responsibility, which is reflected in the fact that Israel was responsible for most of the developments, regardless of whether these were positive, negative, or ambivalent. When combined, however, other parties were more likely to be portrayed as responsible than

Israel for negative developments, albeit only slightly so. Generally, the tendency gravitated towards an even distribution with the exception of Bild. The outlet stood out, as it almost exclusively portrayed Israel as not responsible for negative developments and rarely located blame at Israel.

Interesting to note is that Palestinians were mostly found responsible for negative developments, much more so than other actors. This is most likely relate to the fact that

Palestinians appeared overwhelmingly in the context of conflict in the reporting on Israel, which resulted in a disproportionate responsibility for negative developments. It should be noted, however, that this finding stands contradicts some of the findings for German print media. Troschke, who analyzed amongst other outlets Spiegel and Zeit, stated that the responsibility frame for escalation was distinctly portrayed as Israeli (2015, p. 260), a result that could not be confirmed for their digital news outlets.

Similar to Palestinians, both the USA and Iran were almost exclusively portrayed as responsible for negative developments, which is most likely also related to the context in which they appear in the reporting on Israel. In this regard, comparison to other

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countries – for example, when sampling all reporting during a time period – could offer an interesting comparison here, but was not possible with the data at hand.

During the research period, Israeli politics were distinctly the most prominent topics, corresponding with the years-long political instability,12 as no party could secure a decisive result. Apart from the election and its results itself, other topics surrounding the election, such as a criminal investigation of prime minister Netanyahu and elections promises regarding Israeli settlements in the West Bank were also highly prominent. In contrast to the findings of Beyer, who constituted that Israeli politics were reduced mainly on the positions of the prime minister, a more diverse depiction of Israeli politics could be found (Beyer, 2016, p. 566). While the prime minister was one of the actors which received the most attention, this has to be seen in the context of the elections which did take place during the research period. The opposition, however, also did receive a fair amount of attention, falling only slightly behind the prime minister, although it should be noted that the opposition consists of multiple politicians who received attention, in contrast to the prime minister as a single individual. What can be confirmed is a detachment from the portrayal of Netanyahu as the sole personification of

Israeli politics towards a broader and more diverse depiction. Interesting to note is also

12 The 2019 election was the 3rd election in two years and did not end decisively, resulting in another election in 2020.

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the negative evaluation Netanyahu receives, compared to the neutral evaluation the opposition receives across all news outlets.

This negative evaluation can in part be attributed to the depiction of the criminal investigation of the prime minister as well as his statements regarding a potential recognition of settlements, both of which appear to be largely unpopular with the German online media. This tendency can be found across all outlets. Qualitative approaches could provide some further insights in the future, how exactly Israelis and, in particular, different Israeli politicians are framed in the news.

However, the main takeaway from this is that the reporting is not focused solely on military conflict, as suggested by Beyer (2016, p. 566). Military conflict does play an important role in the reporting across all news outlets when it occurs. This is in line with the findings of the previous studies focusing on times of military conflict between Israel and other actors. However, during times without military conflict, there is still plenty of reporting on Israel. The statements that Israel is only reported on in the context of conflict, which may give the impression of a continuous escalation in the region (Beyer,

2016, p. 570), could not be confirmed. However, the strong focus on crises (such as military conflict when it does happen and the internal political crisis) does provide a negative frame in which Israel is portrayed. Although a diverse number of topics are reported on, the focus remains on a small circle of topics that are covered extensively.

Interestingly, n-tv, Spiegel, t-online, and Zeit focus mainly on the military actions by the Israelis, while Bild was the only outlet which focuses primarily on actions by

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Palestinian groups and Hezbollah. This results in a different framing of the conflict – while the former four outlets depict the events as the result of either shared or, in some cases, Israeli aggression, Bild frames mostly the Palestinians and Hezbollah as responsible for escalation. Whereas the overall evaluation of Israel leaned towards a balanced depiction – leaning towards an overall evaluation of zero, with mean of 0.18 –

Bild often stood out with more positive evaluations of Israel and Israeli actors. This tendency is particularly apparent in the reporting on conflict. While the other news outlets tended to portray all actors involved – including Israel – negatively, Bild evaluated Israel more positively than during times of non-conflict, showing a clear bias in comparison.

This finding is in line with one of the main principles of Bild’s mother company, Axel

Springer SE, which states the “right of existence of the State of Israel” as one of the company's fundamental principles (Axel Springer SE, 2021). Axel Springer himself based this principle of clear partisanship for Israel directly on the German responsibility for the Shoah and described the solidarity to Israel as a historical responsibility (see

Kraushaar, 2011). The fact that Bild’s portrayal of Israel differs this strongly from the other German news outlets bears witness to the fact that this principle appears to play an important role in the reporting of the outlet.

In line with the findings of Behrens (2003), Beyer (2016), Jäger and Jäger (2003),

Troschke (2015), and Wetzstein (2011) in regards to the print formats of Spiegel and Zeit, both news outlets portrayed Israel in particular negatively during conflict. The same can be found in the sample analyzed here, as both outlets evaluated Israel more negatively if

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conflict was involved, confirming the tendency for their digital formats as well. On the contrary, however, n-tv, t-online and especially Bild showed the opposite effect, evaluating Israel more positively during conflict. Since no studies have been done on their reporting in the past or, in the case of Bild, the print format, further research should be conducted to analyze this whether this is a recent development or has been true in the past, as well. Either way, the three outlets clearly go against the trend which were found by the previous research.

Israeli were quoted much more often than other actors, which again is not too surprising in the reporting on Israel and Israelis. While this was expected in the general sample, it is important to note that Israelis were much more often – over four times as much – quoted than Palestinians during times of conflict between Israel and Palestinians.

This does constitute a clear imbalance, as Israelis are given much more space to present their point of view on the conflict. A potential reason for this could be that the Palestinian groups involved in the conflict during the research period are Islamic Jihad and Hamas – the latter being also the controlling force in the affected Gaza strip – both of which are designated as terrorist groups in Germany, which may influence the likelihood of them being quoted. On the other side, the Israeli military appears to be the primary source of information, as they were quoted in most of the articles on confrontation. Again, this may be problematic as the Israeli military is also a participant in the conflict. On the other hand, unlike the Palestinian areas – both the West Bank and the Gaza strip – Israel is a democracy, giving the Israeli military some extend of accountability, which might

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influence the decision by news agencies and news outlets to refer to them more often.

Regardless, what also stood out was the low number of non-military and non- governmental actors which were given a voice during conflict, both for Israeli and

Palestinians, which is in contrast to Behrens (2003), who found that especially Palestinian civilians were quoted during conflict providing an image of Israeli military against

(solely) Palestinian civilians. Future research could be conducted regarding whether this tendency can also be found during prolonged periods of conflict.

A correlation was found between Israelis who were quoted to the advantage of

Israel and non-Israelis who were quoted to the disadvantage of Israel. While the research design did not allow an analysis of the direction – meaning, whether Israelis or non-

Israelis were quoted first – this could provide useful insights. As is, the data could only confirm that the two are statistically significantly likely to appear in the same article. On the other hand, no correlation could be found between the occurrence of negative evaluations of Israel in quoted and positive evaluations overall. While no definitive proof, it does indicate that non-Israelis with negative evaluations are likely to be opposed by

Israelis with positive evaluations of Israel – or vice versa. A future research design that focuses more on the evaluations and gathers quotes as closed communication acts could provide more insight into this. One of the main takeaways, however, is that in the reporting on Israel, it is mainly Israelis who are quoted. It is not a country that is only reported about, but one which is given a voice in the reporting on it, too.

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In regards to the contentual coherency of the headlines, the teaser texts, and the information in the text body of articles, a decrease compared to the findings of Beyer

(2016, pp. 512) can be noted. The number almost halved compared to Beyer's sample of

2009 print articles, which found 8.18% of the articles with a dissonant focus, while in the sample at hand, only 4.1% of the articles were contentual dissonant. The ideal would be to have no contentual dissonant articles, especially as micro-news consumption through mobile devices has increased. When only the headlines and the teaser text of articles are read, for example, because these are shown as previews on social media and news aggregator websites, presenting a different framing of events in the news in these prominent parts of the article – which are more likely to be consumed than the main text

– than in the text body could lead to a biased perception on the matters at hand. The reduced number of articles where this is the case compared to the findings of the previous study should therefore be seen as a positive development. Possible reasons for this development could include the criticism and a public debate about the issue in Germany in 2014, as well as the technological differences, which allow digital news to be edited after being published. This means headlines and text can be edited if criticism arises.

While such edits should be referenced at the end of the article, no evidence of this was found in the sample. It should be noted, though, that some digital news outlets have automated this process (Marshall, 2016); future research focused on this matter could be conducted by gathering the sample twice, once at the time of publishing, potentially automated, and once at a later time, to compare whether the content has changed.

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Unfortunately, this was not possible due to the research period chosen and the implications of the COVID19-pandemic.

Of note is that the articles which are contentual dissonant are often so to the disadvantage of Israel. Beyer proposed this in his 2016 study; however, his data structure did not allow further examination (p. 515). An exception to this trend, which could be found in n-tv, Spiegel, t-online, and Zeit, was again Bild, which instead had its contentual dissonance to Israel's advantage. A broader research, which compares the portrayal of different countries in German news, could provide insight whether this trend is exclusive to Israel or can be found generally in the reporting, regardless of state or nation.

Overall, the evaluation of Israel gravitated towards a neutral or ambivalent depiction of the country, with a slight tendency towards a positive depiction in the overall mean, caused by the outlier Bild. This publication is the only outlet that provided a distinct positive evaluation compared to the other outlets, which does constitute a bias in favor of Israel. This is, again, is in line with the principles of the mother company. It should be noted that the German press system differs in this regard from the one in, for example, the USA, as editorial guidelines are common and not regarded as inherently problematic. What should be criticized, however, that this positioning is not communicated transparently. While the key values and principles can be found on the website of the Axel Springer SE, they do not appear on Bild’s website, much less so on articles.

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Bild's positive depictions of Israel could be found across different types of articles and topics, but were in particular present in opinion pieces – where a partisan view can be expected, although it should be noted that Bild did not offer any opposing views during the research period – and regarding the Arab-Israeli conflict (as well as German-Israeli issues). In particular, Bild’s negative evaluation of Palestinians should be noted, as the news outlet has been criticized in the past for biased reporting on Muslims and Arabs (see e.g. Gutske, 2014, July 27; Schönauer, 2014, July 28).

However, these results should be considered in context, as Palestinians mostly appeared in the reporting in the context of conflict with Israel, which, so it is not necessarily possible to draw a conclusion regarding their general depiction of Palestinians from the sample. Further research in this regard should be conducted before determining a clear bias by the news outlet in this specific matter.

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7. Conclusion

In conclusion, the sample of news outlets analyzed can be organized into two groups – one with a relatively balanced portrayal of Israel – consisting of n-tv, Spiegel, t- online, and Zeit – and Bild, which took a more one-sided stance, often portraying Israel and Israelis more favorably than the other outlets.

The dominant topics in the reporting are politics and conflict. On the one hand, this contradicts results from earlier studies, that the reporting is solely focused on war and military engagements. On the other hand, other topics like economy, culture, and social issues fall behind and are underreported. The German-Israeli relations naturally also play a large role in the German reporting. These tendencies can be found across the two groups, although Bild is much less focused on Israeli internal issues and more focused on the German-Israeli aspects than the other outlets.

There is a strong spotlight on the prime minister, much more so than on any other actor in the reporting, but compared to previous studies on print, the Israeli actors present in the reporting are more diverse. Especially the Israeli opposition to prime minister

Netanyahu was very present, mostly due to the election during the research period. The

Israeli military also plays an important role and is a focus of the reporting when conflict breaks out, more so than their adversaries. Civilians and the different government branches also play an important role, but overall fall behind politicians in terms of quantitative presence in the reporting. International actors play a large role in the reporting on Israel, particularly the UNO and the EU, as well as the USA and Iran. This

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highlights the unique role of Israel in the international community, which is marked by political tensions. Palestinians are almost exclusively present in the reporting in the context of either conflict or the question of Israeli settlements, as are the other regional actors. This could also be confirmed in both groups.

Generally, Israeli actors are portrayed positively, especially compared to the non-

Israelis in the reporting. Israeli civilians, NGOs, and businesses were particularly positively evaluated in the sample. A strong contrast can be seen in the evaluations of settlers and of the military, which were both portrayed slightly positively by Bild but strongly negatively by all other outlets, in particular by Spiegel and t-online. Palestinians were overwhelmingly portrayed negatively, potential due to them mostly appearing in conflict. Other actors have a tendency to also be portrayed negatively but mostly gravitate towards a neutral or ambivalent portrayal. One important exception to this is the Boycott,

Divest, Sanction (BDS) movement, which is evaluated negatively by both groups. To sum the depiction of the actors in the reporting on Israel up, all actors have a tendency to be portrayed negatively, but Israelis are generally evaluated more positively than non-

Israelis. Conflict also did not play a significant role in the evaluation of Israelis. This holds true for all news outlets in the sample.

In both groups, Israelis were much more often quoted than other actors. During conflict, the Israeli military was usually referred to as the primary source for information, much more so than the advisory groups.

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When positive evaluations of Israel are quoted of Israelis, there is a significant correlation that non-Israelis are also quoted with negative evaluations of Israel by non-

Israelis in the same article. This could be confirmed for all five news outlets.

The content of the headlines, teaser text, and main text body is coherent in the majority of the articles. When dissonance between the parts of the articles occurred in n- tv, Spiegel, t-online, or Zeit, they were to the disadvantage of Israel, portraying the country and its actors in a more negative light in the headlines and teaser than in the main text. When dissonance occurred in Bild, however, the opposite can be found, as Israel and

Israelis are portrayed advantageously. The overall relatively small number of contentual dissonant articles, especially when compared to previous studies, however, is a positive development.

No distinct differences can be found between the depiction of Israel regarding to the role the country had in the reporting. When weighting the cases according to the relevance of the article, the general tendencies remain but are at times slightly refined.

This refinement often takes the form that evaluations tend to gravitate more towards the overall mean.

Overall, Israeli was portrayed in a mostly balanced way in n-tv, Spiegel, t-online, and Zeit, only deviating slightly from the ideal mean evaluation of zero. While criticism and negative evaluations can be found, this is not excessively the case, nor can an overall biased portrayal be found – with the exception of Bild, that is. Bild is the only news outlet that overall evaluates Israel clearly positive, constituting a bias.

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Ideally, the quantitative findings of this study should be confirmed by a qualitative, more linguistically focused approached in order to analyze the finer details of evaluations, which could not be done in this study due to the time constraints. As-is, the reporting appeared overall reasonably balanced, especially in contrast to previous studies focused on times of conflict.

While the reporting is focused on negative developments, it is not entirely confined to it as it was in the past. In particular conflict still does play an important role, but it’s not the sole defining topic of the reporting. A much broader spectrum of matters which concern Israel can be found in the reporting, and especially the different positions in the Israeli politics were laid out in the reporting. Instead of focusing on Netanyahu as the sole actor, different politicians were given a voice and their perspectives were portrayed. In this regard, a much more differentiated depiction of Israel could be found than in past reporting.

Overall, the results suggest a development in the German reporting on Israel in the past 10 years, which moved from a one-sided and often anti-Israeli position towards a more balanced one with different perspectives – with the exception of Bild, which took a decidedly biased point of view. Especially the tendency not just by them, but also by n-tv and t-online to evaluated Israel more positively during conflict stands in strong contrast to the very negative depiction of the country during conflicts in the 2000s.

While further research in regards to the potential causes of this shift are advised, the findings here suggest that a development has taken place, potentially due to the public

124

debates on the matter and supported by the previous research. The shift could also be seen as a testimony an increased awareness of journalists to the problematic aspects of monoperspective reporting during conflict. Future research in regards to the production- side of journalism, added intermedia comparisons and audience-focused studies could provide fruitful insights in these regards, to further explore the implications presented here. Comparisons of the evaluations of other countries in the German media on a large scale could also be conducted in order to determine whether Israel is overly affected by the focus on negativity.

The study at hand provides a good foundation for future research to further explore the matter. As is, it certainly dismisses the notion that Israel is portrayed unfairly negative – as it has been, in the past – and that the reporting is focused only on certain issues. Instead, a rather broad spectrum of topics can be found in the German reporting on Israel. A fair share of criticism can be found as well, so it does not appear that the reporting swung in the opposite direction, but rather towards a fairly balanced depiction overall.

125

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Appendix A: Tabluar Overview of the Literatur

Study IFEM 2002 Behrens 2003 Author(s) Institut für empirische Medienforschung (Institute for Rolf Behrens empirical media research), Cologne Theoretical News factors, stereotype background Agenda setting, news bias research

Research time First Intifada 1987-1992; frame 1999-2002 Second Intifada 2000-2002

Research sample 891 TV reports by ARD, ZDF, 345 articles by Der Spiegel RTL and Sat.1 Methodology Mixed quantitative and Mixed quantitative and qualitative content analysis qualitative content analysis Main findings - Predominantly neutral - Dominant negative reporting characterization of Israel - 3% negative bias, 2% - Israel is responsible for positive bias escalations - shift during the conflict - Negativity as the most towards depicting Israel important factor for the as the aggressor reporting - civilian victims were - Antisemitic and racist shown equally stereotypes against both - Israel was depicted as Jews and Arabs could be powerful, cold, brutal found - Palestinians as weak - Personalization of the and helpless conflict (Ariel Sharon - The public broadcasters against Jassir Arafat) reported less - Dichotomy of “Israeli dramatizing than the tank against Palestinian commercial ones stone-thrower” prevalent

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Study Jäger & Jäger 2003 Medien Tenor 2003a & 2003b Author(s) Siegfried Jäger, Margerete Jäger Medien Tenor13 Theoretical Linguistics Agenda Setting background Research time September 2000–August 2001 1st January–31st October .2003 frame Research sample FAZ, FR, Der Spiegel, SZ, 47,089 TV reports from ARD, Tagesspiegel, taz, Welt ZDF, BBC, RTL, SAT.1, ProSieben, ABC, NBC, CBS Methodology Critical discourse analysis Quantitative content analysis

Main findings - Both Israelis and - Reporting on Israel was Palestinians were dominated by the portrayed negatively conflict aspects and - Israel was shown as an negativity inhuman military power, - Palestinian attacks were Palestinians as a weak, often justified by Israeli uncivilized and military actions and anonymous mass injustice - Personalization of the - Regardless, Palestinians conflict were portrayed even - Antisemitic stereotypes more negatively than mostly as religious Israelis references - Paternalistic view on the conflict is common

13 It should be noted that the Medien Tenor institute has been accused by media organizations and former employees to manipulate research results (see ARD und ZDF lehnen Auszeichnungen ab [ARD and ZDF refuse awards], 2004, September 24Grimberg, 2008, April 16; Ludwig, 2004, September 9;).

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Study Medien Tenor 2006 Beyer 2007 Author(s) Medien Tenor Rober Beyer

Theoretical News bias Linguistics, news bias, background stereotype research

Research time 21st July–3rd August 2006 August 2005–April 2006 frame Research sample 456 TV reports by ARD 140 TV reports in Tagesschau (Tagesschau/Tagesthemen) and (ARD) ZDF (Heute/Heute Journal)

Methodology Quantitative content analysis Linguistic quantitative content analysis Main findings - Bias against Israel - The reporting focused on - Israeli military was portrayed negative developments as aggressor, Hisbollah as rather than positive ones retaliating - The Israeli-Palestinian - Structure of reports conflict dominated the suggested that the escalation reporting was Israels fault - Israeli and Palestinian - Israel was criticized four internal affairs were given times as much as Hisbollah the same attention - Hisbollah was rarely blame - Explicit valuations were dfor the escalation – only if rare and affected Israelis both sides were blamed and Palestinans similarly - Implicit valuations targeted Israel more often than Palestinians, but no significant difference could be found - No antisemitic stereotypes could be found, but Israeli and Jewish were used interchangeably

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Study Langenbucher & Yasin 2009 Maier 2011 Author(s) Wolfgang R. Langenbucher, Martin Maier Guni Yasin Theoretical Akteursorientierte News bias background Journalismusforschung [actor oriented journalism research] Research time Summer 2004 15th December 2008–31st frame January 2009 Research sample 17 Interviews with 350 articles by German left- correspondents for German wing newspapers (Junge Welt, news media Neues Deutschland, Freitag, Jungle World) Methodology Qualitative Interviews Discourse Analysis Main findings - Discrepancy between the - Junge Welt, Freitag and self-image of the journalists Neues Deutschland took and previous studies on overly critical, at times biased reporting on Israel antizionist and even - No conscious bias, antisemitic viewpoints journalistic standards were - These included a held high paternalistic view on the - Some journalists felt that the conflict, questioning Israels bias is caused by the editors right to exist and traditional who pick the stories antisemitic imagery such as blood libel - At times, comparisons between Israel and Nazi- Germany were drawn - Jungle World adopted mostly pro-Israeli positions - Palestinians were often prejudged - Positions not clearly in favor of Israel were described as apologetic and antisemitic

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Study Maurer & Kempf 2011 Wetzstein 2011 Author(s) Markus Maurer, Wilhelm Irmgard Wetzstein Kempf Theoretical News Bias, Conflict and Peace Constructive Conflict background studies Journalism Research time Second Intifada (28th 2008, 2008/2009 Gaza War frame September 2000 – 8th February (27th December 2008 – 19th 2005); 2008/2009 Gaza War January 2009), (27th December 2008 – 19th January 2009) Research sample 396 articles by FAZ, FR, SZ, taz 188 articles by The Guardian and Die Welt Weekly, Profil, Die Zeit, Der Spiegel

Methodology Quantitative Content Analysis Mixed Qualitative and Quantitative content analysis Main findings - Negativity dominates the - Der Spiegel was the most reporting balanced, giving both sides - Criticism of Israel could be about the same room found significantly more - Die Zeit had a pro- often than of the Palestinian Palestinian bias, favoring side their point of view - At the same time, Israeli - The Guardian Weekly and actions were often portrayed Profil had a pro-Israeli bias as defensive, negating some - The assessment was done of the bias whether positions and - Comparing the two conflicts, perspectives were while reporting on Israeli portrayed, not how they violence increased, so did were portrayed the justifications - Overall, slight pro-Israeli bias - This bias could have the opposite effect and increase antisemitic stereotypes

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Study Gaisbauer 2012 Hempel et al. 2014 Author(s) Felix Gaisbauer Anja Hempel, Sebastian Bähr, Melanie Neumann Theoretical News bias, framing Framing background

Research time Second Intifada (28th 2012 frame September 2000 – 8th February 2005); 2008/2009 Gaza War (27th December 2008 – 19th January 2009) Research sample 396 articles by FAZ, FR, SZ, 128 opinion pieces in Die Welt taz and Die Welt and Jungle World Methodology Quantitative content analysis Quantitative content analysis with cluster analysis Main findings - Palestinian victims were - Die Welt mostly had opinion reported on more often than pieces focusing on the Israeli ones, mostly due to a strategic goals of actors in focus on military rather than the region with little to no civilian victims moral evaluation, as well as - Palestinians were portrayed a focus on Islamism as a more often as the aggressor threat during the two conflicts - Jungle World focused more - During the Intifada, Israel on diversity of Israeli actors, was portrayed as the victim; in particular Israeli domestic during the Gaza War, politics Palestinians were portrayed - Both newspapers covered as the victim antisemitism in Germany - Increasing pro-Palestinian and German historic bias and decreasing pro- responsibility to a similar Israeli bias from Intifada to extend Gaza war - Die Welt used a more - No significant difference emotionalized language, in between the newspapers particular explicit could be found comparisons to the NS

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Study Witte 2014 Troschke 2015 Author(s) Mareike Witte Hagen Troschke

Theoretical Agenda setting, news bias Linguistics, news bias background Research time First Gaza War (27th December November and December 2012 frame 2008 – 19th January 2009), Second Gaza War (11/14/12 – 11/23/2012) Research 302 articles by FAZ and taz 172 articles by FAZ, taz, Die sample Welt, Spiegel, and Die Zeit Methodology Quantitative content analysis Qualitative content analysis

Main findings - Israel was mostly depicted as - Solely critical valuations of the aggressor during the First Israel were rare, but ‘de- Gaza war but less during the realizations’ – skewing the second one perception of Israel – were - taz reported on Israel more fairly common negatively, but the reporting - The most common ‘de- became more balanced over realizations’ were that Israel time waged a war to influence - Causes of the conflict went upcoming elections, that unreported during both wars Israel is that (sole) aggressor - The Israeli point of view was and that Israel (intendedly) more prevalent during the injures and kills Palestinian Second Gaza War, most likely civilians due to better PR by the IDF - 24 positive, 120 neutral and - A general tendency to 439 negative oversimplify the conflict conceptualizations of Israel - Significant differences were found in the material between the two wars, not the - 61 of the negative two newspapers, as both conceptualizations were became more balanced identified as antisemitic - Troschke confirmed previous studies done on the 2012 Gaza war

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Study Beyer 2016 Author(s) Robert Beyer Theoretical Linguistics background Research time 1st December 2009 – 31st March 2010 frame Research sample 705 articles by Die Welt, SZ, FAZ, Die Zeit, Der Spiegel, Focus and Nürnberger Nachrichten

Methodology Cognitive-linguistic text analysis (mixed qualitative and quantitative content analysis) Main findings - Strong focus on negativity in the reporting - In particular, Israeli actions were reported on more negatively than Palestinian ones (1 to 5 ratio) - A paternalistic view on the situation was dominant in all newspapers - Palestinian perspectives were more common than Israeli ones - Israel was shown as the aggressor more often, as such, the responsibility for de-escalation was put in Israels hands - The negative bias against Israel was found across all newspapers - Criticism of Israel was often in more exposed text position, such as the headline or the lead - Evaluations by other actors – such as interview partners – were always marked as such - Evaluations by the authors are rarely marked - Positive developments in the conflict were often put down or deprecated in a sarcastic way - Israel is portrayed more diverse than the Palestinians, who are often portrayed as a homogenous mass of either religious fundamentalists or victims of violence - While Beyer found a trend regarding negative evaluations of Israel, no significant bias could be found - Overall, both parties are viewed negatively in the German press, but Israel is hit harder by the criticism

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Appendix B: Nullhypotheses and Alternative Hypoytheses

H1 Israel is mostly mentioned in the news in the context of negative developments.

H10 Israel is mentioned evenly in the context of different developments

H1a Israel is mentioned mostly in the context of negative developments

H1.1 The predominant theme of the reporting is conflict/military action.

H1.10 Conflict/military action is not the most common theme in the reporting.

H1.1a Conflict/military action is the most common theme in the reporting.

H1.2 If responsibility for negative development is located, it is Israeli responsibility.

H1.20 There is no significant correlation between negative developments and

Israeli responsibility.

H1.2a There is a significant correlation between negative developments and Israeli

responsibility.

H2 Actors who appear in the reporting are predominantly not Israeli.

H20 If actors appear in the reporting, they are not Israeli.

H2a If actors appear in the reporting, they are Israeli.

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H2.1 If Israeli actors appear in the news, they are evaluated negatively.

H2.10 If Israeli actors appear in the news, they are not evaluated negatively than

other actors.

H2.1a If Israeli actors appear in the news, they are evaluated more negatively than

other actors.

H2.2 Israeli actors are only evaluated negatively in the context of conflict; if they appear in another context, they are evaluated positively.

H2.20 There is no significant correlation between the evaluation of Israeli actors

and conflict.

H2.2a There is a significant correlation between the evaluation of Israeli actors

and conflict.

H3 In times of conflict with Palestinians, Israeli actors are quoted more often than their

Palestinian counterparts.

H30 There is no significant difference between the amount Israeli and Palestinian

actors are quoted during conflict.

H3a There is a significant difference between the amount Israeli and Palestinian

actors are quoted during conflict.

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H3.1 If an Israeli actor is quoted to the advantage of Israel, another actor is quoted to challenge that.

H3.10 There is no correlation between the occurrence of Israeli actors who are

quoted to the advantage of Israel and non-Israeli actors who are quoted to the

disadvantage of Israel.

H3.1a There is a correlation between the occurrence of Israeli actors who are

quoted to the advantage of Israel and non-Israeli actors who are quoted to the

disadvantage of Israel.

H3.2 If an actor is quoted to the disadvantage of Israel, this is not countered by an opposed opinion.

H3.20 Th ere is no significant correlation between actors who are quoted to the

disadvantage of Israel and actors who are quoted to the advantage of Israel.

H3.2a There is a significant correlation between actors who are quoted to the

disadvantage of Israel and actors who are quoted to the advantage of Israel.

H4 The headlines, teaser text, and text body are usually not contentual coherent.

H40 The headlines, teaser text and text body are not contentual coherent in the

majority of articles.

H4a The headlines, teaser text and text body are contentual coherent in the

majority of articles.

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H4.1 If headlines, teaser text, and text body are not contentual coherent, it is to the disadvantage of Israel.

H4.10 If headlines, teaser text and text body are contentual dissonant, it is not to

the disadvantage of Israel.

H4.1a If headlines, teaser text and text body are contentual dissonant, it is to the

disadvantage of Israel.

H4.2 If there is no contextual coherence, the headlines paint Israel in a more negative light than the teaser text and text body.

H4.20 If there is contentual dissonance, the headlines do not portray Israel more

negatively than other parts of the article.

H4.2a If there is contentual dissonance, the headlines portray Israel more

negatively than other parts of the article.

H5 The reporting on Israel has a negative bias.

H50 The reporting on Israel does not have a negative bias.

H5a The reporting on Israel does have a negative bias.

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H6 There are no substantial differences between the different media outlets regarding their reporting on Israel.

H60 There are no significant differences between the different media outlets

regarding their reporting on Israel.

H6a There are significant differences between the different media outlets

regarding their reporting on Israel.

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Appendix C: Codebook

A) Sample material

1. Media sample The sample consists of 5 German online news outlets: Bild.de, n-tv, Spiegel Online, t- online, and Zeit Online. These websites are chosen according to their daily and weekly reach in Germany, as well as to provide a broad sample from different types of online news media. The sample includes all news articles published on their web pages. Audio and video material are not included; user-generated content such as comments as well as content from newsletters are not included.

2. Sample period The analysis period is defined from September 1st 2019 to December 31st 2019.

3. Analysis unit The recording unit is the news article. A news article is defined as a thematically independent text published on the website of the news outlet. An article can be identified by its own headline and its individual link on the main domain of the news outlet. The article must contain text. Further characteristics, though not necessary, may be the assignment to a department, subline, teaser text, and the inclusion of pictures. Background information and info boxes are considered part of the article as long as they are found under the same link.

4. Data collection criteria Included are all articles which contain the term ‘Israel’ in their headline, teaser text or text body. In order to collect the articles, the search bar on the website of the news outlet was used. While the goal is to analyze article which by that references the country Israel as well as Israeli actors, whether this is the case has to be determined during the coding process. The page containing the article was downloaded as is in order to preserve the original layout.

5. Variables Variables are numbered 1 through 60.

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B) Procedure

The downloaded articles are viewed in a browser for the coding process, similar to how they would be encountered on the website. Coding is done in Microsoft Excel and MAXQDA. Unless otherwise noted, the coding will be done on an Excel sheet; for some variables, MAXQDA should be used for the coding and the results will then later be transferred to the Excel file. These variables are marked as such.

1. Formal categories Coding of the formal categories.

2. First read First read of the article, marking any parts that might stick out.

3. Main read Main read, sentence for sentence, paying special attention to the categories.

4. Coding Coding the text according to the coding scheme.

5. Control Checking if all variables have been coded, coding any that might have been overlooked.

C) Formal categories v1 Article number The articles should be numbered in succession: 1-n. v2 Identifier code = Combination of the publication, year, month and day of publication as well as running number for the articles of that day. The files of the material are named in this manner as well.

XXXX-YYYY-MM-DD-ZZ

XXXX = Abbreviation for the news outlet (bild/ntvd/spio/tonl/zeit) 160

YYYY-MM-DD = Year, month, day of the publication ZZ = running number of articles on that day in that outlet v3 Link = Link to the article on the website. v4 Publication = Name of the news outlet the article published in.

1 Bild.de 2 n-tv.de 3 Spiegel Online 4 t-online 5 Zeit Online v5 Date = Date on which the article was published, format YYYY-MM-DD. v6 Section = Section in which the article was published. The section can usually be determined as it is signified in the navigation on the website as well as in the link.

Due to the fact that some German section names which do not have a proper equivalent in US news, in two cases the German name was chosen for the variable. Panorama (60) refers to a section which usually combines miscellaneous articles which do not fit into other sections, often soft news and human interest stories. Daily Summary (100) is a section which in which short summaries of the news of the days are given, often in the form of a briefing. This is usually done either at the beginning or the end of the day. It is also possible that the news are added throughout the day in the form of a news ticker. While different news outlets may have different names for this section (e.g. ntv “Der Tag”, SPIEGEL “Die Lage”), they should be coded in this category as long as they fit the description of a daily summary.

10 Breaking News 161

20 Politics 30 Economy/Business 40 Culture 50 Entertainment 60 Panorama 70 Opinion 80 Sports 90 Local news 100 Daily Summary 110 Digital 120 Gesellschaft (social issues) 130 Science 140 Religion 150 Travel 160 Work/Career 170 Entdecken (discover) 180 History 190 Leben (life) 200 Magazin (magazine) 210 Advise 220 Other 999 Not applicable v7 Type of text = The type of text of the article according to its length and writing style.

If the type of text is provided in the article, code accordingly. If no type is stated, code according to the coding scheme below.

1 Newsflash: A short text on current developments, usually giving only the most important information, such as the actor(s) involved, location, time and a brief summary of events or developments. Further background information is usually not given. Formal style of writing. 162

2 News report: A longer, more comprehensive article on a topic. Often segmented by subheadlines, provides context and background information. Formal style of writing.

3 Feature: Longer, more narrative depiction of the news event. Less formal and more expressionist style of writing, containing subjective impressions of events, usually by eyewitnesses. Often focused on human-interest- stories.

4 Opinion: Subjective and argumentative, presenting a position on a matter. Should be marked as such.

5 Interview: Dialogue with one or more persons. Usually either on a specific topic or more generally. The interviewee is usually introduced in the beginning of the text. Indicator is a question-answer-scheme.

6 Review: A critical appraisal of a cultural product, such as a book, a movie or a play, although other types of products can be review as well. Subjective evaluation often in a less formal style of writing.

7 Portrait: A description or analysis of a person. The focus is on the person may include personal information.

8 Analysis: Deep assessment of a current situation, often discussing different implications of the actions of 163

involved actors or future developments. Often written by or with the input of experts.

9 Column: Reoccurring opinion piece which focuses on the authors personal experiences. The opinion aspect can be pronounced or secondary, depending on the author. Informal style of writing.

10 Report A text which provide background information on issues. Includes scientific reports in newspapers.

11 Dialogue A dialogue between two or more participants. Unlike in an interview, there are little to no questions asked by a moderator, but is instead marked by a back and forth between the participants.

12 List An article which discusses multiple aspects of a topic in the form of a list, often with a short description or review. May include a ranking.

13 Obituary An article which reflects on the life of a recently deceased person of public interest.

14 Press review A short overview of articles in the press on a certain issues. Often includes international media.

15 Other (open)

v8 Length = Length of the article in number of words: 1-n

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All words in the article are counted, including the headline and subline, as well as descriptions under images. Counting should be done using the current version of Microsoft Word 365, Version 2012. v9 Source 1 = News agency sources cited in the article.

The news agencies which are cited as sources for the article, usually either at the beginning or at the end of the text. Sources for the images, if cited independently from the sources for the text, do not fall into this category. A problem which may arise is that the authors of the text often are also marked by two or three character codes, making it hard to differentiated between author and news agency used. For example, in the source citing “jme/dpa/apa”, the first (“jme”) marks the author, while the other two are news agencies. Since a differentiation without knowing the codes of all the authors is not possible, only the most common news agencies will be coded and there is no open coding, in order to not cause any confusion between the codes. Up to three sources can be coded. Coding should be done according to the mention in the article.

1 = AFP 2 = AP 3 = APA 4 = dpa 5 = REUTERS 6 = KNA 7 = SAD 8 = sid 9 = ITIM 10 = other 999 = No source mentioned/not applicable v10 Source 2 = Same coding system as v9. 165

v11 Source 3 = Same coding system as v9. v12 Number of images = Number of images on the main article page: 0-n

The number of images that is immediately visible on the article page is counted. For galleries, only the first picture (the one immediately visible) is counted and only if it does not refer to a different page. v13 Type of image = The type of images in the article.

This variable should only be coded if there is at least one image in the article. Multiple images of the same type are coded as such. If there is more than on type of image, the variable is coded as multiple types of images.

1 Photograph

2 Infographic/table/data visualization

3 Map

4 Multiple types of image

5 Illustration

D) Content categories

v14 Relevance = To what extend does the reporting actually cover Israel, Israelis and Israeli affairs.

The variable differentiates to which extend – if at all – the text is on the matter of the country of Israel, Israeli citizens or Israeli organizations. Since the criteria for data

166

collection is only the mention of the key word Israel, articles may include individuals who bear the name ‘Israel’, as well as only brief mentions of Israel and Israeli actors. Relevance must be coded.

0 No relevance Articles which have no mention of the country Israel or Israeli actors at all.

1 Minor mention Israeli and Israeli actors may be mentioned briefly, but are not a focus of the article.

2 Secondary theme Israel and Israeli actors play a major role in the reporting, but are not the main focus of the reporting.

3 Main theme Israel and Israeli actors are the main focus of the reporting. Other themes may be discussed also, but are given less attention. If two or more topics are discussed to the same amount, they are all coded as main themes. v15 Main topic = The topic which is given most attention in the article.

The main topic is the topic which is the thematic priority of the article. In order to identify the main topic, the whole article should be considered. Indications for the main topic can often be found in the headline and the lead and in some cases subheadlines. The main topic is usually closely related to the occasion of the reporting. If more than one topic is covered, the topic which is given the most attention should be coded. Should all topics be given the same amount of attention, the more general topic should be coded. Only if

167

this is not possible, the variable should be coded as multiple topics. A topic must be coded. Should none of the specific manifestations below apply, the more general code should be coded, e.g. under Israeli internal affairs, Israeli external affairs and so forth.

The topic Israeli internal affairs summarizes all internal issues in Israel. This includes political disputes between politicians, parties and the government as well as administrative bodies, protests by civilians and NGOs as news regarding national sports and the economy. A major difficulty will be the differentiation between Israeli internal security and the Arab-Israeli conflict, in particular the conflict between Israel and Palestinian groups. Coding should be done according to whether both sides are considered (for example, if the Israeli handling of security at the Temple mount only briefly mentions Palestinian complaints, it should be counted as Israeli internal security, but if the Palestinian critic is presented more thoroughly, e.g. by quotes, it should be coded as Arab-Israeli conflict). The judgement of the coder is important to determine which code applies. All actions which involve violent means by Israeli agencies should be coded as Israeli military action, regardless whether one of the military branches, the police or secret services are involved. Events where the responsibility is unclear but Israeli military involvement is suspected in the article should be coded here as well. Violent actions by any Palestinian actor (government, terrorist groups, individuals) should be coded as Palestinian military actions. Similarly, actions where the group or individual responsible cannot be determined for sure should be coded as such (e.g. individual rocket attacks). The question of Israeli settlement may provide another problem area, as the boundaries between the different topics these issues touch on may be muddied, such 168

as Israeli internal politics, external politics, international politics and even internal politics of non-involved countries. All texts which discuss any matters involving settlements should be coded under Settlements. All confrontations between Israel and the Palestinians as well as other countries in the region should be coded under the overarching topic Arab-Israeli conflict. Albeit technically not an Arab nation, this will include Iranian actions regarding Israel. The variable includes military conflict as well as diplomatic affairs. If diplomatic meetings are mediated by third parties such as the UNO, EU or other countries, these should be coded under International politics. Actions involving settlements will be coded here as well, unless they are strictly limited to Israeli internal politics. Topics may overlap, in that case the more specific topic should be coded. Since often more than one topic is covered in an article on foreign affairs, the coder should code one topic, the one which is given most attention, as the main topic and up to two other topics as minor topics.

10 Israeli internal affairs 11 Internal politics 12 Internal security 13 Government decisions 14 Economy 15 Sports 16 Sciences 17 Culture 18 Religion 19 Other Israeli internal affairs 20 Israeli external affairs 21 State visits/meetings 22 Economy/Trade 23 Sports (e.g. national teams and athletes) 24 International politics 25 Other Israeli external affairs 169

30 German affairs 31 German government decisions/positions 32 Germany internal politics 33 German NGO action 34 Holocaust 35 Antisemitism in Germany 36 Economy/Trade 37 Protest 38 Culture 39 Other German-Israeli issues 40 Arab-Israeli conflict 41 Israeli military actions 42 Palestinian military actions 43 Conflict involving other actors in the close region 44 Negotiations (diplomatic relations) 45 BDS Movement 46 Settlements 47 Palestinian internal affairs 48 Iranian affairs 49 Internal affairs of other actors in the region 50 European politics 51 EU politics 52 UK politics 53 Russia 54 Denmark 60 International politics 61 United Nations 62 USA politics 63 India 64 International NGO 70 Special topics 71 Attack on Halle synagogue 72 Olympia Berlin 2036 73 Jewish Museum Berlin 80 Other topics 81 History 82 Oddity 170

83 Crime 84 Biography/Portrait 85 Media 86 Obituary 87 Personal experience 88 Travel 89 Science 999 Not applicable v16 Minor Topic 1 = Secondary topic which is discussed in the article, but not the main focus.

Same coding system as v15. v17 Minor Topic 2 = Tertiary topic which is discussed in the article, but not the main focus.

Same coding system as v15.

News factors = The reasons the event was published.

The news factors are the criteria which make the event(s) in the article news worthy. Since usually more than one value plays into this, the factors will be coded according to their appearance in for the article. While it’s not possible to determine with absolute certainty which factors did play a role from the articles alone, it is possible to deduct which ones most likely did play a role. News factors often overlap. They will be therefore coded individually according whether they do appear to a relevant extend. In the case of relative factors, the deciding argument should be whether the article would have been published if not for this factor. Coding should be done conservatively (when in doubt, code as non-occurring) according to the coders best judgement. Since the news factors are dependable on values – and therefore, culture – they do not apply universally. For 171

example, the news factor ‘proximity’ includes geographical as well as cultural closeness, both depend on the country where the news is published. The variables here should therefore be coded with a German audience in mind. v18 Conflict = Conflict and violence are often reported due to their dramatic effect.

0 = no (major) factor 1 = major factor v19 Eliteness = Events and developments which concern global powers – internationally more influential countries and companies. Also includes events which concern rich, powerful or famous individuals.

0 = no (major) factor 1 = major factor v20 Impact = Impact on the target audience. An event which will affect the audience directly is more likely to be reported on than an event which does/will not affect them at all personally.

0 = no (major) factor 1 = major factor v21 Unexpectedness = Sudden events or developments with unexpected developments are more likely to be reported on.

0 = no (major) factor 1 = major factor v22 Timeliness = Events that have happened recently, are ongoing or are expected to happen soon.

0 = no (major) factor 1 = major factor 172

v23 Negativity = Negative developments are likely to be reported.

0 = no (major) factor 1 = major factor v24 Positivity = In some cases, positive developments are reported as well, especially if a negative outcome was expected or in some fields, e.g. sciences or sports.

0 = no (major) factor 1 = major factor v25 Unambiguity = Events with clear implications are more often reported on that events which depend on a deep understanding of the implications.

0 = no (major) factor 1 = major factor v26 Personalization = Human interest stories and events which can be as the actions of individuals or how events affect specific individuals, often people the audience can relate to.

0 = no (major) factor 1 = major factor v27 Superlativeness = Events which large scale, scope or high intensity are more likely to be reported on.

0 = no (major) factor 1 = major factor v28 Continuity = Events which were previously reported on are more l likely to be reported on further if new developments arise. Continuity should only be coded if previous reports are referenced in the article. 173

0 = no (major) factor 1 = major factor v29 Valency = The valency of the developments in the article.

The valency of the developments in the reporting aims to capture how the nature of the occasion of report is portrayed. The question is whether the news is portraying the event as a positive, negative or neutral development. This should not be confused with the evaluation or personal opinion of the author(s). Rather, this variable should capture whether the development adds to the resolution of the problem or conflict or aggravates it from the observer’s perspective. An example would be an escalation of military conflict, which is generally regarded as a negative development, in contrast to negotiations between the conflict parties, which would generally be viewed as a positive development. If an article includes both aspects of positive and negative developments or portray the development as stagnating it should be coded as ambivalent. This variable may not apply to all news reports.

+1 Positive development 0 Ambivalent developments/stagnation -1 Negative development 999 Not applicable v30 Actor 1 = Main actor in the article.

Actor may describe the individual, the group of persons, the organization or the institution which is either responsible for the action(s) the article is reporting on or is the one affected by an action. This will most likely be politicians,

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other prominent figures of public interest and government institutions such as the military. Up to five actors can be coded per article. The main actor is the one given most attention in the article, either by being the subject of the article or by being quoted. Most attention is defined as most often mentioned in the article. The author(s) of the article will be excluded from this. Should more than five actors be mentioned in one article, the five ones which are mentioned most often will be coded. Generic references are non-specific references to the country or its people where it is not clear which actor is meant, such as “Israel lays out plan to…” or “Germany tries to…” The same actor be referenced in different ways, for example prime minister and Nethanyahu. Representatives of organizations or institutions should be coded as the institution. The roles may overlap, for example an opposition Knesset member may also be a member of the opposition. In such cases, the coding should be done depending on in which role the actor appears in the article, according to the best judgement of the coder. In cases where the exact role is not clear, the more generic variable should be coded. This variable should be coded with MAXQDA.

100 Israel (state, region, generic references) 110 Israeli civilian 111 Settler 112 Protestor 113 Religious person/group 114 Scientist 115 Musician 116 Athlete 117 Business person 118 Actor 119 Author 175

120 Politician 121 Prime Minister 122 Cabinet member/Minister 123 Knesset member 124 Opposition 125 President 130 Military/security forces 131 Minister of Defense 132 Military leader 133 Soldier 134 Police 135 Secret service 136 IDF/IAF 140 Other state institution 141 Fire department 142 Medical personnel 143 Court/Judge 144 Local/regional government 150 NGO 151 Union 160 Media/press 170 Business/Company 180 Government 181 Ministry of Foreign Affairs 182 Ministry of Defense 183 Ministry of Interior 184 Ministry of Justice 185 Ministry of Transportation and Road Safety 186 Ministry of Finance 187 Ministry of Tourism 188 Ministry of Public Security 189 Other ministry (open) 200 Germany (state, region, generic references) 210 German Civilian 211 Protestor 212 Religious group 213 Scientist 176

214 Musician 215 Celebrity 216 Athlete 217 Artist 220 Politician 221 Chancellor 222 Minister 223 Member of Bundestag 224 Opposition 225 President 226 Local politician 230 Military/security forces 231 Minister of Defense 232 Police 233 Secret service 240 Other state institution 241 Court/Judge 242 Local/regional government 250 NGO 251 Museum 260 Media/press 270 Business/Company 280 Government 281 Federal Foreign Office 282 Ministry of Interior 283 Other (open) 300 Palestine/Palestinian (generic reference) 310 Palestinian civilian 311 Protestor 312 Religious Group (non-militant) 313 Musician 320 Palestinian politician 321 President 322 Minister 323 Hamas official 324 PFLP 330 Palestinian Military/Armed group 177

331 Palestinian National Security Forces 332 Hamas 333 Islamic Jihad 340 Palestinian NGO 400 Other Arab, non-Palestinian actor 410 Syria 420 Lebanon 421 Hezbollah 430 Jordan 440 Egypt 450 Iran 451 Iranian Athlete 452 Iranian Musician 460 Iraq 470 Saudi-Arabia 480 Arab League 490 Gulf Cooperation Council 500 European Union 510 Poland 520 UK 521 British writer 522 British politician 523 British artist 530 France 540 Netherland 550 Greece 560 Luxembourg 570 Switzerland 580 Austria 590 Denmark 600 Other Countries 610 USA 611 US Business 620 India 630 Morocco 640 Argentina 650 Australia 178

660 Brazil 670 Turkey 680 Russia 690 Norway 700 International Actors 710 UNO 720 International NGO 730 International Atomic Energy Agency 740 BDS Movement 750 International Crime Court 800 Other 999 Not applicable v31 Actor 2 = Same coding system as v30. v32 Actor 3 = Same coding system as v30. v33 Actor 4 = Same coding system as v30. v34 Actor 5 = Same coding system as v30. v35 Valency of actor 1 = How is actor 1 evaluated?

The valency of the main actor should capture how actor is portrayed. This includes the question of responsibility as well as personal opinions by the author or other (quoted) actors. If an actor is portrayed as responsible for negative development, this should be coded as either negative or very negative and vice versa for positive developments. The coding will be done along a 5-point Likert-scale. If and actor is evaluated both positively and negatively, the variable should be coded as no tendency, unless either a positive or negative evaluation outweighs the other. Coding should be done conservatively. If the coder is unsure between two manifestations, the less extreme – the one closer to “neutral/no tendency” – should be coded.

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+2 Very positive +1 Positive 0 Neutral/no tendency -1 Negative -2 Very negative v36 Valency of actor 2 = Same coding system as v35. v37 Valency of actor 3 = Same coding system as v35. v38 Valency of actor 4 = Same coding system as v35. v39 Valency of actor 5 = Same coding system as v35. v40 Responsibility = Who is depicted as responsible for the valency of the development (v29).

The party which is portrayed as responsible for the development should be coded here. While the main actor may often be portrayed as the one responsible, this is not necessarily the case. For this variable, the same coding system as for the actors should be used. If more than one party from one type of actor are portrayed as responsible, e.g. both the Israeli military and the Israeli police, the next broader category should be applied, in this case Military/security forces. If the responsibility is shared by groups from different countries, the coding should depend on the extend of the sharing of responsibility. If one party is depicted as more responsible, the variable should be coded accordingly. If both parties are portrayed as responsible to about the same extend, this should be coded as shared responsibility. For example, if the Israeli Army bombards targets in Gaza, this should be coded as Israeli responsibility. If the article is on rocket attacks from Gaza, Palestinians should be coded as responsible. If the articles states that Israel responded to Palestinian rocket attacks by force, this should 180

be coded as Palestinian responsibility. However, if the articles states that Israel and Gaza are in a spiral of violence, this should be coded as shared responsibility. Not all developments are depicted having a responsibility, in particular for non-conflict topics the category may not apply.

1 Israeli responsibility 2 Palestinian responsibility 3 German responsibility 4 Syrian responsibility 5 Shared responsibility between multiple parties 6 EU responsibility 7 Iranian responsibility 8 Lebanese (non-Hezbollah) responsibility 9 Hezbollah responsibility 10 UNO responsibility 11 USA responsibility 12 Australian responsibility 13 Austrian responsibility 14 Brazilian responsibility 15 UK responsibility 16 Danish responsibility 17 International Crime Court responsibility 18 Luxembourg responsibility 19 Iraqi responsibility 999 Not applicable

Quotes = Who is quoted how often in the articles.

This is a formal category, as such the content of the quotes does not matter. The goals is to capture who is able to give input on the events in the reporting. In order to keep these variables practical but concise, only the nationality of the actors quoted will be coded. A quote is the repetition of a passage of speech or text. This may be directly by direct quotes, often marked by colons 181

and quotation marks, or indirectly by form of indirect speech. Indirect speech is often marked by content clauses such as “that” and the use of infinitive grammatical forms. The coding will be done according to number of statements. One statement will be defined as one coherent complex of meaning. This means that one statement can consist of multiple sentences and both direct and indirect quotes. Coded is the amount of quotes per type of actor. Quotes by multiple actors of the same type summarized. This variable should be coded with MAXQDA. v41 Israeli quotes = Quoted statements by Israeli actors: 0-n v42 Palestinian quotes = Quoted statements by Palestinian actors: 0-n v43 German quotes = Quoted statements by German actors: 0-n v44 Other quotes = Quoted statements by other actors: 0-n v45 Quoted actor 1 = Who is quoted in the article.

This variable captures who is quoted in the article. Up to five different actors may be captured. Coding is done according to most quotes in the article, so the actor quoted most will be coded as quoted actor 1 and so forth. If more than five actors are quoted, only the actors which are quoted the most are coded. Quotes include direct and indirect speech. This variable should be coded with MAXQDA.

100 Israel (state, region, generic references) 110 Israeli civilian 120 Politician 130 Military/security forces 140 Other state institution 150 NGO 182

160 Media/press 170 Business/Company 180 Government 200 Germany (state, region, generic references) 210 German Civilian 220 Politician 230 Military/security forces 240 Other state institution 250 NGO 260 Media/press 270 Business/Company 280 Government 300 Palestine/Palestinian (generic reference) 310 Palestinian civilian 320 Palestinian politician/official 330 Palestinian Military/Armed group 340 NGO 400 Other Arab, non-Palestinian actor 410 Syria 420 Lebanon 430 Jordan 440 Egypt 450 Iran 460 Iraq 470 Saudi-Arabia 480 Arab League 490 Gulf Cooperation Council 500 European Union 510 Poland 520 UK 530 France 540 Netherland 550 Greece 560 Luxembourg 570 Switzerland 580 Austria 590 Denmark 183

600 Other Countries 610 USA 620 India 630 Morocco 640 Argentina 650 Australia 660 Brazil 670 Turkey 680 Russia 690 Norway 700 International Actors 710 UNO 720 International NGO 730 International Atomic Energy Agency 740 BDS Movement 750 International Crime Court 800 Other 999 Not applicable v46 Quoted actor 2 = Same coding system as v45. v47 Quoted actor 3 = Same coding system as v45. v48 Quoted actor 4 = Same coding system as v45. v49 Quoted actor 5 = Same coding system as v45. v50 Valency quotes actor1 = Evaluation of Israel in the statements by quoted actor1. This variable takes the same unit, the statements defined as complex’ of meanings, according to their evaluation of Israel. This is independent from the author of the statement. The valency is measured as a ternary Likert-scale, either as positive, negative or neutral. Statements with no valency are coded as the latter. This variable should be coded with MAXQDA.

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+1 Quoted statements positive 0 Quoted statements neutral -1 Quoted statements negative v51 Valency quotes actor2 = Same coding system as v50. v52 Valency quotes actor3 = Same coding system as v50. v53 Valency quotes actor4 = Same coding system as v50. v54 Valency quotes actor5 = Same coding system as v50. v55 Content coherency 1 = Thematic coherency of headline, teaser and main text.

This variable aims to capture whether all important information from the main text are represented in the headline and teaser text. Headline and/or teaser text may also focus on one aspect of the news event, thus shifting the attention of that aspect. The headline and teaser text will be regarded as one part of the text in contrast to the main text, as two are viewed from the main pages, as well as when articles are linked on social media. For example, if a text on the conflict between Israel and Hamas is titled “Rocket attacks on Israel” but in the main text there is also an addition that Israel has responded to rockets with their own attacks, this would be coded as dissonant. If the headline would be along the lines of “Hamas and Israel exchange rocket fire” or the information would be portrayed in the teaser text, it would be coded as coherent.

1 Coherent 0 Dissonant

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v56 Content coherency 2 = The tendency of dissonance between headline, teaser text and main text.

This variable should only be coded if the previous variable is coded as dissonant. The goal is to capture whether the dissonance between the headline/teaser text and the main news text is to the advantage or disadvantage of Israel. Taking the previous example, the headline “Rocket attacks on Israel” would be to the advantage of Israel, as it portrays Israel as the victim of violent attacks while concealing Israeli counterattacks. However, if the headline would be “Israeli targets Hamas in Gaza”, this would be to the disadvantage of Israel, as it paints Israel as the aggressor and does not mention the previous rocket attacks. The variable should be coded with the first impression in mind. If the dissonance is neither to the advantage nor disadvantage of Israel, it should be coded as such. The coding should be done conservatively; if it’s not clear whether it is to the advantage/disadvantage of Israel, it should be coded as neutral.

+1 To the advantage of Israel 0 Neither/neutral/not applicable -1 To the disadvantage of Israel v57 Headline evaluation = The depiction of Israel in the headline alone when compared to the whole of the article.

The following variables dissect headline, teaser text and main text regarding whether the non-coherent depiction (v22) of Israel amounts to an advantageous or disadvantageous depiction. For the headline, this should be done with the information in the teaser text and in the text body of the article in mind. The question is whether all main information and context is included in the headline, and whether leaving out some information or focusing on certain aspects over others provides a more positive or more 186

negative impression of Israel when comparing to the information provided by all three elements of the article together. Some articles include subheadlines, which may be written under or above the main headline. These should be counted as part of the headline. The coding is done in a three-step Likert-scale, ranging from +1 for advantageous for Israel to 0 for a neutral or ambivalent depiction to -1 for disadvantageous for Israel.

+1 To the advantage of Israel 0 Neither/neutral -1 To the disadvantage of Israel v58 Teaser evaluation = The depiction of Israel in the teaser text alone when compared to the whole of the article.

Same as 24.1. Not all articles may include a teaser text, in whichcase 99 for not applicable should be coded. A teaser text can be identified by its position at the top of the text. Often, teaser text is emphasized by bold or italic text. It usually gives most of the important information in the article.

+1 To the advantage of Israel 0 Neither/neutral -1 To the disadvantage of Israel 99 Not applicable v59 Text evaluation = The depiction of Israel in the text body alone when compared to the whole of the article.

Same as 24.1 and 24.2.

+1 To the advantage of Israel 0 Neither/neutral -1 To the disadvantage of Israel 187

v60 Overall valency = Overall evaluation of Israel in the article.

This variable should capture how Israel and Israeli actors are generally depicted in the article. All previous variables and all of the text should influence this variable. The valency is to be captured in a five-point Likert-skala, ranging from -2 (very negative) to +2 (very positive). The valency should be considered regarding responsibility for negative and positive developments and explicit and implicit evaluations of Israel and Israeli actors. The first impression of the article should be considered as well as the way context information is provided. For example, if an article describes Israel as responsible for an escalation with Palestinians, it should be considered negative valency; if an article focuses on how measured a military response by Israel is, it should be considered positive valency. The coding is done in a five-step Likert-scale, ranging from +2 very positive to -2 for very negative valency. The coding should be done conservatively, meaning if the coder is unsure between two positions, the less strong (meaning more towards the neutral position) should be coded.

+2 very positive +1 rather positive 0 Neutral/ambivalent -1 rather negative -2 very negative

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Appendix D: Structure of Material

Types of Text per Publication

Publication Type Bild n-tv Spiegel t-online Zeit Total Newsflash n 11 37 9 6 1 64 % 12% 31.1% 7.6% 4.6% 1% 11.4% News Report n 67 78 88 121 70 424 % 72.8% 65.5% 73.9% 92.4% 69.3% 75.4% Feature n 1 0 5 0 6 12 % 1.1% 0% 4.2% 0% 5.9% 2.1% Opinion n 5 1 2 2 4 14 % 5.4% 0.8% 1.7% 1.5% 4% 2.5% Interview n 3 2 5 1 3 14 % 3.3% 1.7% 4.2% 0.8% 3% 2.5% Review n 1 0 2 0 3 6 % 1.1% 0% 1.7% 0.0% 3% 1.1% Portrait n 1 0 2 0 2 5 % 1.1% 0% 1.7% 0% 2% 0.9% Analysis n 0 0 0 1 6 7 % 0% 0% 0% 0.8% 5.9% 1.2% Column n 1 0 5 0 1 7 % 1.1% 0% 4.2% 0% 1% 1.2% Report n 0 1 0 0 3 4 % 0% 0.8% 0% 0% 3% 0.7% Other n 2 0 1 0 2 5 % 2.2% 0% 0.8% 0% 2% 0.9% Total n 92 119 119 131 101 562 % 100% 100% 100% 100% 100% 100%

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Frequencies of Topics per Publication

Publication Topic Bild n-tv Spiegel t-online Zeit Total Israeli Internal Politics n 16 47 53 46 35 197 Israeli Internal Security n 0 0 0 0 1 1 Israeli Government n 0 1 1 0 0 2 Israeli Economy n 2 5 0 0 5 12 Israeli Sports n 0 2 1 3 0 6 Israeli Sciences n 3 0 1 0 0 4 Israeli Culture n 0 0 2 1 5 8 Israel Religion n 1 1 1 0 1 4 Isareli External n 0 6 1 3 0 10 Trade/Economy Israeli External Sports n 9 4 3 5 0 21 Isareli Diplomacy n 0 3 5 3 3 14 Other Israeli Affairs n 0 0 0 0 2 2 German Affairs n 6 2 1 13 0 22 German Government n 5 5 2 0 1 13 German Internal n 28 5 12 11 5 61 Politics German NGO Action n 0 0 3 0 0 3 Holocaust n 4 1 1 2 3 11 Antisemitism in n 18 4 7 14 13 56 Germany German n 3 1 2 1 1 8 Economy/Trade German Protest n 4 0 0 0 0 4 German Culture n 0 0 1 2 0 3 Other German Issues n 3 0 1 0 0 4 Arabi-Israeli Conflict n 3 1 4 5 4 17 Israeli Military Action n 8 16 14 15 13 66 Palestinian Military n 16 11 13 12 13 65 Action Conflict with Other n 5 12 8 6 5 36 Actor in the Region

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Frequencies of Topics per Publication (continued).

Publication Topic Bild n-tv Spiegel t-online Zeit Total Negotiation / Diplomacy n 0 0 1 1 0 2 BDS Movement n 1 0 9 7 5 22 Settlements n 4 25 18 11 9 67 Palestinian Internal n 1 2 0 0 0 3 Affairs Iranian Affairs n 6 7 5 10 10 38 Internal Affairs of Other n 1 2 1 3 1 8 Actor in the Region EU Politics n 7 7 3 3 3 23 UK Politics n 0 0 0 0 1 1 Russia n 0 3 0 1 0 4 Denmark n 0 0 1 0 0 1 United Nations n 6 0 4 1 2 13 USA politics n 0 6 8 8 8 30 Indian Politics n 0 0 1 0 0 1 International NGO n 0 0 3 0 0 3 action Attack on Halle n 0 0 3 1 1 5 Synagogue Olympia Berlin 2036 n 1 0 0 0 0 1 Jewish Museum Berlin n 0 0 0 2 0 2 History n 2 2 7 3 3 17 Oddity n 0 1 0 2 3 6 Crime n 0 5 0 0 0 5 Biography/Portrait n 1 0 1 0 0 2 Media n 0 0 1 0 0 1 Obituary n 0 0 1 0 0 1 Personal Experience n 0 0 5 0 1 6 Travel n 1 0 1 0 0 2 Science n 0 0 1 1 0 2 Total n 92 119 119 131 101 562

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Frequencies of Actors per Publication

Publication Actor Bild n-tv Spiegel t-online Zeit Total Israel (Generic n 32 26 32 26 34 150 Reference) Israeli Civilian n 7 11 11 4 9 42 Israeli Settler n 2 10 5 3 3 23 Israeli Protestor n 0 1 0 0 1 2 Israeli Religous n 1 0 4 0 2 7 Person/Group Israeli Scientist n 2 4 4 3 3 16 Israeli Musician n 1 0 1 3 0 5 Israeli Athlete n 11 4 2 9 1 27 Israeli Business Person n 1 1 2 0 1 5 Israeli Actor n 0 0 1 0 1 2 Israeli Writer n 0 1 1 0 2 4 Israeli Politician n 1 2 5 5 3 16 Israeli Prime Minister n 16 52 56 55 47 226 Israeli Opposition n 16 42 42 57 42 199 Israeli President n 3 5 12 21 11 52 Israeli Soldier n 0 1 0 0 1 2 Israeli Police n 2 0 1 0 0 3 Israeli Secret Service n 2 1 5 1 4 13 IDF/IAF n 13 22 17 27 16 95 Other Israeli State n 0 3 0 1 0 4 Institution Israeli medical n 0 0 2 0 0 2 personnel Israeli Court/Judge n 2 1 9 1 2 15 Israeli Local n 0 3 2 1 0 6 Government Israeli NGO n 7 2 6 6 1 22 Israeli Media n 2 0 2 0 0 4 Israeli n 2 17 2 6 4 31 business/Company 192

Frequencies of Actors per Publication (continued).

Publication Actor Bild n-tv Spiegel t-online Zeit Total Israeli Government n 2 2 1 2 3 10 Israeli Ministry of n 7 3 1 7 5 23 Foreign Affairs Israeli Ministry of n 1 0 3 0 1 5 Defense Israeli Ministry of n 0 4 3 10 6 23 Justice Israeli Ministry of n 2 0 0 0 0 2 Public Security Other Israeli Ministry n 0 1 3 0 0 4 Germany (Generic n 4 1 2 2 7 16 Reference) German Civilian n 4 5 3 8 10 30 German Protestor n 6 0 0 3 3 12 German Religous n 2 2 3 2 4 13 Person/Group German Scientist n 0 0 1 1 0 2 German Musician n 2 0 0 1 1 4 German Athlete n 1 4 1 1 0 7 German Politician n 9 3 7 5 0 24 Chancellor n 0 3 0 1 1 5 Member of Bundestag n 6 0 3 0 0 9 German President n 2 1 0 0 0 3 Local German n 15 1 3 15 1 35 Politician German n 1 0 1 2 0 4 Military/Security Forces German Police n 6 1 1 2 1 11 German Secret Service n 1 0 0 0 1 2 German Court/Judge n 2 1 1 1 0 5

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Frequencies of Actors per Publication (continued).

Publication Actor Bild n-tv Spiegel t-online Zeit Total Local German n 6 1 5 11 2 25 Government German NGO n 15 2 7 5 1 30 German Media n 3 0 5 0 0 8 German n 6 3 2 1 4 16 Business/Company German Government n 10 5 8 1 2 26 German Federal n 8 1 5 5 2 21 Foreign Office Palestine (Generic n 2 5 9 3 1 20 Reference) Palestinian Civilian n 1 2 4 2 2 11 Palestinian Protestor n 0 1 0 4 1 6 Palestinian Musician n 6 0 1 1 0 8 Palestinian President n 3 2 0 4 1 10 Palestinian Minister n 1 4 5 2 3 15 Hamas Official n 0 2 0 3 3 8 PFLP Official n 3 1 0 1 0 5 Palestinian n 9 3 7 2 4 25 military/Armed Group Hamas n 12 5 6 8 10 41 Islamic Jihad n 9 7 9 12 11 48 Palestinian NGO n 2 0 0 3 0 5 Other Arab Actor n 4 1 2 2 2 11 Syria n 1 6 9 9 6 31 Lebanon n 0 3 1 5 2 11 Hezbollah n 6 9 4 4 6 29 Jordan n 0 2 1 1 2 6 Egypt n 0 2 0 1 0 3 Iran n 10 10 16 14 17 67 UK n 1 1 2 0 3 7 British Writer n 0 0 3 2 1 6 194

Frequencies of Actors per Publication (continued).

Publication Actor Bild n-tv Spiegel t-online Zeit Total USA n 8 12 17 16 17 70 US Company/Business n 0 8 0 5 2 15 Turkey n 0 1 2 2 2 7 Russia n 0 5 0 3 0 8 Other Countries n 4 5 6 2 1 18 European Union n 8 13 9 6 7 43 United Nations n 8 2 9 6 5 30 International NGO n 2 1 9 5 5 22 BDS Movement n 4 1 10 8 6 29 Total n 348 367 434 451 363 1963

Note. Up to five Actors were coded per article.

Frequency of Quoted Actors per Publication

Publication Quoted Actor Bild n-tv Spiegel t-online Zeit Total Israeli Civilian n 10 15 12 21 14 72 Israeli Politician n 14 42 43 69 44 212 Israeli n 11 22 15 16 19 83 Military/Security Other Israeli State n 1 2 4 0 0 7 Institution Israeli NGO n 4 2 3 6 1 16 Israeli Media/Press n 1 3 5 3 0 12 Israeli n 0 2 0 3 0 5 Business/Company Israeli Government n 13 11 8 11 9 52 German Civilian n 15 5 6 9 14 49 German Politician n 26 8 11 18 5 68

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Frequency of Quoted Actors per Publication (continued).

Publication Quoted Actor Bild n-tv Spiegel t-online Zeit Total German n 5 0 0 1 2 8 Military/Security Forces Other German State n 4 1 2 10 1 18 Institution German NGO n 12 5 5 6 3 31 German Media/Press n 6 0 1 0 0 7 German n 4 0 3 1 2 10 Business/Company German Government n 12 3 6 5 3 29 Palestine n 1 1 0 1 0 3 Palestinian Civilian n 5 3 2 1 2 13 Palestinian Politician n 6 13 11 17 10 57 Palestinian n 3 2 1 4 3 13 Military/Armed Group Other Arab Actor n 1 1 2 1 2 7 Syria n 0 4 2 3 3 12 Lebanon n 3 6 2 5 3 19 Jordan n 0 2 2 2 1 7 Iran n 2 0 2 5 8 17 UK n 0 0 2 1 1 4 USA n 4 11 10 18 9 52 Turkey n 0 1 0 1 2 4 Other Country n 3 5 2 2 1 13 European Union n 0 6 5 3 2 16 United Nations n 2 1 5 6 3 17 International NGO n 2 1 7 4 6 20 Total n 170 178 179 253 173 953 Note. Up to five quoted actors were coded per article.

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Appendix E: Hypothesis Testing

Hypothesis H1

Frequencies Valency of Event

Statistics Valency of Event

N Valid 562 Missing 0

Frequency Valency of Event

Cumulative Developement Frequency Percent Valid Percent Percent Valid Negative 293 52.1% 52.1% 52.1% Ambivalent / Stagnation 200 35.6% 35.6% 87.7% Positive 69 12.3% 12.3% 100.0% Total 562 100.0% 100.0%

Crosstable Frequency and Distribution of Valency of Development per Publication with Z-test

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent Valency of Event 562 100.0% 0 0.0% 562 100.0% * Publication

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Crosstabulation Valency of Event and Publication

Publication Developement Bild n-tv Spiegel t-online Zeit Total

Valency of Event Positive Count 14a 14a 15a 14a 12a 69 % within 15.2% 11.8% 12.6% 10.7% 11.9% 12.3% Publication

Ambivalent Count 26a 44a 41a 52a 37a 200 /Stagnation % within 28.3% 37.0% 34.5% 39.7% 36.6% 35.6% Publication

198 Negative Count 52a 61a 63a 65a 52a 293

% within 56.5% 51.3% 52.9% 49.6% 51.5% 52.1% Publication Total Count 92 119 119 131 101 562 % within 100.0% 100.0% 100.0% 100.0% 100.0% 100.0 Publication % Note. Each subscript letter denotes a subset of Publication categories whose column proportions do not differ significantly from each other at the .05 level.

ANOVA for Mean Valency of Development per Publication (Not Weighted)

Case Processing Summary

Cases Included Excluded Total N Percent N Percent N Percent Valency of Event 562 100.0% 0 0.0% 562 100.0% * Publication

Report Valency of Event

Publication Mean N Std. Deviation Bild -.41 92 .744 n-tv -.39 119 .692 Spiegel -.40 119 .705 t-online -.39 131 .675 Zeit -.40 101 .694 Total -.40 562 .697

ANOVA Table

Valency of Event * Publication Between Groups Within (Combined) Groups Total Sum of Squares .035 272.683 272.719 df 4 557 561 Mean Square .009 .490 F .018 Sig. .999

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Measures of Association Eta Eta Squared Valency of Event .011 .000 * Publication

ANOVA for Mean Valency of Development per Publication (Weighted)

Case Processing Summary Cases Included Excluded Total N Percent N Percent N Percent Valency of Event 917 100.0% 0 0.0% 917 100.0% * Publication

Report Valency of Event

Std. Publication Mean N Deviation Bild -.42 132 .731 n-tv -.42 203 .665 Spiegel -.45 204 .675 t-online -.42 212 .652 Zeit -.45 166 .665 Total -.43 917 .673

200

ANOVA Table

Valency of Event * Publication Between Groups Within (Combined) Groups Total Sum of Squares .165 414.548 414.713 df 4 912 916 Mean Square .041 .455 F .091 Sig. .985

Measures of Association

Eta Eta Squared Valency of Event .020 .000 * Publication

Frequency of Evaluation of Development per Simplified Main Topic

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent Main topic, Simplified * 562 100.0% 0 0.0% 562 100.0% Valency of Event

201

Crosstabulation Main Topic, Simplified * Valency of Event

Development Ambivalent Main Topic, Simplified Negative /Stagnation Positive Total Israeli Internal Affairs 56 110 22 188 Israeli external Affairs 15 12 9 36 German-Israeli Affairs 52 36 22 110 Arab-Israeli Conflict 161 31 7 199 Other Topics 9 11 9 29 Total 293 200 69 562

ANOVA for Mean Evaluation of Development per Simplified Main Topic (Not Weighted)

Case Processing Summary

Cases Included Excluded Total N Percent N Percent N Percent Valency of Event * Main Topic, 562 100.0% 0 0.0% 562 100.0% Simplified

202

Report Valency of Event

Main Topic, Simplified Mean N Std. Deviation Israeli Internal Affairs -.18 188 .620 Israeli External Affairs -.17 36 .811 German-Israeli Affairs -.27 110 .777 Arab-Israeli Conflict -.77 199 .497 Other Topics .00 29 .802 Total -.40 562 .697

ANOVA Table

Valency of Event * Main topic, Simplified Between Groups Within (Combined) Groups Total Sum of Squares 45.225 227.493 272.719 df 4 557 561 Mean Square 11.306 .408 F 27.683 Sig. .000

Measures of Association

Eta Eta Squared Valency of Event * Main Topic. .407 .166 Simplified

203

ANOVA for Mean Evaluation of Development per Simplified Main Topic (Weighted)

Case Processing Summary

Cases Included Excluded Total N Percent N Percent N Percent Valency of Event * Main Topic, 917 100.0% 0 0.0% 917 100.0% Simplified

Report Valency of Event

Std. Main Topic, Simplified Mean N Deviation Israeli Internal Affairs -.20 357 .609 Israeli External Affairs -.28 53 .794 German-Israeli Affairs -.24 119 .792 Arab-Israeli Conflict -.79 350 .470 Other Topics .03 38 .753 Total -.43 917 .673

204

ANOVA Table

Valency of Event * Main Topic, Simplified Between Groups Within (Combined) Groups Total Sum of Squares 77.791 336.923 414.713 df 4 912 916 Mean Square 19.448 .369 F 52.642 Sig. .000

Measures of Association Eta Eta Squared Valency of Event * Main Topic, .433 .188 Simplified

Hypothesis H1.1

Frequencies News Factor Conflict (Not Weighted)

Statistics News Factor Conflict

N Valid 562 Missing 0

205

New Factor Conflict

Cumulative Frequency Percent Valid Percent Percent Valid No 449 79.9% 79.9% 79.9% Yes 113 20.1% 20.1% 100.0% Total 562 100.0% 100.0%

Frequencies News Factor Conflict (Weighted)

Statistics News Factor Conflict

N Valid 917 Missing 0

News Factor Conflict

Cumulative Frequency Percent Valid Percent Percent Valid No 707 77.1% 77.1% 77.1% Yes 210 22.9% 22.9% 100.0% Total 917 100.0% 100.0%

Occurrence of the News Factor Conflict, per Publication (Not Weighted)

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent NF: Conflict * 562 100.0% 0 0.0% 562 100.0% Publication 206

Crosstabulation News Factor Conflict * Publication

Publication Bild n-tv Spiegel t-online Zeit Total

NF: No Count 75a 95a 93a 104a 82a 449 Conflict % within 81.5% 79.8% 78.2% 79.4% 81.2% 79.9% Publication

Yes Count 17a 24a 26a 27a 19a 113 % within 18.5% 20.2% 21.8% 20.6% 18.8% 20.1% Publication Total Count 92 119 119 131 101 562 % within 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% Publication Note. Each subscript letter denotes a subset of Publication categories whose column proportions do not differ significantly from each other at the .05 level.

Occurrence of News Factor Conflict, per Publication (Weighted)

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent NF: Conflict * 917 100.0% 0 0.0% 917 100.0% Publication

207

Crosstabulation News Factor Conflict * Publication

Publication Bild n-tv Spiegel t-online Zeit Total

NF: No Count 102a 156a 158a 162a 129a 707 Conflict % within 77.3% 76.8% 77.5% 76.4% 77.7% 77.1% Publication

Yes Count 30a 47a 46a 50a 37a 210 % within 22.7% 23.2% 22.5% 23.6% 22.3% 22.9% Publication Total Count 132 203 204 212 166 917 % within 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% Publication Note. Each subscript letter denotes a subset of Publication categories whose column proportions do not differ significantly from each other at the .05 level.

Hypothesis H1.2

Frequency Responsibility (Not Weighted)

Statistics Responsibility for the Event

N Valid 520 Missing 42

208

Responsibility for the Event

Cumulative Responsibility Frequency Percent Valid Percent Percent Valid Israeli 257 45.7% 49.4% 49.4% Palestinian 42 7.5% 8.1% 57.5% German 96 17.1% 18.5% 76.0% Syrian 9 1.6% 1.7% 77.7% Shared 42 7.5% 8.1% 85.8% EU 16 2.8% 3.1% 88.8% Iranian 14 2.5% 2.7% 91.5% Lebanese 9 1.6% 1.7% 93.3% USA 23 4.1% 4.4% 97.7% Other 12 2.1% 2.3% 100.0% Total 520 92.5% 100.0% Missing 999 42 7.5% Total 562 100.0%

Frequency Responsibility (Weighted)

Statistics Responsibility for the Event

N Valid 859 Missing 58

209

Responsibility for the event

Cumulative Responsibility Frequency Percent Valid Percent Percent Valid Israeli 485 52.9% 56.5% 56.5% Palestinian 81 8.8% 9.4% 65.9% German 103 11.2% 12.0% 77.9% Syrian 17 1.9% 2.0% 79.9% Shared 69 7.5% 8.0% 87.9% EU 29 3.2% 3.4% 91.3% Iranian 17 1.9% 2.0% 93.2% Lebanese 12 1.3% 1.4% 94.6% USA 32 3.5% 3.7% 98.4% Other 14 1.5% 1.6% 100.0% Total 859 93.7% 100.0% Missing 999 58 6.3% Total 917 100.0%

Crosstable Responsibility and Valency of Development (Not Weighted)

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent Valency of Event * Responsibility 520 92.5% 42 7.5% 562 100.0% for the Event

210

Crosstabulation Valency of Event * Responsibility for the Event Crosstabulation

Development negative Ambivalent/Stagnation Positive Total % within % within % within % within Responsibility Valency of Valency of Valency of Valency of for the Event Count event Count event Count event Count event Israeli 116 40.0% 106 64.6% 35 53.0% 257 49.4% Palestinian 38 13.1% 2 1.2% 2 3.0% 42 8.1% German 54 18.6% 28 17.1% 14 21.2% 96 18.5% Syrian 8 2.8% 1 0.6% 0 0.0% 9 1.7% 211 Shared 24 8.3% 7 4.3% 11 16.7% 42 8.1% EU 7 2.4% 9 5.5% 0 0.0% 16 3.1% Iranian 14 4.8% 0 0.0% 0 0.0% 14 2.7% Lebanese 3 1.0% 2 1.2% 4 6.1% 9 1.7% USA 21 7.2% 2 1.2% 0 0.0% 23 4.4% Other 5 1.7% 7 4.3% 0 0.0% 12 2.3% Total 290 100.0% 164 100.0% 66 100.0% 520 100.0%

Chi-Square Tests

Asymptotic Significance Value df (2-sided) Pearson Chi- 88.771a 18 .000 Square Likelihood Ratio 102.165 18 .000 Linear-by-Linear 4.926 1 .026 Association N of Valid Cases 520 Note. a. 10 cells (33.3%) have expected count less than 5. The minimum expected count is 1.14.

Symmetric Measures

Approximate Value Significance Nominal by Phi .413 .000 Nominal Cramer's V .292 .000 N of Valid Cases 520

Crosstable Valency of Events (Binary) and Responsibility (Binary)

Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Valency of Events, Binary * 520 92.5% 42 7.5% 562 100.0% Responsibility, Binary

212

Crosstabulation Valency of Events, Binary * Responsibility, Binary Responsibility Development Israeli Other Total Valency of Positive/ Count 141 89 230 Events, Binary Ambivalent % within Valency of 61.3% 38.7% 100.0% Events, Binary Negative Count 116 174 290 % within Valency of 40.0% 60.0% 100.0% Events, Binary Total Count 257 263 520 % within Valency of 49.4% 50.6% 100.0% Events, Binary

Chi-Square Tests

Asymptotic Significance Exact Sig. (2- Exact Sig. (1- Value df (2-sided) sided) sided) Pearson Chi- 23.290a 1 .000 Square Continuity 22.446 1 .000 Correctionb Likelihood Ratio 23.468 1 .000 Fisher's Exact .000 .000 Test Linear-by-Linear 23.246 1 .000 Association N of Valid Cases 520 Note. a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 113.67. b. Computed only for a 2x2 table

213

Symmetric Measures

Approximate Value Significance Nominal by Phi .212 .000 Nominal Cramer's V .212 .000 N of Valid Cases 520

Crosstable Valency of Events (Binary) and Responsibility (Binary) per Publication (Not Weighted)

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent Valency of Events, Binary * Responsibility 520 92.5% 42 7.5% 562 100.0% Binary * Publication

214

Crosstabulation Valency of Events, Binary * Responsibility, Binary * Publication

Responsibility Publication Developement Israeli Other Total Bild Valency Positive/ Count 13 15 28 of Ambivalent % within Valency 46.4% 53.6% 100.0% Events, of Events, Binary Binary Negative Count 3 47 50 % within Valency 6.0% 94.0% 100.0% of Events, Binary Total Count 16 62 78 % within Valency 20.5% 79.5% 100.0% of Events, Binary n-tv Valency Positive/ Count 34 19 53 of Ambivalent % within Valency 64.2% 35.8% 100.0% Events, of Events, Binary Binary Negative Count 29 32 61 % within Valency 47.5% 52.5% 100.0% of Events, Binary Total Count 63 51 114 % within Valency 55.3% 44.7% 100.0% of events, binary Spiegel Valency Positive/ Count 33 16 49 of Ambivalent % within Valency 67.3% 32.7% 100.0% Events, of Events, Binary Binary Negative Count 30 32 62 % within Valency 48.4% 51.6% 100.0% of Events, Binary Total Count 63 48 111 % within Valency 56.8% 43.2% 100.0% of Events, Binary t-online Valency Positive/ Count 33 26 59 of Ambivalent % within Valency 55.9% 44.1% 100.0% Events, of Events, Binary Binary Negative Count 32 33 65 % within Valency 49.2% 50.8% 100.0% of Events, Binary

215

Crosstabulation Valency of Events, Binary * Responsibility, Binary * Publication (continued).

Responsibility Publication Development Israeli Other Total t-online Total Count 65 59 124 % within Valency 52.4% 47.6% 100.0% of Events, Binary Zeit Valency Positive/ Count 28 13 41 of Ambivalent % within Valency 68.3% 31.7% 100.0% Events, of Events, Binary Binary Negative Count 22 30 52 % within Valency 42.3% 57.7% 100.0% of Events, Binary Total Count 50 43 93 % within Valency 53.8% 46.2% 100.0% of Events, Binary Total Valency positive/ Count 141 89 230 of Ambivalent % within Valency 61.3% 38.7% 100.0% Events, of Events, Binary Binary Negative Count 116 174 290 % within Valency 40.0% 60.0% 100.0% of Events, Binary Total Count 257 263 520 % within Valency 49.4% 50.6% 100.0% of Events, Binary

216

Chi-Square Tests Asymptotic Sig. Exact Sig. (2- Exact Sig. Publication Value df (2-sided) sided) (1-sided) Bild Pearson Chi-Square 17.992c 1 .000 Continuity Correctionb 15.598 1 .000 Likelihood Ratio 17.789 1 .000 Fisher's Exact Test .000 .000 Linear-by-Linear Association 17.762 1 .000 N of Valid Cases 78 n-tv Pearson Chi-Square 3.165d 1 .075 Continuity Correctionb 2.529 1 .112 217 Likelihood Ratio 3.186 1 .074 Fisher's Exact Test .091 .056 Linear-by-Linear Association 3.137 1 .077 N of Valid Cases 114 Spiegel Pearson Chi-Square 4.009e 1 .045 Continuity Correctionb 3.273 1 .070 Likelihood Ratio 4.054 1 .044 Fisher's Exact Test .055 .035 Linear-by-Linear Association 3.973 1 .046 N of Valid Cases 111 t-online Pearson Chi-Square .557f 1 .456 Continuity Correctionb .321 1 .571 Likelihood Ratio .557 1 .455 Fisher's Exact Test .477 .286

Chi-Square Tests (continued).

Asymptotic Sig. Exact Sig. (2- Exact Sig. (1- Publication Value df (2-sided) sided) sided) t-online Linear-by-Linear Association .552 1 .457 N of Valid Cases 124 Zeit Pearson Chi-Square 6.227g 1 .013 Continuity Correctionb 5.226 1 .022 Likelihood Ratio 6.326 1 .012 Fisher's Exact Test .021 .011 Linear-by-Linear Association 6.160 1 .013

218 N of Valid Cases 93 a Total Pearson Chi-Square 23.290 1 .000 Continuity Correctionb 22.446 1 .000 Likelihood Ratio 23.468 1 .000 Fisher's Exact Test .000 .000 Linear-by-Linear Association 23.246 1 .000 N of Valid Cases 520 Note. a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 113.67. b. Computed only for a 2x2 table c. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 5.74. d. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 23.71. e. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 21.19. f. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 28.07. g. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 18.96.

Crosstable Valency of Events (Binary) and Responsibility (Binary) per Publication (Weighted)

Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Valency of Events, Binary * Responsibility 859 93.7% 58 6.3% 917 100.0% Binary * Publication

Crosstabulation Valency of Events, Binary * Responsibility, Binary * Publication

Responsibility Publication Developement Israeli Other Total Bild Valency Positive/ Count 23 20 43 of Ambivalent % within Valency 53.5% 46.5% 100.0% Events, of Events, Binary Binary Negative Count 6 64 70 % within Valency 8.6% 91.4% 100.0% of Events, Binary Total Count 29 84 113 % within Valency 25.7% 74.3% 100.0% of Events, Binary n-tv Valency Positive/ Count 64 26 90 of Ambivalent % within Valency 71.1% 28.9% 100.0% Events, of Events, Binary Binary Negative Count 55 50 105 % within Valency 52.4% 47.6% 100.0% of Events, Binary Total Count 119 76 195 % within Valency 61.0% 39.0% 100.0% of events, binary

219

Crosstabulation Valency of Events, Binary*Responsibility, Binary*Publication (continued).

Responsibility Publication Development Israeli Other Total Spiegel Valency Positive/ Count 63 20 83 of Ambivalent % within Valency 75.9% 24.1% 100.0% Events, of Events, Binary Binary Negative Count 59 52 111 % within Valency 53.2% 46.8% 100.0% of Events, Binary Total Count 122 72 194 % within Valency 62.9% 37.1% 100.0% of Events, Binary t-online Valency Positive/ Count 59 34 93 of Ambivalent % within Valency 63.4% 36.6% 100.0% Events, of Events, Binary Binary Negative Count 62 46 108 % within Valency 57.4% 42.6% 100.0% of Events, Binary Total Count 121 80 201 % within Valency 60.2% 39.8% 100.0% of Events, Binary Zeit Valency Positive/ Count 52 14 66 of Ambivalent % within Valency 78.8% 21.2% 100.0% Events, of Events, Binary Binary Negative Count 42 48 90 % within Valency 46.7% 53.3% 100.0% of Events, Binary Total Count 94 62 156 % within Valency 60.3% 39.7% 100.0% of Events, Binary Total Valency positive/ Count 261 114 375 of Ambivalent % within VEB 69.6% 30.4% 100.0% Events, Negative Count 224 260 484 Binary % within VEB 46.3% 53.7% 100.0% Total Count 485 374 859 % within VEB 56.5% 43.5% 100.0%

220

Chi-Square Tests

Asymptotic Sig. Exact Sig. (2- Exact Sig. (1- Publication Value df (2-sided) sided) sided) Bild Pearson Chi-Square 28.170c 1 .000 Continuity Correctionb 25.865 1 .000 Likelihood Ratio 28.357 1 .000 Fisher's Exact Test .000 .000 Linear-by-Linear Association 27.921 1 .000 N of Valid Cases 113 n-tv Pearson Chi-Square 7.148d 1 .008 b

221 Continuity Correction 6.382 1 .012

Likelihood Ratio 7.237 1 .007 Fisher's Exact Test .008 .006 Linear-by-Linear Association 7.111 1 .008 N of Valid Cases 195 Spiegel Pearson Chi-Square 10.532e 1 .001 Continuity Correctionb 9.579 1 .002 Likelihood Ratio 10.808 1 .001 Fisher's Exact Test .002 .001 Linear-by-Linear Association 10.477 1 .001 N of Valid Cases 194 t-online Pearson Chi-Square .759f 1 .384 Continuity Correctionb .528 1 .467 Likelihood Ratio .761 1 .383 Fisher's Exact Test .391 .234 Linear-by-Linear Association .755 1 .385

Chi-Square Tests (continued).

Asymptotic Significance (2- Exact Sig. (2- Exact Sig. (1- Publication Value df sided) sided) sided) t-online N of Valid Cases 201 Zeit Pearson Chi-Square 16.405g 1 .000 Continuity Correctionb 15.091 1 .000 Likelihood Ratio 17.073 1 .000 Fisher's Exact Test .000 .000 Linear-by-Linear Association 16.300 1 .000

222 N of Valid Cases 156 a Total Pearson Chi-Square 46.739 1 .000 Continuity Correctionb 45.795 1 .000 Likelihood Ratio 47.495 1 .000 Fisher's Exact Test .000 .000 Linear-by-Linear Association 46.684 1 .000 N of Valid Cases 859 Note. a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 163.27. b. Computed only for a 2x2 table c. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 11.04. d. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 35.08. e. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 30.80. f. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 37.01. g. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 26.23.

Hypothesis H2

Frequencies All Actors

Case Summary

Cases Valid Missing Total N Percent N Percent N Percent Actorsa 562 100.0% 0 0.0% 562 100.0% Note. a. Group

Frequencies All Actors

Responses Actors N Percent Percent of Cases Israel Israel (Generic Reference) 150 7.6% 26.7% Israeli Civilian 42 2.1% 7.5% Israeli Settler 23 1.2% 4.1% Israeli Protestor 2 0.1% 0.4% Israeli Religious Person/Group 7 0.4% 1.2% Israeli Scientist 16 0.8% 2.8% Israeli Musician 5 0.3% 0.9% Israeli Athlete 27 1.4% 4.8% Israeli Business Person 5 0.3% 0.9% Israeli Actor 2 0.1% 0.4% Israeli Writer 4 0.2% 0.7% Israeli Politician 16 0.8% 2.8% Israeli Prime minister 226 11.5% 40.2% Israeli Opposition 199 10.1% 35.4% Israeli President 52 2.6% 9.3% Israeli Soldier 2 0.1% 0.4% Israeli Police 3 0.2% 0.5% Israeli Secret Service 13 0.7% 2.3% IDF/IAF 95 4.8% 16.9% Other Israeli State Institution 4 0.2% 0.7%

223

Frequencies All Actors (continued).

Responses Actors N Percent Percent of Cases Israeli Medical Personnel 2 0.1% 0.4% Israeli Court/Judge 15 0.8% 2.7% Israeli Local Government 6 0.3% 1.1% Israeli NGO 22 1.1% 3.9% Israeli Media/Press 4 0.2% 0.7% Israeli Business/Company 31 1.6% 5.5% Israeli Government 10 0.5% 1.8% Israeli Ministry of Foreign Affairs 23 1.2% 4.1% Israeli Ministry of Defense 5 0.3% 0.9% Israeli Ministry of Justice 23 1.2% 4.1% Israeli Ministry of Public Security 2 0.1% 0.4% Other Israeli Ministry 4 0.2% 0.7% Germany Germany (Generic Reference) 16 0.8% 2.8% German Civilian 30 1.5% 5.3% German Protestor 12 0.6% 2.1% German Religious Person/Group 13 0.7% 2.3% German Scientist 2 0.1% 0.4% German Musician 4 0.2% 0.7% German Athlete 7 0.4% 1.2% German Politician 24 1.2% 4.3% Chancellor 5 0.3% 0.9% Member of Bundestag 9 0.5% 1.6% German President 3 0.2% 0.5% Local German Politician 35 1.8% 6.2% German Military/Security Forces 4 0.2% 0.7% German Police 11 0.6% 2.0% German Secret Service 2 0.1% 0.4% German Court/Judge 5 0.3% 0.9% Local German Government 25 1.3% 4.4% German NGO 30 1.5% 5.3% German Media/Press 8 0.4% 1.4% German Business/Company 16 0.8% 2.8% German Government 26 1.3% 4.6% German Federal Foreign Office 21 1.1% 3.7%

224

Frequencies All Actors (continued).

Responses Actors N Percent Percent of cases Palestine Palestine (Generic Reference) 20 1.0% 3.6% Palestinian Civilian 11 0.6% 2.0% Palestinian Protestor 6 0.3% 1.1% Palestinian Musician 8 0.4% 1.4% Palestinian President 10 0.5% 1.8% Palestinian Minister 15 0.8% 2.7% Hamas Official 8 0.4% 1.4% PFLP Official 5 0.3% 0.9% Palestinian Military/Armed Group 25 1.3% 4.4% Hamas 41 2.1% 7.3% Islamic Jihad 48 2.4% 8.5% Palestinian NGO 5 0.3% 0.9% Other Arab Other Arab Actor 11 0.6% 2.0% Syria 31 1.6% 5.5% Lebanon 11 0.6% 2.0% Hezbollah 29 1.5% 5.2% Jordan 6 0.3% 1.1% Egypt 3 0.2% 0.5% Iran 67 3.4% 11.9% Other UK 7 0.4% 1.2% British Writer 6 0.3% 1.1% USA 70 3.6% 12.5% US company/business 15 0.8% 2.7% Turkey 7 0.4% 1.2% Russia 8 0.4% 1.4% Other Countries 18 0.9% 3.2% European Union 43 2.2% 7.7% United Nations 30 1.5% 5.3% International NGO 22 1.1% 3.9% BDS movement 29 1.5% 5.2% Total 1963 100.0% 349.3% Note. a. Group Up to five actors were coded per article. 225

Crosstable of Actors (Reduced) and Publication

Case Summary

Cases Valid Missing Total N Percent N Percent N Percent Actors (Reduced) 562 100.0% 0 0.0% 562 100.0% *Publication

Crosstabulation Actors (Reduced) *Publication

Publication t- Actor Bild n-tv Spiegel online Zeit Total Israel/Israelis Count 135 219 235 248 203 1040 Germany/Germans Count 109 34 58 67 40 308 Palestine/Palestinians Count 48 32 41 45 36 202 Other Arab Actors Count 11 23 17 22 18 91 Iran Count 10 10 16 14 17 67 European Union Count 8 13 9 6 7 43 Other Countries Count 5 12 13 9 7 46 USA Count 8 12 17 16 17 70 International actors Count 14 4 28 19 16 81 Total Count 92 119 119 131 101 562 Note. Up to five actors were coded per article.

226

Frequency of Actors (Reduced) (Not Weighted)

Case Summary

Cases Valid Missing Total N Percent N Percent N Percent Actors 562 100.0% 0 0.0% 562 100.0% (Reduced)a Note. a. Group

Frequencies Actors (Reduced)

Responses Percent of Actors (Reduced) N Percent Cases Israel/Israelis 1040 53.4% 185.1% Germany/Germans 308 15.8% 54.8% Palestine/Palestinians 202 10.4% 35.9% Other Arab actors 91 4.7% 16.2% Iran 67 3.4% 11.9% European Union 43 2.2% 7.7% Other countries 46 2.4% 8.2% USA 70 3.6% 12.5% International actors 81 4.2% 14.4% Total 1948 100.0% 346.6%

227

Frequency Actors (Reduced) (Weighted)

Case Summary

Cases Valid Missing Total N Percent N Percent N Percent Actors 917 100.0% 0 0.0% 917 100.0% (Reduced)a Note. a. Group

Frequencies Actors (Reduced)

Responses Percent of Actors (Reduced) N Percent Cases Israel/Israelis 1874 58.8% 204.4% Germany/Germans 350 11.0% 38.2% Palestine/Palestinians 358 11.2% 39.0% Other Arab actors 151 4.7% 16.5% Iran 96 3.0% 10.5% European Union 72 2.3% 7.9% Other countries 64 2.0% 7.0% USA 101 3.2% 11.0% International actors 119 3.7% 13.0% Total 3185 100.0% 347.3%

228

Crosstable Frequency of Actors (Reduced) per Publication (Not Weighted)

Case Summary

Cases Valid Missing Total N Percent N Percent N Percent Actors (Reduced) 562 100.0% 0 0.0% 562 100.0% *Publication

Crosstabulation Actors (Reduced) * Publication Publication

Actors (Reduced) Bild n-tv Spiegel t-online Zeit Total Israel/Israelis Count 135 219 235 248 203 1040 Germany/Germans Count 109 34 58 67 40 308 Palestine/Palestinians Count 48 32 41 45 36 202 Other Arab actors Count 11 23 17 22 18 91 Iran Count 10 10 16 14 17 67 European Union Count 8 13 9 6 7 43 Other countries Count 5 12 13 9 7 46 USA Count 8 12 17 16 17 70 International actors Count 14 4 28 19 16 81 Total Count 92 119 119 131 101 562 Note. Up to five actors were coded per article.

Crosstable Frequency of Actors (Reduced) per Publication (Weighted)

Case Summary

Cases Valid Missing Total N Percent N Percent N Percent Actors (Reduced) 917 100.0% 0 0.0% 917 100.0% *Publication

229

Crosstabulation Actors (Reduced) * Publication

Publication Actors Bild n-tv Spiegel t-online Zeit Total Israel/Israelis Count 228 397 434 451 364 1874 Germany/Germans Count 125 40 67 74 44 350 Palestine/Palestinians Count 73 56 79 83 67 358 Other Arab actors Count 13 40 30 37 31 151 Iran Count 13 17 23 20 23 96 European Union Count 14 21 16 9 12 72 Other countries Count 6 19 14 15 10 64 USA Count 13 15 28 21 24 101 International actors Count 19 7 44 26 23 119 Total Count 132 203 204 212 166 917 Note. Up to five actors were coded per article.

Hypothesis H2.1

Mean Evaluation of Actors per Publication

Case Processing Summary

Cases Included Excluded Total N Percent N Percent N Percent Actor Valency * Actor 1956 69.6% 854 30.4% 2810 100.0%

230

Report Actor Valency

Publication Bild n-tv SPIEGEL t-online Zeit Total Actor M N SD M N SD M N SD M N SD M N SD M N SD Israel .52 33 1.03 .13 24 1.26 -.52 31 1.00 .23 30 1.01 .29 31 1.01 .13 149 1.1 (Generic Reference) Israeli Civilian .75 4 .96 .09 11 1.51 .50 10 1.18 .56 9 1.24 1.13 8 .84 .55 42 1.21 Israeli Settler -1.17 3 1.53 -.6 5 .55 -1.0 5 1.00 -1.75 4 .50 -1.17 6 .75 -.91 23 1

231 Israeli Protestor .00 1 -1.00 1 -.50 2 .71

Israeli Religious .00 2 .00 -1.00 1 1.00 3 1.00 1.00 -1.0 1 .14 7 1.07

Person/Group Israeli Scientist .67 3 .58 .00 1 .75 4 .957 .67 6 1.033 1.00 2 1.41 .69 16 .87 Israeli Musician 2.00 1 1.00 4 .00 1.20 5 .45 Israeli Athlete .00 7 1.16 .56 9 1.01 1.00 1 -.17 6 1.33 .25 4 1.26 .22 27 1.12 Israeli Business -.67 3 .58 -1.0 1 .00 1 -.60 5 .55

Person Israeli Actor 2.00 1 2.00 1 2.00 2 .00 Israeli Writer 2.00 1 . 1.00 1 2.00 2 .00 1.75 4 .50 Israeli Politician .00 2 .00 .00 4 .00 -1.0 1 -.75 4 .50 .00 5 .00 -.25 16 .45 Israeli Prime -.48 25 .65 -.77 56 .81 -.82 49 .93 -.62 55 .68 -.64 39 .78 -.69 224 .79 Minister Israeli .00 20 .46 -.03 36 .61 .04 52 .34 .08 52 .39 -.08 38 .71 .01 198 .51 Opposition

Report Actor Valency (continued).

Publication Bild n-tv Spiegel t-online Zeit Total Actor M N SD M N SD M N SD M N SD M N SD M N SD Israeli President .00 3 .00 .00 16 .00 .00 17 .00 .00 7 .00 .00 9 .00 .00 52 .00 Israeli Soldier .00 1 -1.0 1 -.50 2 .71 Israeli Police 2.00 1 -1.0 2 1.41 .00 3 2.0 Israeli Secret 1.00 3 1.00 -1.33 3 1.16 -1.0 1 -.50 4 1.00 .00 2 1.41 -.31 13 1.25 service

232 IDF/IAF .29 14 1.07 .00 18 1.03 -.19 21 .60 -.29 24 .91 .11 18 1.02 -.05 95 .93 Other Israeli State .00 3 .00 .00 1 . .00 4 .00 Institution Israeli Medical 2.00 1 2.00 1 2.00 2 .00 Personnel Israeli Court/Judge -.25 4 1.26 -1.0 4 1.16 -1.00 3 1.00 -.50 4 1.00 -.67 15 1.05 Israeli Local .75 4 .96 1.00 1 .00 1 .67 6 .82 Government Israeli NGO 1.3 3 1.16 -.33 3 .58 1.17 6 .98 1.00 6 .89 .25 4 .50 .77 22 .97 Israeli Media/Press -.50 2 .71 .00 1 .00 1 . -.25 4 .50 Israeli 2.00 4 .00 .69 16 1.40 1.25 4 .96 -.20 5 1.79 .50 2 2.12 .77 31 1.43 Business/Company Israeli .00 2 .00 .25 4 .96 -.50 2 .71 .00 1 2.00 1 . .20 10 .92 Government Israeli Ministry of .50 8 .54 .00 3 1.73 .33 3 .58 .20 5 .45 .00 3 ,00 .27 22 .70 Foreign Affairs

Report Actor Valency (continued).

Publication Bild n-tv Spiegel t-online Zeit Total Actor M N SD M N SD M N SD M N SD M N SD M N SD Israeli Ministry of -.50 2 .71 .00 1 -.50 2 .71 -.40 5 .55 Defense Israeli Ministry of .00 4 .00 .25 4 .50 .11 9 .33 .17 6 .41 .13 23 .34 Justice Israeli Ministry of .50 2 .71 .50 2 .71

233 Public Security Other Israeli .00 2 .00 -1.00 2 .00 -.50 4 .58 Ministry Germany (Generic -2.0 1 . -.50 4 1.00 -1.0 2 .00 -.50 2 .71 -.57 7 1.27 -.69 16 1.01 Reference) German Civilian -.25 4 1.71 -.67 3 1.16 .00 1 . .43 14 1.09 -.38 8 1.51 .00 30 1.29 German Protestor -1.8 5 .45 -2.00 1 . -1.5 2 .71 -2.00 1 . -1.0 2 1.41 -1.64 11 .67 German Religious 1.00 2 .00 1.25 4 .50 .75 4 .50 1.00 3 1.00 1.00 13 .58 Person/Group German Scientist .00 1 . -2.00 1 . -1.00 2 1.41 German Musician -1.0 2 .00 1.00 1 . -.50 4 1.00 German Athlete .00 1 . 1.00 3 .00 2.00 1 . -.50 2 .71 .57 7 .98 German Politician -.33 6 1.37 -.33 3 1.53 .00 7 1.53 .00 3 .00 .20 5 .45 -.08 24 1.14 Chancellor 2.00 1 . .67 3 .58 1.00 1 . 1.00 5 .71 Member of .00 3 2.00 1.50 2 .71 1.00 2 .00 -.50 2 2.12 .44 9 1.51 Bundestag

Report Actor Valency (continued).

Publication Bild n-tv Spiegel t-online Zeit Total Actor M N SD M N SD M N SD M N SD M N SD M N SD German president -2.00 1 . -2.00 1 . 1.00 1 . -1.00 3 1.73 Local German .17 12 .39 .00 3 1.00 -.25 4 .50 -.31 13 .63 -.33 3 .58 -.11 35 .58 Politician German Military/Security 2.00 1 . .00 3 1.73 .50 4 1.73

234 Forces German Police -.57 7 .98 1.00 2 1.41 -.50 2 .71 -.27 11 1.10

German secret .00 1 . .00 1 . .00 2 .00

Service German -.50 2 2.12 .00 1 . -.80 5 1.30

Court/Judge Local German -.50 6 .55 -.50 2 .71 -.43 7 .54 -1.50 2 .71 .00 4 .00 -.29 24 .46 government German NGO .17 6 .41 -.80 10 1.03 .00 4 2.31 .00 5 .00 .25 4 .50 -.23 30 1.10 German - 1 . -1.00 2 1.41 -.67 3 1.16 -.17 6 .75 -.50 2 .71 -.88 8 .99 media/press 2.00 German .33 3 .58 .00 1 . .33 6 1.03 -.75 4 .50 -.50 2 .71 -.06 16 .85 business/company German .33 6 .82 -.50 8 .76 .14 7 .69 -1.00 2 1.41 -.33 3 .58 -.15 26 .83 government

Report Actor Valency (continued).

Publication Bild n-tv Spiegel t-online Zeit Total Actor M N SD M N SD M N SD M N SD M N SD M N SD German Federal -.71 7 .76 .00 1 . - 3 1.00 -.75 4 .96 -1.00 6 .89 -.81 21 .81 Foreign Office 1.00 Palestine (Generic - 1 . .13 8 .84 .20 5 .45 .33 3 .58 .00 3 .00 .05 20 .76 Reference) 2.00 Palestinian 1.00 2 .00 .80 5 .84 1.00 2 1.41 .00 2 1.41 .73 11 .91

235 Civilian Palestinian .00 1 . .00 1 . .00 2 1.41 -1.00 2 .00 -.33 6 .82

Protestor Palestinian -2.0 6 .00 -2.0 1 . -2.00 1 . -2.00 8 .00

Musician Palestinian .00 2 .00 .00 2 .00 -.33 3 .58 -.33 3 .58 -.20 10 .42

President Palestinian -.67 3 1.16 .00 4 .00 .00 2 .00 .00 5 .00 .00 1 . -.13 15 .52 Minister/Fatah Official Hamas Official .00 1 . .00 1 . .00 3 .00 .00 2 .00 .00 1 . .00 8 .00 PFLP Official -1.0 1 . .00 1 . -1.0 2 1.41 -2.00 1 . -1.00 5 1.00 Palestinian -1.6 7 .79 -1.17 6 .75 -.60 5 .55 -1.33 3 1.16 -1.50 4 1.00 -1.24 25 .83 Military/Armed Group

Report Actor Valency (continued).

Publication Bild n-tv Spiegel t-online Zeit Total Actor M N SD M N SD M N SD M N SD M N SD M N SD Hamas -1.1 12 1.00 -1.11 9 .78 - 9 .44 -.67 6 .82 -1.40 5 .89 -1.22 41 .85 1.78 Islamic Jihad -1.4 10 .84 -1.56 9 .88 -.82 11 .75 -1.64 11 .67 -1.86 7 .38 -1.42 48 .79 Palestinian NGO -1.0 3 1.00 -2.00 1 . -1.00 1 . -1.20 5 .84 Other Arab Actor .00 1 . .00 2 .00 .00 6 1.27 1.00 2 1.41 .18 11 1.08

236 Syria -.50 4 .58 -.17 6 .41 -.25 4 .50 -.13 8 .35 -.44 9 .73 -.29 31 .53 Lebanon .00 1 . .50 2 2.12 -.50 2 .71 .60 5 1.34 2.00 1 . .45 11 1.29

Hezbollah -1.6 5 .55 -1.80 5 .45 -.63 8 .52 -.60 5 .55 -1.33 6 1.03 -1.14 29 .79 Jordan .00 2 .00 .00 1 . .33 3 .58 .17 6 .41 Egypt 2.00 1 . .00 1 . .00 1 . .67 3 1.16 Iran -1.4 12 .79 -1.00 9 .71 .00 14 1.24 -1.15 20 .75 -.25 12 1.22 -.78 67 1.09 European Union -1.2 9 .97 -.13 8 .35 .00 9 .50 .00 10 .00 -.29 7 .95 -.33 43 .78 UK 1.00 1 . -2.0 3 .00 .00 2 .00 2.00 1 . -.43 7 1.62 British Writer .33 3 .58 -1.00 2 .00 .00 1 . -.17 6 .75 Other Country -.20 5 1.10 .33 6 1.37 -.25 4 .96 .33 3 1.53 .06 18 1.16 USA -.38 8 .74 -.68 19 .82 -1.0 15 1.00 -.44 16 .63 -.67 12 .78 -.66 70 .81 US -.29 7 .95 -.50 6 .55 -1.00 2 .00 -.47 15 .74

Company/Business Turkey -2.0 1 . .00 1 . .50 2 .71 .00 1 . -.50 2 .71 -.29 7 .95 Russia .00 1 . .00 1 . .00 1 . .00 5 .00 .00 8 .00

Report Actor Valency (continued).

Publication Bild n-tv Spiegel t-online Zeit Total Actor M N SD M N SD M N SD M N SD M N SD M N SD United Nations -1.0 4 1.16 -.57 7 .98 -.14 7 .38 -.50 8 .93 -.25 4 .50 -.47 30 .82 International NGO .00 1 . .00 4 .00 .56 9 .88 .25 4 .50 .75 4 1.50 .41 22 .85 BDS Movement -1.0 7 .82 -1.50 2 .71 -1.2 6 .98 -1.00 8 .93 -.83 6 .75 -1.03 29 .82 Total -.28 322 1.14 -.26 406 1.04 -.26 418 1.00 -.25 458 .94 -.20 352 1.03 -.25 1956 1.02 237

Independent T-test for Mean Evaluation of Israeli and Non-Israeli Actors

Group Statistics

Actor Std. Std. Error Binary N Mean Deviation Mean Actor Israeli 1035 -.06 .969 .030 Valency Non-Israeli 921 -.46 1.043 .034

Independent Samples Test Actor_valency Equal variances Equal variances assumed not assumed Levene's Test for F 59.213 Equality of Variances Sig. .000 t-test for Equality of t 8.790 8.752 Means df 1954 1885.851 Sig. (2-tailed) .000 .000 Mean Difference .400 .400 Std. Error Difference .046 .046 95% Confidence Lower .311 .310 Interval of the Upper .489 .490 Difference

238

Mean Evaluation of Israelis per Publication

Actor Valency (Only Israel, Reduced)

Publication Israeli Actor Total Bild n-tv SPIEGEL t-online Zeit (Reduced) M N SD M N SD M N SD M N SD M N SD M N SD Israel (Generic .13 149 1.10 .52 33 1.03 .13 24 1.26 .23 30 1.01 .23 30 1.01 .29 31 1.01 Reference) Civilian .49 110 1.13 .31 16 .95 .19 26 1.27 .42 26 1.14 .42 26 1.14 .89 19 1.1 Settler -.91 23 1.0 .33 3 1.53 -.60 5 .55 -1.75 4 .50 -1.75 4 .50 -1.17 6 .75

239 Politician -.06 68 .24 .00 5 .00 .00 20 .00 -.27 11 .47 -.27 11 .47 0 14 0

Prime -.69 224 .79 -.48 25 .65 -.77 56 .81 -.62 55 .68 -.62 55 .68 -.64 39 .78 Minister Opposition .01 198 .51 .00 20 .46 -.03 36 .61 .08 52 .39 .08 52 .39 -.08 38 .71 Military -.09 113 .99 .50 18 1.10 -.18 22 1.10 -.32 28 .91 -.32 28 .91 .1 20 1.02 Other State -.07 27 1.17 .25 8 1.17 -.13 8 1.13 -.13 8 1.13 -.4 5 0.89 Institution NGO .77 22 .97 1.33 3 1.16 -.33 3 .58 1.00 6 .89 1.00 6 .89 .25 4 .5 Business/ .66 35 1.39 2.00 4 .00 .56 18 1.38 -.20 5 1.79 -.20 5 1.79 .33 3 1.53 Company Government .12 66 .65 .29 14 .61 .08 13 .86 -.05 19 .52 -.05 19 .52 .3 10 .68 Total -.06 1035 .97 .26 141 .96 -.13 231 1.03 -.11 244 .90 -.11 244 .90 -.02 189 .96

Hypothesis H2.2

T-Test for Independent Variables, Evaluation of Israelis during Conflict and Non- Conflict

Mean Evaluation of Israelis During Non-conflict/Conflict

N Mean Std. Deviation Std. Error Mean Israelis - no conflict 833 -.07 .984 .034 Israelis - conflict 202 -.04 .908 .064

T-Test for Independent Variables – Differences Between Evaluation of Israelis for Non- Conflict/Conflict.

Levene's Test

F Sig. t df Sig. (2- Mean Std. Error tailed) Difference Difference Lower Equal 2.852 .092 - 1033 .681 -.031 .076 -.180 variances .411 assumed Equal - 325.313 .667 -.031 .072 -.174 variances .431 not assumed

Hypothesis H3

Paired Sample T-test for Mean Number of Israeli and Palestinian Quotes During Conflict Between the Two

Paired Samples Statistics

Std. Std. Error Mean N Deviation Mean Quotes Israel 2.04 164 1.708 .133 Quotes Palestine .45 164 .703 .055 240

Paired Samples Correlations

N Correlation Sig. Pair 1 Quotes Israel & 164 .313 .000 Quotes Palestine

Paired Samples Test

Quotes Israel - Quotes Palestine Paired Mean 1.591 Differences Std. Deviation 1.631 Std. Error Mean .127 95% Confidence Lower 1.340 Interval of the Upper 1.843 Difference t 12.496 df 163 Sig. (2-tailed) .000

Hypothesis H3.1 Hypothesis H3.2

Crosstable Actor and Evaluation of Actor

Case Summary

Cases Valid Missing Total N Percent N Percent N Percent Actors all * 412 73.3% 150 26.7% 562 100.0% Valency Actors All

241

Crosstabulation Actors and Valency

Valency Very Neutral/No Very Mean Actor Positive Positive Tendency Negative Negative Evaluation Israelis Total N 74 211 619 137 74 .07 Israeli Civilian N 13 21 82 20 8 .076 Israeli Politician N 27 87 346 56 38 .016 Israeli Military/Security N 13 57 84 23 17 .134 Other Israeli State N 0 4 9 2 1 .000 Institution

242 Israeli NGO N 4 5 17 10 2 -.026

Israeli Media/Press N 0 0 26 3 1 -.167 Israeli N 1 3 1 1 0 .067 Business/Company Israeli Government N 16 34 54 22 7 .226 Germans Total N 90 133 217 53 51 .29 German Civilian N 16 21 54 14 11 .147 German Politician N 30 50 64 16 16 .352 German Military N 3 3 10 0 6 -.136 Other German State N 2 18 18 0 0 .058 Institution German NGO N 11 17 29 5 6 .324 German Media/Press N 12 2 1 2 3 .900 German Business N 5 5 9 3 2 .333 German Government N 11 17 32 13 7 .150

Crosstabulation Actors and Valency (continued).

Valency Very Neutral/No Very Mean Actor Positive Positive Tendency Negative Negative Evaluation Palestinians Total N 25 55 93 55 73 -.32 Unspecified Pal. N 3 0 1 5 3 -.417 Palestinian Civilian N 2 5 13 5 13 -0.5789 Palestinian Politician N 17 39 63 41 49 -.316 Palestinian Military N 3 11 16 4 8 -.071 Other Regional Total N 9 38 68 31 40 -.30

243 Actors Syria N 4 10 13 5 0 .406

Lebanon N 3 9 20 8 6 -.109 Jordan N 2 3 7 6 7 -.520 Iran N 0 10 18 2 12 -.381 Turkey N 0 1 4 5 6 -1.000 Other N 0 5 6 5 9 -.720 Other Countries Total N 29 37 63 30 36 -.04 UK N 0 0 1 2 2 -1.200 USA N 26 33 57 24 30 .006 Other N 3 4 5 4 4 -.100 International actors Total N 16 33 44 28 40 -.27 European Union N 9 8 10 13 17 -.368 International NGO N 5 14 13 7 7 .065 United Nations N 2 11 21 8 16 -.431 Total N 243 507 1104 334 314 .012

Syntax for Combining the Variables for Quoted Actors and Their Evaluation of Israel in one Variable if (Quoted_Actor1_binary=100 & VQA1_binary=1) VQA1test=1. if (Quoted_Actor1_binary=100 & VQA1_binary=0) VQA1test=2. if (Quoted_Actor1_binary=200 & VQA1_binary=1) VQA1test=3. if (Quoted_Actor1_binary=200 & VQA1_binary=0) VQA1test=4. EXECUTE if (Quoted_Actor2_binary=100 & VQA2_binary=1) VQA2test=1. if (Quoted_Actor2_binary=100 & VQA2_binary=0) VQA2test=2. if (Quoted_Actor2_binary=200 & VQA2_binary=1) VQA2test=3. if (Quoted_Actor2_binary=200 & VQA2_binary=0) VQA2test=4. EXECUTE if (Quoted_Actor3_binary=100 & VQA3_binary=1) VQA3test=1. if (Quoted_Actor3_binary=100 & VQA3_binary=0) VQA3test=2. if (Quoted_Actor3_binary=200 & VQA3_binary=1) VQA3test=3. if (Quoted_Actor3_binary=200 & VQA3_binary=0) VQA3test=4. EXECUTE if (Quoted_Actor4_binary=100 & VQA4_binary=1) VQA4test=1. if (Quoted_Actor4_binary=100 & VQA4_binary=0) VQA4test=2. if (Quoted_Actor4_binary=200 & VQA4_binary=1) VQA4test=3. if (Quoted_Actor4_binary=200 & VQA4_binary=0) VQA4test=4. EXECUTE if (Quoted_Actor5_binary=100 & VQA5_binary=1) VQA5test=1. if (Quoted_Actor5_binary=100 & VQA5_binary=0) VQA5test=2. if (Quoted_Actor5_binary=200 & VQA5_binary=1) VQA5test=3. if (Quoted_Actor5_binary=200 & VQA5_binary=0) VQA5test=4. EXECUTE

COMPUTE VQA_Isr_pos=0. if (VQA1test=1 | VQA2test=1 | VQA3test=1 | VQA4test=1 | VQA5test=1) VQA_Isr_pos=1. EXECUTE

244

COMPUTE VQA_Isr_neg=0. if (VQA1test=2 | VQA2test=2 | VQA3test=2 | VQA4test=2 | VQA5test=2) VQA_Isr_neg=1. EXECUTE

COMPUTE VQA_nonIsr_pos=0. if (VQA1test=3 | VQA2test=3 | VQA3test=3 | VQA4test=3 | VQA5test=3) VQA_nonIsr_pos=1. EXECUTE

COMPUTE VQA_nonIsr_neg=0. if (VQA1test=4 | VQA2test=4 | VQA3test=4 | VQA4test=4 | VQA5test=4) VQA_nonIsr_neg=1. EXECUTE

Compute VQA_filter=1. if (VQA_Isr_pos=0 & VQA_Isr_neg=0 & VQA_nonIsr_pos=0 & VQA_nonIsr_neg=0) VQA_filter=0. Execute

Compute VQA_all_pos=0. if (VQA_Isr_pos=1 | VQA_nonIsr_pos=1) VQA_all_pos=1. Execute

Compute VQA_all_neg=0. if (VQA_Isr_neg=1 | VQA_nonIsr_neg=1) VQA_all_neg=1. Execute

245

Crosstable and Chi²-Test for Occurance of Israeli Quotes with Positive Evaluation and Non-Israeli Quotes with Negative Evaluation of Israel

Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Israeli-Positive (Binary) * Non- 562 100.0% 0 0.0% 562 100.0% Israeli-Negative (Binary)

Crosstabulation Israeli-Positive (binary) * Non-Israeli-Negative (binary)

Non-Israeli-negative (binary) No Yes Total Israeli-Positive No 376 70 446 (Binary) Yes 77 39 116 Total 453 109 562

Chi-Square Tests

Asymptotic Significance Exact Sig. (2- Exact Sig. (1- Value df (2-sided) sided) sided) Pearson Chi-Square 18.921a 1 .000 Continuity 17.792 1 .000

Correctionb Likelihood Ratio 17.123 1 .000 Fisher's Exact Test .000 .000 Linear-by-Linear 18.888 1 .000

Association N of Valid Cases 562 Note. a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 22.50. b. Computed only for a 2x2 table

246

Symmetric Measures

Approximate Exact Value Significance Significance Nominal by Phi .183 .000 .000 Nominal Cramer's V .183 .000 .000 N of Valid Cases 562

Crosstable All Positive and Negative Evaluations in Quotes

Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent VQA all-positive (binary) * VQA 562 100.0% 0 0.0% 562 100.0% all-negative (binary)

Crosstabulation Valency of Quoted Actors All-Positive (Binary) * Valency of Quoted Actors All-Negative (Binary)

All-Negative (Ninary) No Yes Total All-Positive No Count 272 90 362 (Binary) Expected Count 263.4 98.6 362.0 Yes Count 137 63 200 Expected Count 145.6 54.4 200.0 Total Count 409 153 562 Expected Count 409.0 153.0 562.0

247

Chi-Square Tests

Asymptotic Significance Exact Sig. Exact Sig. Point Value df (2-sided) (2-sided) (1-sided) Probability Pearson Chi- 2.865a 1 .091 .094 .056 Square Continuity 2.540 1 .111 Correctionb Likelihood Ratio 2.830 1 .093 .113 .056 Fisher's Exact .094 .056 Test Linear-by-Linear 2.860c 1 .091 .094 .056 .019 Association N of Valid Cases 562 Note. a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 54.45. b. Computed only for a 2x2 table c. The standardized statistic is 1.691.

Crosstable All Positive and Negative Evaluations in Quotes, Leveled per Publication

Case Processing Summary

Valency Quoted Actors Cases Valid Missing Total N Percent N Percent N Percent All-Positive (Binary) 562 100.0% 0 0.0% 562 100.0% * All-Negative (Binary) * Publication

248

Crosstabulation Valency Quoted Actor All-Positive (Binary) * Valency Quoted Actor All-Negative (Binary) * Publication

VQA All-Negative (Binary) Publication No Yes Total Bild VQA All- No 39 9 48 Positive (Binary) Yes 32 12 44 Total 71 21 92 n-tv VQA All- No 57 20 77 Positive (Binary) Yes 27 15 42 Total 84 35 119 Spiegel VQA All- No 66 18 84 Positive (Binary) Yes 25 10 35 Total 91 28 119 t-online VQA All- No 64 24 88 Positive (Binary) Yes 28 15 43 Total 92 39 131 Zeit VQA All- No 46 19 65 Positive (Binary) Yes 25 11 36 Total 71 30 101 Total QA All-Positive No 272 90 362 (Binary) Yes 137 63 200 Total 409 153 562

249

Chi-Square Tests

Asymptotic Exact Exact Sig. Sig. Sig. Publication Value df (2-sided) (2-sided) (1-sided) Bild Pearson Chi-Square .947c 1 .331 Continuity Correctionb .525 1 .469 Likelihood Ratio .947 1 .330 Fisher's Exact Test .456 .234 Linear-by-Linear .936 1 .333 Association N of Valid Cases 92 n-tv Pearson Chi-Square 1.242d 1 .265 Continuity Correctionb .817 1 .366 Likelihood Ratio 1.223 1 .269 Fisher's Exact Test .297 .183 Linear-by-Linear 1.231 1 .267 Association N of Valid Cases 119 Spiegel Pearson Chi-Square .701e 1 .403 Continuity Correctionb .360 1 .549 Likelihood Ratio .683 1 .408 Fisher's Exact Test .478 .271 Linear-by-Linear .695 1 .405 Association N of Valid Cases 119 t-online Pearson Chi-Square .800f 1 .371 Continuity Correctionb .478 1 .489 Likelihood Ratio .789 1 .374 Fisher's Exact Test .418 .243 Linear-by-Linear .794 1 .373 Association N of Valid Cases 131 Zeit Pearson Chi-Square .019g 1 .889 Continuity Correctionb .000 1 1.000 Likelihood Ratio .019 1 .889 Fisher's Exact Test 1.000 .531 Linear-by-Linear .019 1 .890 Association

250

N of Valid Cases 101 Chi-Square Tests (continued).

Publication Value df Asymptotic Exact Sig. Exact Sig. Significanc (2-sided) (1-sided) e (2-sided) Total Pearson Chi-Square 2.865a 1 .091 Continuity Correctionb 2.540 1 .111 Likelihood Ratio 2.830 1 .093 Fisher's Exact Test .094 .056 Linear-by-Linear 2.860 1 .091 Association N of Valid Cases 562 Note. a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 54.45. b. Computed only for a 2x2 table c. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 10.04. d. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 12.35. e. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 8.24. f. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 12.80. g. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 10.69.

251

Symmetric Measures Approximate Publication Value Significance Bild Nominal by Phi .101 .331 Nominal Cramer's V .101 .331 N of Valid Cases 92 n-tv Nominal by Phi .102 .265 Nominal Cramer's V .102 .265 N of Valid Cases 119 Spiegel Nominal by Phi .077 .403 Nominal Cramer's V .077 .403 N of Valid Cases 119 t-online Nominal by Phi .078 .371 Nominal Cramer's V .078 .371 N of Valid Cases 131 Zeit Nominal by Phi .014 .889 Nominal Cramer's V .014 .889 N of Valid Cases 101 Total Nominal by Phi .071 .091 Nominal Cramer's V .071 .091 N of Valid Cases 562

Hypothesis H4

Crosstable and Fisher’s Exact Test for Contentual Dissonant and Coherent Articles per Publication

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent Publication * Content 562 100.0% 0 0.0% 562 100.0% Coherency1

252

Crosstabulation Publication * Content coherency1

Content coherency1 Publication Dissonant Coherent Total Bild 4 88 92 n-tv 6 113 119 Spiegel 5 114 119 t-online 2 129 131 Zeit 6 95 101 Total 23 539 562

Chi-Square Tests

Asymptotic Significance Exact Sig. Exact Sig. Point Value df (2-sided) (2-sided) (1-sided) Probability Pearson Chi-Square 3.368a 4 .498 .507 Likelihood Ratio 3.916 4 .417 .446 Fisher's Exact Test 3.797 .427 Linear-by-Linear .038b 1 .846 .875 .454 .061 Association N of Valid Cases 562 Note. a. 4 cells (40.0%) have expected count less than 5. The minimum expected count is 3.77. b. The standardized statistic is .194.

253

Hypothesis H4.1

Crosstable Contentual Dissonant Articles to the Disadvantage and Advantage of Israel per Publication

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent Publication * Content 23 4.1% 539 95.9% 562 100.0% Coherency 2

Crosstabulation Publication * Content Coherency 2

Content Coherency 2 To the To the Disadvantage Neither/ Advantage of Publication of Israel Neutral Israel Total Bild 0 1 3 4 n-tv 4 1 1 6 Spiegel 5 0 0 5 t-online 1 0 1 2 Zeit 5 0 1 6 Total 15 2 6 23

254

Chi-Square Tests

Asymptotic Exact Exact Sig. Sig. Sig. Point Value df (2-sided) (2-sided) (1-sided) Probability Pearson Chi-Square 12.522a 8 .129 .108 Likelihood Ratio 15.629 8 .048 .051 Fisher's Exact Test 12.202 .037 Linear-by-Linear 3.173b 1 .075 .088 .043 .014 Association N of Valid Cases 23 Note. a. 15 cells (100.0%) have expected count less than 5. The minimum expected count is .17. b. The standardized statistic is -1.781.

Mean Evaluation of Contentual Dissonant Articles per Publication

Case Processing Summary

Cases Included Excluded Total N Percent N Percent N Percent Content Coherency 2 * 23 4.1% 539 95.9% 562 100.0% Publication

Report Content Coherency 2

Std. Publication Mean N Deviation Bild .75 4 .500 n-tv -.50 6 .837 Spiegel -1.00 5 .000 t-online .00 2 1.414 Zeit -.67 6 .816 Total -.39 23 .891

255

ANOVA and Post-Hoc-Test for Mean Evaluation of Contentual Dissonant Articles per Publication

Test of Homogeneity of Variances: Content Coherency 2

Levene Statistic df1 df2 Sig. 3.558 4 18 .026

ANOVA Content Coherency 2

Sum of Squares df Mean Square F Sig. Between Groups 7.895 4 1.974 3.707 .023 Within Groups 9.583 18 .532 Total 17.478 22

256

Multiple Comparisons Dependent Variable: Content Coherency 2 Games-Howell

Mean 95% Confidence Interval (I) (J) Difference Std. Lower Upper Publication Publication (I-J) Error Sig. Bound Bound Bild n-tv 1.250 .423 .099 -.21 2.71 Spiegel 1.750* .250 .023 .42 3.08 t-online .750 1.031 .926 -19.51 21.01 Zeit 1.417 .417 .054 -.02 2.86 n-tv Bild -1.250 .423 .099 -2.71 .21 Spiegel .500 .342 .621 -.87 1.87 t-online -.500 1.057 .980 -17.38 16.38 Zeit .167 .477 .996 -1.40 1.74 Spiegel Bild -1.750* .250 .023 -3.08 -.42 n-tv -.500 .342 .621 -1.87 .87 t-online -1.000 1.000 .843 -27.22 25.22 Zeit -.333 .333 .846 -1.67 1.00 t-online Bild -.750 1.031 .926 -21.01 19.51 n-tv .500 1.057 .980 -16.38 17.38 Spiegel 1.000 1.000 .843 -25.22 27.22 Zeit .667 1.054 .950 -16.50 17.83 Zeit Bild -1.417 .417 .054 -2.86 .02 n-tv -.167 .477 .996 -1.74 1.40 Spiegel .333 .333 .846 -1.00 1.67 t-online -.667 1.054 .950 -17.83 16.50 Note. *. The mean difference is significant at the 0.05 level.

257

Hypothesis H4.2

Paired Samples T-Test for Headline and Teaser/Text Evaluation

Paired Samples Statistics

Std. Std. Error Mean N Deviation Mean Headline -.36 22 .848 .181 Evaluation Teaser Text -.2273 22 .66775 .14236 Evaluation

Paired Samples Correlations

N Correlation Sig. Pair 1 Headline Evaluation & 22 .899 .000 Teaser Text Evaluation

Paired Samples Test

Headline Evaluation - Teaser Text Evaluation Paired Differences Mean -.13636 Std. Deviation .38365 Std. Error Mean .08179 95% Confidence Lower -.30646 Interval of the Upper .03374 Difference t -1.667 df 21 Sig. (2-tailed) .110

258

Hypothesis H5

Mean Overall Evaluation in the Sample (Not Weighted)

Descriptive Statistics

Std. N Mean Deviation Variance Overall Valency 562 .18 .955 .912 Valid N (Listwise) 562

Mean Overall Evaluation in the Sample (Weighted)

Descriptive Statistics

Std. N Mean Deviation Variance Overall Valency 917 .10 .953 .908 Valid N (Listwise) 917

Hypothesis H6

Mean Overall Evaluation per Publication (Not Weighted)

Case Processing Summary

Cases Included Excluded Total N Percent N Percent N Percent Overall Valency 562 100.0% 0 0.0% 562 100.0% * Publication

259

Report Overall Valency

Std. Publication Mean N Deviation Bild 1.04 92 .913 n-tv .08 119 .922 Spiegel -.04 119 .951 t-online .02 131 .673 Zeit -.01 101 .933 Total .18 562 .955

Mean Overall Evaluation per Publication (Weighted)

Case Processing Summary

Cases Included Excluded Total N Percent N Percent N Percent Overall Valency 917 100.0% 0 0.0% 917 100.0% * Publication

Report Overall Valency

Std. Publication Mean N Deviation Bild 1.06 132 .947 n-tv .03 203 .898 Spiegel -.14 204 .933 t-online -.02 212 .663 Zeit -.12 166 .907 Total .10 917 .953

260

ANOVA Overall Evaluation per Publication with Post-Hoc (Not Weighted)

Test of Homogeneity of Variances: Overall Valency

Levene Statistic df1 df2 Sig. 5.288 4 557 .000

ANOVA Overall Valency

Sum of Squares df Mean Square F Sig. Between Groups 82.631 4 20.658 26.830 .000 Within Groups 428.857 557 .770 Total 511.488 561

261

Multiple Comparisons Dependent Variable: Overall Valency Games-Howell

Mean 95% Confidence Interval (I) (J) Difference Std. Lower Upper Publication Publication (I-J) Error Sig. Bound Bound Bild n-tv .968* .127 .000 .62 1.32 Spiegel 1.085* .129 .000 .73 1.44 t-online 1.021* .112 .000 .71 1.33 Zeit 1.053* .133 .000 .69 1.42 n-tv Bild -.968* .127 .000 -1.32 -.62 Spiegel .118 .121 .869 -.22 .45 t-online .053 .103 .986 -.23 .34 Zeit .086 .126 .960 -.26 .43 Spiegel Bild -1.085* .129 .000 -1.44 -.73 n-tv -.118 .121 .869 -.45 .22 t-online -.065 .105 .972 -.35 .22 Zeit -.032 .127 .999 -.38 .32 t-online Bild -1.021* .112 .000 -1.33 -.71 n-tv -.053 .103 .986 -.34 .23 Spiegel .065 .105 .972 -.22 .35 Zeit .033 .110 .998 -.27 .34 Zeit Bild -1.053* .133 .000 -1.42 -.69 n-tv -.086 .126 .960 -.43 .26 Spiegel .032 .127 .999 -.32 .38 t-online -.033 .110 .998 -.34 .27 Note. *. The mean difference is significant at the 0.05 level.

ANOVA Overall Evaluation per Publication with Post-Hoc (Weighted)

Test of Homogeneity of Variances Overall Valency

Levene Statistic df1 df2 Sig. 11.757 4 912 .000

262

ANOVA Overall Valency

Sum of Squares df Mean Square F Sig. Between Groups 145.944 4 36.486 48.533 .000 Within Groups 685.624 912 .752 Total 831.568 916

Multiple Comparisons Dependent Variable: Overall Valency Games-Howell

(I) (J) Mean Std. Sig. 95% Confidence Interval Publication Publication Difference Error Lower Upper (I-J) Bound Bound Bild n-tv 1.026* .104 .000 .74 1.31 Spiegel 1.203* .105 .000 .91 1.49 t-online 1.084* .094 .000 .83 1.34 Zeit 1.181* .108 .000 .88 1.48 n-tv Bild -1.026* .104 .000 -1.31 -.74 Spiegel .177 .091 .295 -.07 .43 t-online .058 .078 .945 -.16 .27 Zeit .155 .094 .472 -.10 .41 Spiegel Bild -1.203* .105 .000 -1.49 -.91 n-tv -.177 .091 .295 -.43 .07 t-online -.119 .080 .571 -.34 .10 Zeit -.022 .096 .999 -.28 .24 t-online Bild -1.084* .094 .000 -1.34 -.83 n-tv -.058 .078 .945 -.27 .16 Spiegel .119 .080 .571 -.10 .34 Zeit .097 .084 .776 -.13 .33 Zeit Bild -1.181* .108 .000 -1.48 -.88 n-tv -.155 .094 .472 -.41 .10 Spiegel .022 .096 .999 -.24 .28 t-online -.097 .084 .776 -.33 .13 Note. *. The mean difference is significant at the 0.05 level.

263

Additional Findings

Topics and Evaluation

Mean Evaluation of Main Topics (Simplified, Not Weighted)

Case Processing Summary

Cases Included Excluded Total N Percent N Percent N Percent Overall Valency * 562 100.0% 0 0.0% 562 100.0% Main Topic, Simplified

Report Overall Valency

Std. Main Topic, Simplified Mean N Deviation Israeli internal Affairs -.04 188 .776 Israeli external Affairs .31 36 .920 German-Israeli Affairs .75 110 .826 Arab-Israeli Conflict -.01 199 1.044 Other Topics .59 29 .867 Total .18 562 .955

Mean Evaluation of Main Topics (Simplified, Weighted)

Case Processing Summary

Cases Included Excluded Total N Percent N Percent N Percent Overall Valency * Main Topic, 917 100.0% 0 0.0% 917 100.0% Simplified

264

Report Overall Valency

Std. Main Topic, Simplified Mean N Deviation Israeli internal Affairs -.07 357 .746 Israeli external Affairs .25 53 .918 German-Israeli Affairs .78 119 .835 Arab-Israeli Conflict -.02 350 1.070 Other Topics .55 38 .860 Total .10 917 .953

Mean Evaluation of Main Topics (Reduced, Weighted)

Case Processing Summary

Cases Included Excluded Total N Percent N Percent N Percent Overall valency * Main Topic, 562 100.0% 0 0.0% 562 100.0% reduced

265

Report Overall Valency

Main Topic, Reduced Mean N Std. Deviation Israeli Internal Politics -.18 162 .609 Israeli Economy .78 9 1.481 Israeli Sports .50 6 1.225 Israeli Sciences 1.00 3 .000 Israeli Culture 1.13 8 .641 Israeli Trade/Economy .00 10 1.155 Israeli External Sports .47 19 .905 Israeli Diplomacy .29 7 .488 German Affairs .67 21 .856 German Government Decision -.33 6 .816 German Internal Politics .81 31 .749 Holocaust .25 4 .500 Antisemitism in Germany .91 35 .818 German Economy/Trade 1.17 6 .408 Culture .33 3 .577 Other German-Israeli Issues 1.25 4 .957 Arab-Israeli Conflict -.38 8 1.188 Israeli Military Action .06 35 1.027 Palestinian Military Action .65 26 1.056 Conflict Involving Other Actor in the Region .05 20 .686 BDS Movement .00 7 .577 Settlements -.91 34 .866 Iranian Affairs .16 19 .501 Internal Affair of Other Actor in the Region .57 7 1.134 EU Politics .24 17 1.200 United Nations 1.43 7 .787 USA Politics -.47 17 .514 Other Topics .75 8 1.282 History .83 6 .753 Oddity .33 6 .516 Crime .00 5 .000 Personal Experience .50 6 1.049 Total .18 562 .955

266

ANOVA Mean Overall Evaluation per Main Topic (Simplified, Not Weighted) ANOVA Overall Valency

Sum of Squares df Mean Square F Sig. Between Groups 57.722 4 14.431 17.714 .000 Within Groups 453.765 557 .815 Total 511.488 561

ANOVA Mean Overall Evaluation per Main Topic (Simplified, Not Weighted)

ANOVA Overall Valency

Sum of Squares df Mean Square F Sig. Between Groups 80.119 4 20.030 24.309 .000 Within Groups 751.449 912 .824 Total 831.568 916

267

Mean Overall Evaluation per Topic and Publication

Report Overall Valency

Publication Main Topic, Simplified Bild n-tv Spiegel t-online Zeit Total Mean Israeli Internal Affairs .20 .09 -.14 -.13 -.05 -.04 Israeli External Affairs .25 .27 1.00 -.11 .67 .31 German-Israeli Affairs 1.24 .25 .77 .44 .62 .75 Arab-Israeli Conflict 1.38 -.02 -.39 -.21 -.37 -.01 Other Topics 2.00 .00 .33 .75 1.20 .59 Total 1.04 .08 -.04 .02 -.01 .18 N Israeli Internal Affairs 15 45 43 46 39 188 Israeli External Affairs 8 11 5 9 3 36 German-Israeli Affairs 38 12 13 34 13 110 Arab-Israeli Conflict 29 45 46 38 41 199 Other Topics 2 6 12 4 5 29 Total 92 119 119 131 101 562 SD Israeli Internal Affairs .862 .874 .804 .453 .887 .776 Israeli External Affairs .463 1.272 1.000 .601 .577 .920 German-Israeli Affairs .786 .866 .832 .613 .768 .826 Arab-Israeli Conflict .820 .965 .930 .741 .829 1.044 Other Topics .000 .000 .778 .957 .837 .867 Total .913 .922 .951 .673 .933 .955

ANOVA for Mean Evaluation of Arab-Israeli Conflict per Publication

Test of Homogeneity of Variances Overall Valency

Levene Statistic df1 df2 Sig. 1.196 4 194 .314

268

ANOVA Overall Valency

Sum of Squares df Mean Square F Sig. Between Groups 69.390 4 17.348 22.958 .000 Within Groups 146.590 194 .756 Total 215.980 198

Multiple Comparisons Dependent Variable: Overall Valency Bonferroni

Mean 95% Confidence Interval (I) (J) Difference Std. Lower Upper Publication Publication (I-J) Error Sig. Bound Bound Bild n-tv 1.402* .207 .000 .81 1.99 Spiegel 1.771* .206 .000 1.19 2.36 t-online 1.590* .214 .000 .98 2.20 Zeit 1.745* .211 .000 1.15 2.34 n-tv Bild -1.402* .207 .000 -1.99 -.81 Spiegel .369 .182 .442 -.15 .89 t-online .188 .192 1.000 -.36 .73 Zeit .344 .188 .686 -.19 .88 Spiegel Bild -1.771* .206 .000 -2.36 -1.19 n-tv -.369 .182 .442 -.89 .15 t-online -.181 .191 1.000 -.72 .36 Zeit -.025 .187 1.000 -.56 .50 t-online Bild -1.590* .214 .000 -2.20 -.98 n-tv -.188 .192 1.000 -.73 .36 Spiegel .181 .191 1.000 -.36 .72 Zeit .155 .196 1.000 -.40 .71 Zeit Bild -1.745* .211 .000 -2.34 -1.15 n-tv -.344 .188 .686 -.88 .19 Spiegel .025 .187 1.000 -.50 .56 t-online -.155 .196 1.000 -.71 .40 Note. *. The mean difference is significant at the 0.05 level. 269

ANOVA for Mean Evaluation of German-Israeli Topics per Publication

Test of Homogeneity of Variances Overall Valency

Levene Statistic df1 df2 Sig. .909 4 105 .462

ANOVA Overall Valency

Sum of Squares df Mean Square F Sig. Between Groups 15.487 4 3.872 6.904 .000 Within Groups 58.885 105 .561 Total 74.373 109

270

Multiple Comparisons Dependent Variable: Overall Valency Bonferroni

Mean 95% Confidence Interval (I) (J) Difference Std. Lower Upper Publication Publication (I-J) Error Sig. Bound Bound Bild n-tv .987* .248 .001 .28 1.70 Spiegel .468 .241 .546 -.22 1.16 t-online .796* .177 .000 .29 1.30 Zeit .621 .241 .112 -.07 1.31 n-tv Bild -.987* .248 .001 -1.70 -.28 Spiegel -.519 .300 .862 -1.38 .34 t-online -.191 .251 1.000 -.91 .53 Zeit -.365 .300 1.000 -1.23 .49 Spiegel Bild -.468 .241 .546 -1.16 .22 n-tv .519 .300 .862 -.34 1.38 t-online .328 .244 1.000 -.37 1.03 Zeit .154 .294 1.000 -.69 1.00 t-online Bild -.796* .177 .000 -1.30 -.29 n-tv .191 .251 1.000 -.53 .91 Spiegel -.328 .244 1.000 -1.03 .37 Zeit -.174 .244 1.000 -.87 .53 Zeit Bild -.621 .241 .112 -1.31 .07 n-tv .365 .300 1.000 -.49 1.23 Spiegel -.154 .294 1.000 -1.00 .69 t-online .174 .244 1.000 -.53 .87 Note. *. The mean difference is significant at the 0.05 level.

271

Conflict and Evaluation

Two-Way ANOVA for Differences in the Mean Overall Evaluation during Conflict and Non-Conflict per Publication

Between-Subjects Factors

Value Label N Publication 1 Bild 92 2 n-tv 119 3 Spiegel 119 4 t-online 131 5 Zeit 101 NF: Conflict 0 Nein 449 1 Ja 113

272

Descriptive Statistics Dependent Variable: Overall Valency

Std. Publication NF: Conflict Mean Deviation N Bild Nein .92 .912 75 Ja 1.59 .712 17 Total 1.04 .913 92 n-tv Nein .00 .934 95 Ja .38 .824 24 Total .08 .922 119 Spiegel Nein -.02 .967 93 Ja -.12 .909 26 Total -.04 .951 119 t-online Nein .01 .690 104 Ja .07 .616 27 Total .02 .673 131 Zeit Nein .06 .960 82 Ja -.32 .749 19 Total -.01 .933 101 Total Nein .16 .951 449 Ja .26 .971 113 Total .18 .955 562

Levene's Test of Equality of Error Variancesa Dependent Variable: Overall Valency

F df1 df2 Sig. 2.299 9 552 .015 Note. Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a. Design: Intercept + Publication + NF Conflict + Publication * NF Conflict

273

Tests of Between-Subjects Effects Dependent Variable: Overall Valency

Source Type III Sum df Mean Square F Sig. of Squares Corrected Model 93.971a 9 10.441 13.804 .000 Intercept 23.266 1 23.266 30.760 .000 Publication 76.215 4 19.054 25.191 .000 NF Conflict 1.424 1 1.424 1.882 .171 Publication * NF 10.208 4 2.552 3.374 .010 Conflict Error 417.516 552 .756 Total 530.000 562 Corrected Total 511.488 561 Note. a. R Squared = .184 (Adjusted R Squared = .170)

274

Multiple Comparisons Dependent Variable: Overall valency Bonferroni

Mean 95% Confidence Interval (I) (J) Difference Std. Lower Upper Publication Publication (I-J) Error Sig. Bound Bound Bild n-tv .97* .121 .000 .63 1.31 Spiegel 1.09* .121 .000 .75 1.43 t-online 1.02* .118 .000 .69 1.35 Zeit 1.05* .125 .000 .70 1.41 n-tv Bild -.97* .121 .000 -1.31 -.63 Spiegel .12 .113 1.000 -.20 .44 t-online .05 .110 1.000 -.26 .36 Zeit .09 .118 1.000 -.25 .42 Spiegel Bild -1.09* .121 .000 -1.43 -.75 n-tv -.12 .113 1.000 -.44 .20 t-online -.06 .110 1.000 -.38 .25 Zeit -.03 .118 1.000 -.36 .30 t-online Bild -1.02* .118 .000 -1.35 -.69 n-tv -.05 .110 1.000 -.36 .26 Spiegel .06 .110 1.000 -.25 .38 Zeit .03 .115 1.000 -.29 .36 Zeit Bild -1.05* .125 .000 -1.41 -.70 n-tv -.09 .118 1.000 -.42 .25 Spiegel .03 .118 1.000 -.30 .36 t-online -.03 .115 1.000 -.36 .29 Note. Based on observed means. The error term is Mean Square(Error) = .756. *. The mean difference is significant at the

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