Staying Ahead on the Financial News

ASCoR, the Amsterdam School of Communication Research.

Staying ahead on the financial news

An agenda setting analysis between social media and traditional regarding the coverage of

the Dutch banking sector

Master Thesis

Written by Oscar Thiellier (Std. 6162347)

Graduate school of Communication

Master’s programme Communication science,

Corporate Communication master track

Supervised by Mr. Dr. Piet Verhoeven

Date of completion: 29th of July 2016

Abstract

The media landscape has changed drastically over the last decade. The online media is steadily taking over the role that once was only attributed to the traditional media; the dispersion of the news. This shift can have a big influence on corporations. Especially for the financial sector, that has to deal with a volatile stock market and strict government regulation, it is important to understand the dynamics in the coverage of the news in contemporary society. By using the classic theory of agenda-setting, this research tries to give insight in the bilateral relationship of the social media and the traditional media on the coverage of issues concerning the Dutch Banking sector. A content analysis of 2085 tweets and 276 newspaper articles is conducted to investigate the reportage on issue news concerning two of the largest banks in the Netherlands (i.e. the “Rabobank” and the “ABN AMRO”) over a fifteen day period. Both media agendas were compared and differentiated significantly on the overall issue coverage regarding the Dutch banking sector. Individual issues were also checked and differentiated significantly over the entire time period researched. Next, through the exploration of the percentages of coverage on the individual issues over the time period researched, this study found some indications that the attention of these issues on social media did have an influence on the attention of these issues in the traditional news media the next day. Lastly, issue obtrusiveness was measured to see whether the reportage on issues differed between the two media based on whether people have real-life personal experience with an issue. Comparing the obtrusiveness of the issues covered in both media showed no significant results, meaning the average obtrusiveness in both media was the same. Although no statistical evidence is found supporting agenda setting effects between both media on the coverage of issues concerning the financial, further research is suggested to investigate the delayed agenda-setting effects of social media on traditional news media indicated by the exploration of the individual variables.

Introduction

There is a call for a deeper investigation of where and how communication takes place in the age of the new and social media (Castell, 2009). The media landscape is changing drastically, and so is the way people gather information they need. A recent study by Newman et al. (2016) showed that news consumption is making a shift from the offline world to the online world, with usage of print media as a news source dropping (24 percent in 2016), and the use of social media as a news source rising (46 percent in 2016).Consequently, the

traditional role of the “printed” news media as one of the main producer and distributor of our day-to-day information is gradually disappearing, and is taken over by the virtue of the peer to peer network in the internet society. In the face of the changing communication flows within contemporary society, research has yet to grasp the essence of this phenomenon (Ceron, 2014). A well-known theory that can be used for explaining the communication flows between media, corporations, politics and the public is the agenda setting-theory by McCombs and Shaw (1972).

In 1972 McCombs and Shaw introduced the agenda setting theory. With this theory they made the mechanism behind media effects transparent. Showing that the minds of the public are not necessarily affected by the mere exposure to the media, but by being exposed the coverage of certain issues, the public is prone to think about them. This proposition is well encapsulated in Cohen’s (1963) quote, that the press "may not be successful much of the time in telling people what to think, but it is stunningly successful in telling its readers what to think about” (McCombs and Shaw, 1972).

Although the theory is still relevant today, it was developed in a time where only traditional media filled the media landscape. Nowadays, through technological development, the traditional media have to share their place in society with others. Bloggers, citizen journalists, Facebook and other social media, all are part of the media arena today. Through the internet, the news can spread faster and can bridge large distance easier. Furthermore online blogs and social media are viewed by traditional media as an important source for newsgathering (Sayre, 2010). Not only because they give the traditional media the eyes and sight from the citizens (Citizen Journalism), but also because it creates an expansion of the public sphere, where people can give their opinion and talk about issues that are important to them.

Although the agenda-setting theory has been a subject of research for many decades, only a few studies focussed on corporate communication (Carroll & McCombs, 2003). However to know how the media agenda is set could bring advantages for businesses. For instance, understanding the communication flows in the public sphere gives opportunities to corporations to help evaluate threats or gain control over their image or reputation (Meyer and Kleinnijenhuis, 2006b). A study conducted by Meyer and Kleinnijenhuis (2006a) combined the agenda-setting theory with issue ownership and found out that businesses who do well in issue management, are more likely to control the first and second level agenda-setting

concerning the company. Especially the financial sector, which primarily has to deal with volatile stock markets, could benefit from controlling the communication about issues concerning their organization. As a study by Tetlock (2007) showed that news coverage with a negative sentiment can cause a downwards pressure on the stock market. As stocks are integral part of the important products or assets of a corporation in the financial sector, to be able to predict the stock markets can be a valuable asset. Therefore it is important for have insights in the communication flows. Furthermore, the attention on issues concerning the financial sector in the media, albeit social media or traditional media, could invoke policy makers to regulate certain aspects of the financial sector (Cook et al., 1983), especially after the global financial crisis of 2008 (Helleiner and Pagliari, 2011). From all of the research that has been done on corporate communication in the financial world, almost no research yet has incorporated social media agendas. To find out how the media agenda is transferred, taking in account the social media, the following research question has been formulated:

RQ: Do the social media agenda and the traditional media influence each other concerning the news coverage on issues regarding the Dutch financial sector?

Theoretical framework

News media has always been accredited to have a considerable influence on corporations (e.g. Meijer and Kleinnijenhuis, 2006a). Cameron (1994), for instance, showed that third party editorial content could outperform advertisement when it comes to brand recognition. Another study conducted by Meijer and Kleinnijenhuis (2006a) found evidence that the way in which news about certain corporations are reported influences the reputation of those corporations. Especially in the financial world, the influence of the news media on the organizations can have big consequences. Chakravartty and Schiller (2010) suggest that the role financial news has played over the past decades contributed for a big part in the banking crisis of 2008. Another example is the Dutch “DSB bank”, which already had liquidity problems in 2009 due to the American banking crisis, but was still a viable organization. Only after news media covered the internal problems the bank struggled, the issue was put on the public agenda. This caused a “bank run” resulting in the bankruptcy of the organization (Scheltema et al., 2010). Although these examples concern the economic crisis and are not representing “common practice” in the financial world, they do show that the influence of news media on banks and other financial corporations can be imminent. Besides, there is significant evidence revealing the influence of news media on corporation

outside crisis times. For instance, Tetlock (2007) found evidence that media pessimism can have a negative effect on the prices of the stock market. Furthermore, there are numerous other studies demonstrated a direct link between media and corporations in the financial/banking sector (e.g. Deephouse, 2000; Bollen, Mao & Zeng, 2011). It is therefore of utter importance for corporations in the financial/banking sector to have insight in the dynamics of media influence within society. An excellent framework in communication practices that can provide such insights is the agenda-setting theory (Soroka, 2002). The roots of the agenda-setting theory lie in the political field of communication. Therefore most of the research done on this topic is done during political elections or is at least related to political communication (McCombs, 2005). Nonetheless, Carroll and McCombs (2003) argue that the main idea of the agenda-setting theory is applicable to subjects outside of the field of political communication. However, to this day, the scope on agenda-setting research has mainly focused on political communication (e.g. Carrol and McCombs, 2003; Meijer & Kleinnijenhuis, 2006a; McCombs et al., 2014). McCombs et al. (2014) therefore suggest that agenda-setting research should reach beyond the domain of public affairs and go into the domain of public relationship. This research tries to use the agenda-setting literature from the public relationship perspective, with the main focus on the Dutch financial sector for reasons argued above.

The agenda-setting theory was first introduced to the academic world by McCombs and Shaw (1972). Their study on presidential campaign in Chapel Hill shifted the focus of academics onto the salience of issue news. Hereafter, the theory attracted more and more attention among scholars, being replicated in hundreds of studies in multiple countries around the world (McCombs, 2005). A review of 112 empirical studies on the agenda-setting effect by Dearing and Rogers (1996) concluded that about 60 percent of all studies reviewed were able to find evidence for an agenda-setting effect, supporting the idea that the agenda-setting effect is a relevant and useful theory to explain the transfer of salience between the media agenda and the public agenda. The basic agenda-setting theory developed ever since the first appearance in the Chapel Hill study (McCombs, Shaw & Weaver, 2014). New developments in the agenda-setting research focusses on the psychological mechanisms that explain the agenda-setting effects (e.g. the need for orientation) (Matthes, 2008), the consequences of the agenda-setting effects, the origins of the media agenda, and agenda melding, which is the manner in which people converge the civic agendas of the media and our personal views and experience to create a gratifying worldview (Ragas and Roberts, 2009). The agenda-setting

effects today are differentiated in three different levels. The first level is the transmission of the salience of the issue agenda of the media to the issue agenda of the public (McCombs & Shaw, 1972). The second level of agenda-settings refers to the transmission of salience of attributes appointed to certain objects in the media agenda to the public agenda (McCombs et al., 1997). Lastly, the third level of agenda-setting, also called the networked agenda-setting, suggest that the news media create bundles of objects and attributes, which simultaneously become salient in the public’s agenda. Certain objects and attributes which have strong connections in the news media are both more salient when one or the other is mentioned in the public’s agenda. For instance when news media mentioned the economic crisis often in combination with bankers, the audiences are more prone to have an association between these concepts (Guo & McCombs, 2012).

According to McCombs and Weaver (1973) the main psychological mechanism that can explain the first level of agenda-setting effects is the need for orientation. The need for orientation concerns two elements, the relevance that one gives to a certain topic and the amount of uncertainty one endures when thinking about a certain topic. The two elements do not equally make up the level need for orientation. For instance, in a study done by Camaj (2014) showed that people with a low level of relevance and with a high level of uncertainty produces a different level of need for orientation then with a high level of relevance and low level of uncertainty. In his study, Camaj identifies four distinct levels of need for orientation; a low level (low relevance and low uncertainty), a so-called moderate-active level (high relevance and low uncertainty), a moderate-passive level (low relevance and high uncertainty), and a high level (high relevance and high uncertainty). Subsequently, the moderate-active has stronger agenda-setting effects than the moderate-passive and also the high level of NFO. This difference is related to the fact that people who have a moderate- active level of NFO make use of more horizontal (partisan, or biased) media than the people with other levels of NFO. Furthermore, McCombs and Stroud (2014) conclude that when looking at agenda-setting effects, it is not only the level of need for orientation that is important, but also the preferred media (horizontal vs. vertical media) and the level of agenda- setting that is being researched. McCombs and Stroud (2014) speculate that people who use more horizontal/niche media are more likely to be affected by first and second level agenda- setting effects, because they are more accuracy driven. On the other hand, people who use vertical/mainstream media are more affected by the first level agenda-setting and not by the

second level of agenda-setting because they are more direction driven. Social media users fall under the category horizontal/niche media users.

Social media and agenda-setting

There is an ongoing discussion among scholars on how to measure public opinion in the internet age (e.g. Freeman & Berger, 2011; Vargo, 2011). Due to the shift from the mass media to post-mass media era, several scholars claim that new innovative forms of research are needed (Freeman & Berger, 2011; McCombs & Stroud, 2014). The “older” vertical media set the rules to limited access of general information, and agenda-setting is therefore naturally more evident. In the realm of the “new” horizontal media, like social media, the access to information is more open and the people can choose wherefrom they get their information based on their own interest. One suggestion is the use of twitter as a subject of public opinion research. Jansen et al. (2009) ague that Twitter can be seen as a microblogging platform that is aimed to influence where people talk about worldwide. This research also showed that the microblogging is an important part of the branding of organizations. Approximately 20 percent of all microblogs included in the research contained a mention of a brand, and therefore can play an important part in the electronic word of mouth communication of organizations. Furthermore, Twitter coordinates the circulation of information between different online platforms (Vargo, 2011). O’Connor et al. (2010) suggest that, although online public opinion and Tweets are not the same, nonetheless it approximates the online public opinion closely. Accordingly, several studies on agenda-setting theory have already used Twitter to investigate the public opinion online (Ceron, 2014; Russell Neuman, 2011; Vargo, 2011), suggesting Twitter is an appropriate subject to research and use as a measure of online public opinion.

There is a growing interest among scholars in the influence of social media with respect to agenda-setting (Russell Neuman et al., 2014; Camaj, 2014). Mainly, because it opens up different possibilities to effectively measure and analyze the dyadic relationship between social media and traditional media. Previous agenda-setting research most of the time used as a starting point the Gallup Poll’s MIP question: “What is the most important problem facing this country today?” (McCombs et al., 2014). Nowadays, because of the possibility to use online data, it has become easier to access to both types of agendas (traditional media agenda and social media agenda). Researchers are able to get extensive

amounts of data in short amount of time over any period of time they want. This makes it easier to use different and innovative methods for research, e.g. time-series analysis (Russell Neuman et al., 2014). Moreover, the use of big bulks of data taken from the internet and used for analysis can have opens up other possibilities for researchers. For instance, Scharkow and Vogelgesang (2011) used data from Google insight for search as a measure for the public agenda. They suggested that these kinds of data could potentially forecast even tomorrow’s news by analysing the information seeking behaviour. When using a survey in agenda-setting research to investigate what people find the most important issues of the day, you get a so- called a prioritized agenda. According to Neuman (1990) a prioritized agenda accounts only for 10 % of the public issue agenda, whereas the social media agenda accounts for a much larger part of the public issue agenda. Consequently, social media reveal a much larger part of the civic conversation. However there might be other differences too, since the users of social media construct the social media agenda. As mentioned above, McCombs and Stroud (2014) argue that the social media usage may contribute to the differences in the two agenda’s, as the social media users are more focused on the niche or specific information. McCombs et al. (2014) also argue that there could be other variables apart from news coverage that can explain internet activity. Nonetheless, in prior research these differences are not well researched in aspect of the corporate world, let alone the financial sector. It would be interesting to see if these differences in media agenda’s apply in the financial sector, and in this case the Dutch Financial sector, as well. Therefore a first hypothesis will be formulated as follows:

H1: The social media agenda and the traditional news media agenda differentiate when it comes to the reportage on issues concerning the financial sector.

The rise of social media, because of its widespread diffusion of information, made it possible for their users to influence the agendas of both the media and the public (Camaj, 2014). For example, the former mayor of New York, Micheal Bloomberg, held tweeting citizens accountable for undermining his policy making it hard for him to govern the city. This is in line with the findings of Vargo, McCombs and Shaw (2014), who claim that social media are used by citizens for the commenting, distribution of information and the seeking of information concerning the news of the day. On the other hand, journalists actively use twitter as a tool to get new news stories, especially when there is a crisis situation (Permalee, 2013). These findings show that, although the general idea of agenda-setting is that the media agenda can be pushed on the public agenda, through the use of social media, people can push the

public agenda on towards the media agenda. Or as Meraz (2011) puts it, there is a flow in both directions.

Agenda-setting is an excellent framework to analyze a combination of different agendas and to get an insight in the direction in which these flows go (Soroka, 2002). Several studies tried to find evidence of these two-way flow of influence between the media agenda and the social media agenda using the agenda-setting theory. Another study by Vargo (2011) looked at the bilateral influence between the new and the old media, showing that there is a transfer of salience from news media to social media. However, failed to find a transfer of salience from the social media agenda onto the news media agenda. This is in line with the findings of Ceron (2014), who looked at the agenda-setting effects in the relation between online news media agenda and social media agenda on twitter. Ceron concludes that on the first level of agenda-setting, online news media set the agenda of the social media, and not the other way around.

In contrast to these finding, other studies did find evidence supporting the hypothesis of the agenda-setting by the social media, and in particular blogs. Woodly (2008) found evidence that blogs set the agenda for political elites like journalists and politicians. These findings were in line with Permalee (2013) who added that political tweets too play a role in the building of agendas. Kim and Lee (2006) proposed a three-step mechanism that explained agenda building through the internet. First an opinion about a certain topic or issue is formed by the anonymous internet users, which cultivates and spreads to an important agenda on the internet through important online channels such as blogs, social networks, and internet bulletin boards. Second, when news media pick up the issue presented in these channels the opinion spreads to other and much wider online audience. Thirdly, the traditional media then picks up the information and the issue is dissimilated as well online as offline. Nonetheless, the evidence for the agenda-setting effect of the social media is still scarce and most often conflicting. An extensive study by Russel Neuman et al. (2014) on the attention on 29 different issues among traditional news media (i.e. print and broadcast), Twitter users, blogs, forums, found a complex reciprocal interplay between the traditional media and the social media. Where sometimes the traditional media leads the social media, other times the social media leads the traditional media. Which media agenda influenced the other was dependent on the issue that was being investigated. For instance with social issues like birth control, abortion and same-sex marriages, social media were most often leading, while other issues like economic policy and government functioning the traditional media were most often

leading. They concluded that the traditional media and the social media do influence each other’s agenda, however the influence traditional media and social media have on each other do not have a one-directional pattern, but is rather complex and dynamic. These findings show that, although it is difficult to forecast the direction, it can be expected that both media agendas can have an influence on each other from day-to-day. Therefore the following hypothesis is formulated:

H2: If individual issues about the financial banking sector are frequently covered on social media, then those issues also are frequently covered in the traditional newspapers on the same day.

As mentioned above, when looking at the agenda-setting effects between traditional media and social media, the characteristic of an issue may play an important role. One characteristic that has shown to be of interest among agenda-setting theorists is the obtrusiveness of an issue. Obtrusiveness first appeared in literature in the 1970’s as one of the several factors that could explain that the news covering of issues were likely to have a stronger agenda-setting effect than the others (Demers et al., 1989). Earlier research defined issues as unemployment, cost of living and energy as obtrusive issues and international problems and dissatisfaction with government as unobtrusive (Demers et al., 1989). These examples are obviously related to political communication research and are not necessarily related to corporate communication research. Most studies that investigated a moderation on agenda-setting effects have failed to prove it (Winter, 1981). Nonetheless, there are some questions from scholars about the relationship between agenda-setting effects and obtrusiveness; therefore obtrusiveness is still part of contemporary agenda-setting research (Cha et al., 2015; Lischka, 2015). Vargo (2011) suggest that real-world cues could mediate the bilateral relationship between mass media and twitter. A study done by Soroka (2002) looked at the dynamics between the public agenda and the news media agenda. For this they used Zucker’s (1978) obtrusiveness hypothesis, which says that the influence of the media is dependent on the chance that the public experience the issues covered by the media directly. The results showed that the public is quicker to react to real-world conditions than traditional media. Twitter can be seen as a platform where the public can give their opinion (Vargo, 2011). It can be expected that the average issue obtrusiveness is higher on Twitter than it is in Traditional newspapers. It would be interesting to see whether this also accounts for corporate issues, and more specifically for the financial/banking sector. For this the following hypotheses are formulated:

H3: The average score on issue obtrusiveness on the issues represented in the social media are higher than the average score on issue obtrusiveness on the issues represented in the traditional news media.

Founded on the theoretical framework a schematic representation has been constructed, which is presented below:

Issue obtrusiveness

+ H3 -

@ @ @ Social media issue + News media issue @ agenda H2 agenda

Method

Selection of the research units

To measure the salience of issues and issue obtrusiveness in traditional news, Dutch newspapers are chosen as the unit of research. Newspapers generally have a stronger influence on the awareness of news issues than other media and are therefore used often in Agenda-setting research (Culbertson et al., 1994) Dutch newspapers are suitable to use to research agenda-setting effects as a large percentage of the circulation is subscription-based (Bakker & Scholten, 2003 in Meijer & Kleinnijenhuis, 2006b). Besides, the corporations included in this research are Dutch-based so therefore Dutch newspapers would be the obvious choice.

Following prior research (Ceron, 2014; Russell Neuman, 2011; Vargo, 2011) twitter was chosen as a unit of research to measure the issue coverage on social media. As mentioned above, twitter controls the circulation of information between different online platforms (Vargo, 2011) and Twitter can be seen as a microblogging platform what is aimed to influence where people talk about worldwide (Jansen et al., 2009).

The selection of corporations included in this study is chosen following a study of Meijer and Kleinnijenhuis (2006b). In their study, they looked at several different industries (e.g. the oil industry, the banking industry, the transport industry etc.). Then, per industry they then selected two cases (e.g. Shell and British petroleum for the oil industry). Considering this study focuses solely on the financial sector, only the corporations of the financial industry from the Meyer and Kleinnijenhuis (2006b) will be used. Hence, this research will focus on the salience of issues on social media and in traditional media concerning four different corporations grouped in two financial corporations. The corporations included in the study are therefore ABN-AMBRO bank and Rabobank.

Design

Ensuing the Acapulco typology (McCombs, 2014 in McCombs et al., 2014) there are four types of research designs used to test agenda-setting theory nowadays. The first type is comparing the salience of issues in news media to the salience of issues of the public agenda, for instance using the Gallop polls mentioned above. The second type of research design is the same as the first, but focusses on the agenda of the individual rather than the sum of all agendas. The third and the fourth type of agenda-setting research are focusing on the salience of individual issues over time, whereby type four uses a controlled experimental setup and type three is not. This research will have a slightly different approach. By comparing the salience in of issues in the social media agenda as a measurement of public opinion with the salience of issues in the traditional media, and focusing on individual issues over time, this research will make combine both the first and the third type of agenda-setting research. To do so, this research will use a quantitative content analysis to investigate issue coverage concerning the Dutch financial sector on both media. A content analysis is a “research technique for the objective, systematic, and quantitative description of the manifest content of communication.” (Berelson, 1952: 18) and therefore is best fit to compare social media and traditional newspaper content. To test the hypotheses, the salience of corporate issues on social media (social media agenda) versus the salience of issues in the traditional news media shall be compared to assess the agenda-setting flows go from the one and the other, or the other way around. Furthermore, the type of issues (obstructive vs. non-obstructive) and the issue attributes will be measured from the collected data.

Operationalization of the variables

Issue coverage. Following the research of Ceron (2014) and Vargo (2014), issue coverage is operationalized as the frequency of issues covered in tweets and in newspapers. This research incorporates issues that are more closely related to the corporations involved (i.e. the “Rabobank” and the “ABN-AMRO”). Meijer (2004) divided several important issues that can be attributed to all corporation, albeit in different ways, into categories. These categories entail the performance based issues (investments, profits, product quality), economic issues (world economy, price of currency and employment), mergers, image and finally issues that incorporate the social responsibility of corporations like environment, energy consumption, wages and inflation.

Issue Obtrusiveness. The operationalization of issue obtrusiveness has always been a point of discussion. For example, on the evaluation of the issue crime. Zucker (1978) argues that crime is an obtrusive issue, while Weaver, Graber, McCombs, and Eyal evaluate it as an unobtrusive issue (in Demers et al., 1981). A few studies have tried to operationalize this variable, however most of those studies were surveys (e.g. Cha Su and Kim, 2015). Making the operationalization of the obtrusiveness variable inappropriate for content analysis. Other studies used real world indices as a measurement for obtrusiveness (e.g. Ju, 2014). However the world indices are too broad for this research, which focusses specifically on the Dutch financial market. No other reliable measurement for issue obtrusiveness which can be used in this research was found. Therefore a new measurement tool for the variable issue obtrusiveness is constructed from the definitions taken from prior research. The most common definition used for obtrusiveness is the amount of personal experience one can have with certain issues (Winter, 1981; Demers et al., 1989, Cha et al., 2015). Or as Lischka (2015) puts it, an obtrusive issue is an issue that people experience personally and something that relates to their daily lives. According to Demers et al. (1989), there are two aspects which are important to keep in mind when defining issue obtrusiveness. First of all, issue obtrusiveness should not be operationalized as how important an issue is to people. Sometimes obtrusiveness is mistaken for issue salience, however obtrusiveness is solely based on real world personal experiences of people not on what issues are important to them at the moment. For instance some people find important, but most of them don’t have personal experiences with them. Secondly, obtrusive issues are issues where people have direct personal experience with and not indirect, talking about it in interpersonal relationship or only in the media. Based on this definition a question is formulated which shall be used to measure obtrusiveness (i.e. To what extend does the public have a personal day-to-day experience with

this issue?). According to Demers et al. (1989) there is not a clear distinction between which issues are obtrusive and which issues are not, instead the difference between obtrusive and non-obtrusive issues appears to be a continuum. Thus, to answer the question formulated above, the coder has to fill in a 7-point likert scale (ranging from, 1. No personal experience, up to 7. A lot of experience)

Data collection

There are two datasets that are being used for the quantitative content analysis with time-series, Twitter data and traditional newspaper articles. The tweets were derived from public Twitter accounts through Twitter’s API for developers. Herein search queries were applied to select only tweets referring to the corporations included in this research (i.e. ABN- AMRO and Rabobank). These keywords for the search queries included the names of the selected corporations. The collected data entailed a time period of 15 days, namely from the 29th of June 2016, till the 13th of July 2016. Because of the restriction of Twitter to access only the twitter data as far as 8 days prior to the collection day, the data was collected at two points in time. Graphics, video, or audio, were not included in the data, only text was included. Hyperlinks within the twitter data was also not used for this research. In total, 2085 tweets were collected for the purpose of this research.

For the second dataset, the news articles were depicted from the biggest Dutch daily national newspapers, “De Telegraaf”, “De Volkskrant”, “Het Financieel Dagblad” “Het Parool”, “Metro”, “NRC”, “Trouw” and “NRC-next”. These newspapers were not only selected because they are the newspapers with the highest circulation in the Netherlands (Nationaal Onderzoek Multimedia, 2016), but also because they include both tabloid and quality newspapers which cover a wider spectrum of opinion and a wider array of issues (Esser, 1999). The news articles relevant to the corporations included in this research were then retrieved from the online newspaper data bank Lexis Nexis, using keywords corresponding to the names of the corporations included in the research. An advance search was conducted to obtain the data from the relevant time period (from the 29th of June 2016, till the 13th of July 2016) and from the selected newspapers. A total of 276 newspaper articles were collected for the purpose of this research.

Coding procedure

After the data collection the total sample contained 2361 items. To transform the raw collected data into analyzable bits, a codebook was drafted to ensure the measurements of the data were conducted in a reliable, coherent and clear-cut matter. For this research one coder analyzed all of the data collected through the use of this codebook. The codebook consisted of several questions compliant with the variables needed to answer the hypotheses. First the coder wrote down on which day and month the news article or tweet was published. Secondly the coder coded the unit of analysis, newspaper or twitter, and the company involved in the news article or tweet. Thirdly the coder needed to read and analyze the text to check which issue was discussed in the news article or tweet. The coder used a list which was compiled accordingly the issue used in the study of Meyer and Kleinnijenhuis (2006b). This list contained twelve generic issues that could be attributed to all of the industries included in the study of Meyer and Kleinnijenhuis (2006b). Examples of the issues in this list are investments, profits, product quality, and world economy etc. However, because this research concentrates on the banking sector and the some of the issues concerning the financial sector are more specified to the banks themselves, an extra option (namely “other issue”) is added where the coder could fill in a description of the issue at hand that best seems fit. Furthermore, another option is put in (namely “not applicable”) for when the text did not incorporate an issue. Lastly, the coder had to measure the obtrusiveness of an issue. Because there is no measurement for obtrusiveness in prior research using a content analysis, the coder needed to answer a question based on the operational definition mentioned above (this question is as follows: “To what extend does the public have a personal day-to-day experience with this issue?”). Because (Demers et al., 1989) argued that issue obtrusiveness can be seen as a continuum rather than opposites a 7-point Liker-scale is used (ranging from “No personal experience” to “A lot of personal experience”)

Coder reliability

To check whether the coder measured the concepts he set out to measure, an intercoder reliability test was conducted. For this test, a small sample of five percent of the total sample (consisting of 15 newspapers and 100 tweets) was coded by another individual, who was not involved in the research process beforehand. A Krippendorf’s Alpha then was used to test the reliability of the used concepts, this was calculated through the use of an online tool called Recal2 (http://dfreelon.org/utils/recalfront/recal2/). The first concept;

corporate issue’s, had a sufficient reliability score (Krippendorf’s Alpha 0.729), and therefore the variable could be used for further analysis. Unfortunately, the obtrusiveness variable did not meet the requirements for a reliable measurement (Krippendorf’s Alpha 0.440). There are two reasons; first the general ambiguity of the concept obtrusiveness is somewhat problematic to create a univocal measurement (see Demers et al., 1989). Secondly, the high level of abstraction this variable has makes it difficult for an untrained coder to comprehend at first glance. Although the Krippendorf’s Alpha of the obtrusiveness variable was below requirements, this variable will still be used for analysis given the limited timespan to conduct the research. The implications of this failed reliability test will be further discussed in the conclusion and discussion section.

Analysis

Before analyzing the coded material, the dataset was checked for missing values and all values were labeled. Then all of the items that scored not applicable (n = 242) on the issue variable were excluded from the analysis, to ensure that the analyzable material was solely issue news. All of the data cleaning, handling and analyses is done with the statistical software SPSS. For the analysis, first a univariate analysis was conducted to give a description of the final sample and of all of the variables involved. Next the hypotheses were tested through a multivariate analysis. First a Pearson’s chi-square test was conducted to test the differences in media agendas. Then an independent sample t-test was performed to compare the average scores of issue obtrusiveness of the different media. Finally three individual cases with the largest sample size were selected in SPSS. To compare the frequencies of covered issues per day, a Pearson’s chi-square test was used on all three individual issues. Furthermore to further explore the individual issues, a graph of the percentage of coverage per medium per day was made for each individual issue. These graphs were then checked for anomalies and described.

Results

The final sample (N = 2019) included 1871 Tweets and 248 newspaper articles divided over the two corporations (“Rabobank” and “ABN AMRO”). The “Rabobank” consists of 1685 tweets and 114 newspaper articles, which accounts for 84,9 % of all items and the “ABN AMRO” accounts for 184 Tweets and 134 Newspaper articles, which accounts for 15.1 percent of all items. 20.9 % of the issues concerned product quality (n = 443), 20.1 % concerned world economy (n = 425), 14.5% concerned investments (n = 308), 5.4 %

concerned the image of the corporation (n = 114), 3.8 % concerned profits (n = 80). Furthermore, 29.2 % of the issues concerned issues other than the issues included in the list of issues composed from the Meyer and Kleinnijenhuis (2006b) study. “Other issues” concerned the Libor scandal (n = 369), which accounted for 17.1 percent of the total issues, and 8.8 % of the issues involved Brexit (n = 186). The remaining issues accounted for less than 9.5 % (e.g. mergers, price of currency employment sport etc.). See figure 1 for more information about the issues represented in all of the items. The overall issue obtrusiveness of the coded items had an average score of 5.30 with a standard deviation of 2.02.

25,0

20,0

15,0

10,0

5,0 percentage percentage coverage of onIssue an

0,0

Issues

Figure 1. Percentage of issues covered in both Tweets and traditional newspaper. The percentage is based on the total coverage of issues during the research period.

First, a Chi-square analysis is used to analyze whether the coverage on news issues on twitter and in the newspaper articles overall differed, whereby the independent variable is the media agenda and the dependent variable is the issue coverage. The percentage of issues covered in the traditional news media did not differentiate statistically from the percentage of issues covered in the social media agenda, χ2 (12, N = 2119) = 137.6, p < .001. This means

that the overall coverage on the various issues measured are statistically the same on Twitter and in newspapers.

Secondly, the individual issues will be analysed to investigate whether the frequency of reportage on the single issues is relatively similarly on social media and traditional news media. To ensure that the explanatory power of the statistical analyses used are sufficient, the top three individual issues that have the largest sample per medium appeared in the dataset are selected. These issues are the following: the issue of investment (n = 308), the issue of product quality (n = 443), the issue of world trade (n = 425). The “Libor” issue scored higher on the overall coverage in both media then the investment issue. Nonetheless, the distribution of coverage over the two media was better for the investment issue because the “Libor” issue only was covered eight times in the newspaper over the entire research period. Because this would make it difficult to do a test with, the investment issue is chosen.

For the first issue, investments, a Chi-square is conducted to analyse whether the daily coverage on the investment issue on Twitter is positively related to the daily coverage on the investment issue in traditional newspaper articles. In other words if the investment issue count is high on Twitter, then the investment issue count is also high in Traditional newspaper articles on the same day. The percentage of the investment issue covered in the traditional news media per day did differentiate statistically from the percentage of the investment issue covered in the social media agenda per day, χ 2 (13, N = 308) = 83.0, p < .001. In other words, the percentages of the daily coverage on the investment issue did differ by medium.

To investigate the investment issue reportage a little more in depth, a graph is composed which represents the relative reportage on the specific issue per medium (Twitter or traditional newspaper), which is presented and be discussed below (see figure 2).

Twitter (n = 275) 30

Traditional newspaper 20 (n = 33)

10 Percentage Percentage of issue totalcoverage

Date

Figure 2. Percentages of the total investment issue coverage per day on Twitter versus traditional newspapers over the entire research period (from 29-6-2016 till 13-7-2016). The percentage is based on the total amount of issue coverage per medium during the research period.

There are few similarities and differences that can be identified in the graph. On the third day of the research period (i.e. the first of July 2016) the twitter data shows a large peak (54.5 % of the total issue coverage) in the coverage on the investment issue. Interestingly, when looking at the coverage on the investment issue in the traditional newspaper in the same period, a smaller but similar peak (18.2 % of the total issue coverage) in the percentage of investment issue news coverage arises. However, this peak lags one day behind on the investment issue coverage peak on Twitter. Going back to the raw data, both peaks are triggered by the same event (namely an investment made by Daimler in Athlon, an auto lease company owned by the Rabobank). This difference in the day in which the news coverage peaks indicates that the attention on the issue in twitter is leading the attention on the issue in traditional newspapers. Notable is that the peak in twitter data is much higher than the peak in the traditional newspaper data. This can be explained by the other peak in the coverage of the investment issue in the newspaper articles at the end of the research period. Looking back at the raw data, the event that triggered this second peak in the data concerns a personal loan by a Dutch individual. The fact that it concerns a Dutch individual could explain this difference

in coverage between media types. Dutch Daily newspapers are more prone to report on national news while the Twitter community is more internationally orientated.

The second issue that will be analysed is the product quality issue. To check whether the daily coverage on the product quality issue on Twitter is positively related to the daily coverage on the investment issue in traditional newspaper articles, a Chi-square test is conducted. In other words, if the product quality issue count is high on Twitter, then the product quality issue count is also high in Traditional newspaper articles on the same day. The percentage of the product quality issue covered in the traditional news media per day did differentiate statistically from the percentage of the product quality issue covered in the social media agenda per day, χ 2 (1, N = 308) = 83.0, p < .001. This leads to the conclusion that the percentages of the daily coverage on the product quality issue did differ by medium.

Similar to the first issue, a graph is composed to give a more in-depth analysis of the dynamics between the two media agendas. This graph represents the relative reportage on the issue per medium (Twitter or traditional newspaper), which is presented and be discussed below (see figure 3).

20 Twitter (n = 348)

Traditional 10 newspaper (n = 95)

5 Percentage Percentage of issue total coverage

Date

Figure 3. Percentages of the total product quality issue coverage per day on Twitter versus traditional newspapers over the entire research period (29-6-2016 to 13-7-2016). The percentages are based on the total of issue coverage per medium during the research period.

A few anomalies emerge when looking at the graph portrayed above. On the sixth day of the research period (4-7-2016) there is a peak in the coverage on the product quality issue on the Twitter (25% of the total issue coverage), then two days after (6-7-2016) there is a large peak in the coverage on the product quality issue in the traditional newspapers. However, when looking at the raw data, these peaks appear to be irrelated. Because the spike in coverage on twitter concerns primarily the development of a new banking technology for better service, while the spike in coverage in traditional newspapers concerns the bad quality of an financial product. Another anomaly that will be discussed is the smaller peak (10% of the total coverage) in the coverage of the product quality issue on Twitter on the ninth day of the research period (7-7-2016). This peak is similar to the peak in the coverage on the product quality in the newspapers one day later. The raw data showed that this upswing in both the Twitter and the newspapers coverage primarily concerned the same cause, namely the bad quality of a service. This suggests that the increase in attention on the product quality issue on twitter leads the increase in attention about the same issue in the newspaper by one day.

The third issue that will be discussed is the world economy issue. A Chi-square test is used, to investigate that when the world economy issue count is relatively high on Twitter, then the world economy issue count is also high in Traditional newspaper articles on the same day. The percentage of the world economy issue covered in the traditional news media per day did differentiate statistically from the percentage of the world economy issue covered in the social media agenda per day, χ2 (14, N = 425) = 40.0, p < .001. In other words, the percentages of the daily coverage on the world economy issue did differ by medium.

Similar prior issues discussed, a graph is composed to give a more in-depth analysis of the dynamics between the two media agendas. This graph represents the relative reportage on the issue per medium (Twitter or traditional newspaper), which is presented and to be discussed below (see figure 4).

20 Twitter (n = 402) 15

Traditional newspaper 10 (n = 23)

5 Percentage Percentage of issue totalcoverage

Date

Figure 4. Percentage of the world economy issue coverage per day on Twitter versus traditional newspapers over the entire research period (29-6-2016 to 13-7-2016). The percentages are based on the total of issue coverage per medium during the research period.

In the graph presented above, there are few anomalies that stand out. At the end of the research period (12-7-2016) there is a spike in both Twitter and the newspaper coverage on the world economy issues. This suggests that the media agenda’s issue salience could thrive

each other in terms of issues concerning world economy. Contrary to this a peak in issue coverage on twitter on the eight day of the research period (6-7-2016) is followed by a peak in the issue coverage in the newspapers. This might indicate that the increase of coverage of the world economy issue on twitter could imply an increase of coverage in news the next day.

Lastly, an independent sample t-test is conducted to check whether the average score on issue obtrusiveness is statistically higher in tweets pertaining to the score in traditional newspapers. To do so, one compares the average score of issue obtrusiveness on Twitter (M = 5.31, SD = 2.02) to the average score on traditional news media (M= 5.25, SD = 2015). The independent sample t-test indicated that the difference between the average score of issue obtrusiveness on Twitter and traditional news media is not statistically significant, t (2117) = 0.403, p = .687 CI [-.213, .323]. This means the null-hypothesis is accepted, and that issue obtrusiveness would not be statistically more apparent on Twitter then on traditional news media. Unlike the hypothesis suggests, there is no statistical difference found in the average scores on obtrusiveness between Twitter and traditional news media.

Conclusion

The central aim of this study is to investigate the differences of the social media agenda and the traditional news media agenda in terms of corporate issues in the financial sector. By comparing the salience of issues on both media agenda this research conducted a chi-square analysis. Furthermore, a more focused analysis was performed on individual issues to analyze whether the coverage on Twitter and traditional newspapers would correlate. Lastly, through the use of an independent sample t-test, this research compared the average scores of issue obtrusiveness to investigate whether the social media agenda is more obtrusive than the traditional news media agenda in the reportage on the financial sector. With this, this research tries to give insight into the research question: Do the social media agenda and the traditional media influence each other concerning the news coverage on issues regarding the Dutch financial sector?

The results of this study show that the salience of issues in the social media agenda significantly differs from the salience of issues in the traditional news media in terms of reportage on the financial sector. When covering issues concerning the financial sector, the social media agenda has emphasis on different issues then the traditional news media. This means that the agenda-setting effect in coverage on the Dutch financial sector over the issues

incorporated in this research is not confirmed. These findings are in line with the suggestion made by McCombs and Shaw (2014), who argue that due to the social media usage there could be differences between the social media agenda and traditional media agenda in terms of issue coverage, as the social media users are more focused on the niche or specific information. Thus, the results confirm that attention towards issues in the social media agenda and the traditional news media agenda differ, when it comes to the reportage on issues concerning the Dutch financial industry.

When focusing on individual issues this research showed mixed results. First, the results show that the coverage on a daily basis of the individual issues is differing significantly between the social media and the traditional news media. This indicates that the amount of coverage on a single issue on twitter on a certain day is not related to the amount of news coverage in traditional newspapers on the same day. Thus, a high level attention towards a single issue on the social media followed a high level of attention towards a single issue on the traditional news media on the same day cannot be expected. Although the social media and the traditional news media do not influence each other in an immediate fashion, this does not rule out the possibility that there is not a delayed effect. The exploration of the graphs in the result section indicated that sometimes the social media attention on a certain issue concerning the financial sector can have a delayed influence of one day on the attention of the same issue in traditional newspapers. This might indicate that the amount of coverage on a certain issue on twitter influences the amount of coverage on the same issue in traditional news media the next day, which is in line with the findings of Woodly (2008) and Permalee (2013). Another explanation for this could be the fact that the traditional newspaper need time to be made. Although there is no significant result that shows there is an influence of the social media on the traditional news media or vice versa, there are still some indications that in some cases there can be an influence, but the extent of the influence and the direction are not to foretell. As Russel Neuman et al. (2014) point out, the interplay between traditional media and social media does not have a one-directional pattern but is rather complex and dynamic.

In contrast to what was expected, the issue obtrusiveness variable showed no differences between the issues covered on social media and the issues reported on in the Traditional news media. This means that the average issue obtrusiveness in issues that are discussed on social media is not significantly higher than the average issue obtrusiveness in issues that are reported on in the traditional news media.

To conclude, following the results of this research, agenda-setting effects between the social media agenda and the traditional media agenda concerning the Dutch financial sector is not confirmed by the results of this research. The difference in salience show that the media agendas differ on the overall coverage of issues concerning the Dutch financial sector, making agenda-setting effects between the social media agenda and the traditional media agenda highly unlikely. The other results did not show conclusive evidence for agenda-setting effects between the social media agenda and the traditional media as well. There are some indications that the social media influences the traditional media in terms of reportage on the Dutch financial sector. However further research is needed to confirm these indications.

Discussion

There are several implications for this research, which will be discussed. First, the measurement of the variable issue obtrusiveness. As mentioned earlier, a clear and conclusive issue obtrusiveness measurement has always been a topic for discussion amongst scholars. An example of this is the evaluation of the issue crime. Zucker (1978) argues that crime is an obtrusive issue, while Weaver, Graber, McCombs, and Eyal evaluate it as an unobtrusive issue (in Demers et al., 1981). Due to its abstract and ambiguous nature, making a concise reliable definition and/or measurement is therefore problematic. Furthermore this study was not able to use a prior developed measurement tool for this variable, and therefore a new measurement had to be constructed, derived from definitions taken from prior research. Unfortunately, after calculating the intercoder reliability, the Krippendorf’s Alpha was too low for the measurement to be reliable. This means that it is unsure if the coder measured what he set out to measure. Given the limited timespan for this research, the measurement of issue obtrusiveness is used in an explorative manner. Consequently, the results concerning this variable are not reliable. For further research using content analysis it is recommendable to develop a reliable and concise measurement tool for issue obtrusiveness.

The second limitation of this research was the use of the issue list from the Meyer (2004) study. Meyer used a particular method, called the NET-method, to do a semantic evaluation of all of the content they collected. With this they made an extensive list of all the issues found in their research material, of which they only put in a few in their research paper. Due to the limited resources available for this research, therefore is chosen only to use this list with an option for the coder to put in an “other variable”. This list of issues was somewhat

generic and was attributed to all types of industries (e.g. the transport industry, the food industry etc.). Although these issues were overall pretty exhaustive and also partially applicable to the financial sector, for this research a list of issues specified to the financial sector would have had preference. Especially for the analysis of the individual issues, some of the issues from the list entailed many different issues at once and therefore could influence the outcomes. For example the World economy issue was perhaps too ambiguous, incorporating a whole lot of different events and topics.

The third limitation of this research was the choice of using the traditional newspapers as a unit of analysis, and putting them next to the social media as a second unit of analysis. Traditional newspapers are most often published one day after the news occurs, this makes it inconsistent with the fast dispersion of information on Twitter. Furthermore only one Newspaper used in the content analysis have a Saturday and a Sunday edition, most newspapers used for this research have only one of both edition (e.g. the “Volkskrant” and the “NRC” have only a Saturday edition). This gives a distorted view when put against the continuous flow of tweets on the internet. An alternative that can be proposed for further research be the digital newspaper, because the digital newspaper’s publication date is more parallel to the publication of Tweets.

The fourth limitation of this research was the decision to focus solely on the Dutch national newspapers. The downfall when researching the news coverage on international renowned businesses as the “Rabobank” and the “ABN-AMRO”, is the emphasis of the newspapers on the national news. Considering proximity is an important news value for journalist to pick up issues to write about (Bell, 1991). Because Twitter is an online platform where people from all over the world can contribute, the salience of issue coverage is logically more international orientated on companies with a worldwide outreach, like “Rabobank” and to a lesser extent “ABN-AMRO”. For further research it is therefore recommendable that the companies involved are bound to a national scale, or the newspapers used are more internationally orientated.

The fifth limitation is the 140 character limit imposed by Twitter on its users. This limit in the amount of characters used obviously limits the user’s ability to express himself. For example, a lot of the raw data that was collected contained links or very specific hashtag (e.g. #datahub). This made it difficult to see which issue was involved. This limitation is soon

to be resolved, as Twitter announced the 140 character limit will be adapted to a 10000 character limit which enhances the user’s ability to express himself (Leijten, 2016).

Lastly, a suggestion for further research is to use time-analysis to investigate the bilateral influence of the social media agenda versus the traditional news media agenda on individual issues. A granger, ARIMA or lead-lag analysis would be more suitable to capture the dynamics of the Agenda-setting effects between the two media (Ceron, 2014). Moreover, to conduct a time-analysis for a longer research period then the research period of this study is recommended. For example an ARIMA time-series model requires to have at least 30 to 40 data point to be significant (Sayre et al. 2010, in Vargo, 2010).

References

Bell, A. (1991). The language of news media (pp. 84-85). Oxford: Blackwell.

Berelson, B. (1952). Content analysis in communication research. Free Press, New York

Bollen, J., Mao, H., & Zeng, X. (2011). Twitter mood predicts the stock market. Journal of Computational Science, 2(1), 1-8.

Camaj, L. (2014). Need for orientation, selective exposure and attribute agenda-setting effects. Mass Communication and Society, 17, 689–712.’

Cameron, G. T. (1994). Does publicity outperform advertising? An experimental test of the third-party endorsement. Journal of Public Relations Research, 6(3), 185-207.

Carroll, C. E., & McCombs, M. (2003). Agenda-setting effects of business news on the public's images and opinions about major corporations. Corporate reputation review, 6(1), 36-46.

Castells, M. (2009). Communication Power. Oxford University Press: Oxford

Cha, H., Suh, J. W., & Kim, J. R. (2015). The effect of issue obtrusiveness, issue congruence, and response strategies on the acceptance of crisis communication messages. Asian Journal of Communication, 25(3), 307-326.

Chakravartty, P., & Schiller, D. (2011). Global Financial Crisis| Neoliberal Newspeak and Digital Capitalism in Crisis. International Journal of Communication, 4, 23.

Ceron, A. (2014). Twitter and the traditional media: Who is the real agenda setter?. In APSA 2014 Annual Meeting Paper.

Cohen, B. C. (1963). The press, the public and foreign policy. Reader in Public Opinion and Communication, 134-35.

Cook, F. L., Tyler, T. R., Goetz, E. G., Gordon, M. T., Protess, D., Leff, D. R., & Molotch, H. L. (1983). Media and agenda-setting: Effects on the public, interest group leaders, policy makers, and policy. Public Opinion Quarterly, 47(1), 16-35.

Culbertson, H.M., D. Evarts, P.B. Richard, K. Sandell and G.H. Stempel (1994). ‘Media Use, Attention to Mass Media and Agenda Richness’, Newspaper Research Journal 15(1): 14–19.

Dearing, J. W., & Rogers, E. (1996). Agenda-setting (Vol. 6). Sage publications.

Deephouse, D. L. (2000). Media reputation as a strategic resource: An integration of mass communication and resource-based theories. Journal of management, 26(6), 1091-1112.

Demers, D. P., Craff, D., Choi, Y. H., & Pessin, B. M. (1989). Issue obtrusiveness and the agenda-setting effects of national network news. Communication Research, 16(6), 793- 812.

Esser, F. (1999). ‘Tabloidization’ of News: A Comparative Analysis of Anglo- American and German Press Journalism. European Journal of Communication 14(3)

Freeman, M., & Berger, L. (2011). The Issue of Relevance of Agenda-Setting Theory to the Online Community. Meta-communicate, 1(1).

Guo, L., Vu, H. T., & McCombs, M. (2012). An Expanded Perspective on Agenda- Setting Effects. Exploring the third level of agenda setting Una extensión de la perspectiva de los efectos de la Agenda Setting. Explorando. Revista de Comunicación, 11, 51.

Helleiner, E., & Pagliari, S. (2011). The end of an era in international financial regulation? A postcrisis research agenda. International Organization, 65(01), 169-200.

Jansen, B. J., Zhang, M., Sobel, K., & Chowdury, A. (2009). Twitter power: Tweets as electronic word of mouth. Journal of the American society for information science and technology, 60(11), 2169-2188.

Kim, S. T., & Lee, Y. H. (2006). New functions of Internet mediated agenda-setting: Agenda-rippling and reversed agenda-setting. Korean journal of journalism & communication studies, 50(3), 175-205.

Leijten, J. (2016, May 24). Twitter pakt limiet van 140 tekens aan. NRC handelsblad. Retrieved from https://www.nrc.nl/nieuws/2016/05/24/twitter-pakt-limiet-van-140-tekens- aan-a1407041

Lischka, J. A. (2015). What Follows What? Relations between Economic Indicators, Economic Expectations of the Public, and News on the General Economy and Unemployment in Germany, 2002-2011. Journalism & Mass Communication Quarterly, 92(2), 374-398.

Nationaal Onderzoek Multimedia. (2016). Oplage Dagbladen. Retrieved from https://dundas.reports.nl/NOM/Dashboard/Free

Newman, N., Fletcher, R., A. L. Levy, D., & K Nielsen, R. (2016). Reuters Institute Digital News Report 2016. Retrieved from http://po.st/pkDNSZ

Matthes, J. (2008). Need for orientation as a predictor of agenda-setting effects: Causal evidence from a two-wave panel study. International Journal of Public Opinion Research, 20(4), 440-453.

Meijer, M.M. (2004). Does success breed success? Effects of news and advertising on reputation. Amsterdam: Aksant

Meijer, M. M., & Kleinnijenhuis, J. (2006a). Issue news and corporate reputation: Applying the theories of agenda setting and issue ownership in the field of business communication. Journal of Communication, 56(3), 543-559.

Meijer, M. M., & Kleinnijenhuis, J. (2006b). News and corporate reputation: Empirical findings from the Netherlands. Public Relations Review, 32(4), 341-348.

Meraz, S. (2011). The fight for ‘how to think’: Traditional media, social networks, and issue interpretation. Journalism: Theory, Practice, and Criticism, 12, 107–127.

McCombs, M. (2005). A look at agenda setting: Past, present, and future. Journalism Studies, 6(4), 543557.

McCombs, M., Llamas, J. P., Lopez-Escobar, E., & Rey, F. (1997). Candidate images in Spanish elections: Second-level agenda-setting effects. Journalism & Mass Communication Quarterly, 74(4), 703-717.

McCombs, M. E., & Shaw, D. L. (1972). The agenda-setting function of mass media. Public opinion quarterly, 36(2), 176-187.

McCombs, M. E., Shaw, D. L., & Weaver, D. H. (2014). New directions in agenda- setting theory and research. Mass Communication and Society, 17(6), 781-802.

McCombs, M., & Stroud, N. J. (2014). Psychology of agenda-setting effects: Mapping the paths of information processing. Review of Communication Research, 2(1), 68–88.

McCombs, M., & Weaver, D. (1973). Voters' Need for Orientation and Use of Mass Communication.

Meraz, S. (2011b). The fight for ‘how to think’: Traditional media, social networks, and issue interpretation. Journalism: Theory, Practice, and Criticism, 12, 107–127.

Neuman, W. R. (1990). The threshold of public attention. Public Opinion Quarterly, 54(2), 159-176.

O'Connor, B., Balasubramanyan, R., Routledge, B. R., & Smith, N. A. (2010). From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series. ICWSM, 11(122- 129), 1-2.

Parmelee, J. H. (2013) The agenda-building function of political tweets. New Media Society. doi:10.1177/1461444813487955

Sayre, B., Bode, L., Shah, D., Wilcox, D., & Shah, C. (2010). Agenda setting in a digital age: Tracking attention to California Proposition 8 in social media, online news and conventional news. Policy & Internet, 2(2), 7-32.

Scharkow, M., & Vogelgesang, J. (2011). Measuring the Public Agenda using Search Engine Queries, International Journal of Public Opinion Research Vol. 23 No. 1,104-113.

Scheltema, C., Graafsma, L., Koedijk, K., & du Perron, E. (2010). Rapport van de commissie van onderzoek DSB Bank. Onderzoeksrapport, Commissie Scheltema, Den Haag, 1.

Soroka, S. N. (2002). Issue attributes and agenda‐setting by media, the public, and policymakers in Canada. International Journal of Public Opinion Research, 14(3), 264-285.

Ragas, M. W., & Roberts, M. S. (2009). Agenda setting and agenda melding in an age of horizontal and vertical media: A new theoretical lens for virtual brand communities. Journalism & Mass Communication Quarterly, 86(1), 45-64.

Russell Neuman, W., Guggenheim, L., Mo Jang, S., & Bae, S. Y. (2014). The Dynamics of Public Attention: Agenda‐Setting Theory Meets Big Data. Journal of Communication, 64(2), 193-214.

Tetlock, P. C. (2007). Giving content to investor sentiment: The role of media in the stock market. The Journal of Finance, 62(3), 1139-1168.

Vargo, C. (2011). Twitter as Public Salience: An Agenda-Setting Analysis. Paper presented at the annual conference of AEJMC, St. Louis, Mo.

Vargo, C., Guo, L., McCombs, M., & Shaw, D. (2014). Network issue agendas on Twitter during the 2012 U.S. presidential election. Journal of Communication, 64, 296–316.

Winter, J. P. (1981). Contingent conditions in the agenda-setting process. Mass communication review yearbook, 2, 235-243.

Woodly, D. (2008). New competencies in democratic communication? Blogs, agenda setting and political participation. Public Choice, 134(1-2), 109-123.

Ju, Y. (2014). Issue obtrusiveness and negative bias: exploring the moderating factors for asymmetric news coverage of the economy. Asian Journal of Communication, 24(5), 441- 455.

Zucker, H. G. (1978). The Variable Nature of News Media Inﬂuence (pp 225-240). Communication Yearbook, 2.

Appendix

Codebook

Corporate Communication Master Thesis

Oscar Thiellier (Std. 6162347)

ASCoR, the Amsterdam School of Communication Research.

Introduction

This codebook can be used as a reference or instruction manual for this master thesis. The aim of this thesis is to explore the relationship between social media and traditional regarding the transfer of salience of issues from a corporate perspective. For this the issue salience will be coded per media outlet (Traditional news vs. Social media) and the measurements will be used for a time-series analysis later on. The traditional news outlets used are the Dutch dailies “De Volkskrant” and the “De Telegraaf” and Twitter will be the unit of analysis for the social media outlet. Furthermore, an extra moderating variable, obtrusiveness, will be coded which also will be used for analysis. This research will look at the newsfeed of four different companies in two different industries.

Sample

Company N Tweets N Newspaper articles

ABN-AMBRO 216 1869

Rabobank 1869 129

Total Sample 2085 276

General coding guidelines

First the coder has to read the news article or tweet. After reading, the coder fills in the questions below, using the description formulated under the question. These guidelines can be used for both the Tweets and the newspaper articles.

001: Article ID

Fill in the number of the article used, starting from 001

002: Unit of analysis

1 Twitter 2 Newspaper

Here the coder fills in the origin of the coded material. One can choose either Twitter as social media, or “De Volkskrant” and “De Telegraaf” as traditional news media

003: Company name

1 ABN-AMBRO 2 Rabobank

The coder selects the company name mentioned in the article or tweet. N.B. when needed, multiple companies can be selected at once.

004: Day of publication

(dd)

The day of publication can be filled in by using two digits representing the day of the month

005: Month of publication

(mm)

The month of publication can be filled in by using two digits representing the month of the year

006: Issue attributed to the company in the article

1 Investments: Investments can be any investment (or sale) made by or in the company or government involving the company. Investments also concern personal loans given by the bank to individual. 2 Profits: An indication or suggestion of profit or loss by the company concerned (Rabobank or ABN AMRO). This can be actual numbers of profits and los, but also when the stock value of the banks themselves 3 Product quality Involving the product or service quality. Quality means the overall evaluation of the product or the improvement of ones products, for instance innovation, but also service related issues like compensation. 4 World economy Concerning the world economy, for instance world trade, prices of goods, interest rates etc. N.B., it does not concern price of currency or investments the company is involved in. For instance, trading 5 Price of currency Concerning the relative value of money. For instance the Chinese yen has dropped in value against the US dollar.

6 Employment Concerning everything that has to do with employement, for instance hiring of new people. 7 Mergers Concerning mergers where the selected companies is involved. No investments or partnerships 8 Image Image issues are problems that involve the brands image or reputation. For instance, winning of awards. Image issues are not the evaluation of a company by one single individual (for instance, “Rabobank sucks” 9 Environment Every issue that has to do with the environment. For instance, projects or events that emphasize the environment and the company is involved in. 10 Energy consumption Concerning the energy consumption of the corporation 11 Wages For instance, fair wages or exorbitant wages etc. 12 Inflation Concerning the value of money in one single country (inflation or deflation). Does not concern the relative value of money towards other countries. 13 Other issue Issues that do not comply with any of the issues mentioned above can be selected here. For instance Brexit, Libor, Sport 14 Not applicable When the text does not incorporate an issue, for instance when there is no text, only a link in the description. Or when the issue is not clear what it is

When selecting the issues attributed to the corporation in the article, the coder uses only one of the choices mentioned above. When there are more than one issue in the article, the coder choses the main issue represented in the article. The main issue refers to the issue that underlies all the issues represented in the text, causality is most important as selection criteria. For instance, when Rabobank invests in environmental business, the issue chosen will be the investments. When an issue is not in the list, the coder can fill in the “other issue” option, and afterwards fill in the blank text square in the next question

007: Other issues

When using the “other issue” option in the last question, the coder can fill in a word in the blank space that adequately entails the issue at hand (max. three words). For instance, Brexit, Libor, Sports.

008: Issue obtrusiveness

To what extend does the public have a personal day-to-day experience with this issue?

1 No personal experience up to 7. A lot of experience

To code this, the coder has to indicate to what level people can have personal experience with this issue. There are two aspects important. The amount of personal experience is not interchangeable with how important an issue is to people, nor as talking about it in interpersonal relationship. Personal experience can be seen as the day in day out direct experience one has with an issue (Demers et al., 1989)