Trump’s Twiplomacy: A New Diplomatic Norm?
Kajsa Hughes
Two-year Political Science MA programme in Global Politics and Societal Change Dept. of Global Political Studies Course: Political Science Master’s thesis ST631L (30 credits) Thesis submitted: Summer, 2020 Supervisor: Corina Filipescu Kajsa Hughes 19940526-2867 Political Science: Global Politics
Abstract
This study examined how Trump frames various countries and their leaders and whether the framing changes from different factors. It also observed whether foreign leaders were following the same path as Trump in their diplomatic communication and interaction on Twitter. This was to contribute more knowledge that connects global politics with social media to see if changes of frames through Twitter caused any global politica l consequences. Theories including realist constructivism and framing theory, along with concepts of social norms, political context, events, and enemy images, were applied to the study. Using directed content analysis, together with longitudinal and comparative elements, the findings showed a separation between Trump’s and the other leaders’ tweets. Almost all tweets were connected to the concepts, and various techniques of framing were identified in tweets from most leaders. However, Trump’s informa l, disdain, and dramatics in his tweets have distanced himself from the rest of the leaders’ posts. Although a couple of leaders’ attempt to be hostile towards Trump and the U.S. in their tweets, they were still formal. It shows that not only is Trump’s Twiplomacy a reflection of American superpower forcefulne ss, but also a unique form that the rest choose to ignore.
Keywords: framing, social norms, Trump, Twiplomacy, Twitter, Word count: 21,979
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Table of Contents
1. Introduction…………………………………………………………...5 1.1 Research Question and Aim……………………………………………..7 1.2 Research Contribution………………………………………………..….9 1.3 Relevance to Political Science and Global Politics…………………….10 1.4 Outline of Thesis……………………………………………………...... 10 2. Background………………………………………………………….12 2.1 The U.S. as a Superpower and its Negotiating Behavior….…………....12 2.2 Donald J. Trump and His Presidential Behavior……………………….13 3. Literature Review……………………………………………………16 3.1 Digital Diplomacy Literature…………………………………………...16 3.2 Framing Literature……………………………………………………...19 3.3 Explanatory Model for Political Agenda and Power Relations…………20 4. Theoretical Framework……………………………………………...23 4.1 Realist Constructivism as an Approach..……...………………………..23 4.2 Framing Theory………………………………………………………...24 4.3 Conceptual Framework……………………………………………..…..26
4.3.1 Social Norms……………………………………………………………….26 4.3.2 Events………………………………………………………………………27 4.3.3 Politica l Context..……… ……………………………………………...…..28 4.3.4 Enemy Images……………………………………………………………...28 5. Methodology………………………………………………………...30 5.1 Content Analysis…………………………………………………….…30
5.2 Longitudinal and Comparative Elements………………………..……..31
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5.3 Data Collection……………………………………………..…………..31
5.3.1 Primary Sources……………………………………………………………32 5.3.2 Additional Material………………………...………………………………33 5.4 Data Analysis and Interpretation………………………………..……...33 6. Findings……………………………………………………………...36 6.1 Overview……………………………………………………………….36 6.2 Trump’s Twitter Findings ……………………………..……………….36
6.2.1 Language…………………………………………………...………………36 6.2.2 Features..……………………………...……………………………………41 6.2.3 Trump’s Framed Groups………………………………...…………………41 6.2.3.1 Friendlies..……………………………………………………………….42 6.2.3.2 Friendlies with Negative Tweets……………………………...…………43 6.2.3.3 Mixed Relationships………………………………..……………………45 6.2.3.4 Non-Friendlies with Positive Tweets……………………………………47 6.2.3.5 Non-Friendlies…………………………..………………………………50 6.3 Findings from Foreign Leaders’ Tweets…………………………..……51
6.3.1 Friendlies…………………………………………………………………...51 6.3.2 Mixed Relationships………………………………………………………..59 6.3.3 Non-Friendlies………………………….…………………………………..63 6.3.4 Leaders without Twitter…………………………………………………….68 7. Analysis……………………………………………………………...70 7.1 Political Context………………………………………………………..70 7.2 Events…………………………………………………………………..71 7.3 Enemy Images…………………...……………………………………...73 7.4 Change in Social Norms?...... 74 7.5 Framing Theory and its Techniques Applied...………………………....75
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7.6 Realist Constructivism Revealed in Tweets...... 80 8. Conclusion…………………………………………………………...82 8.1 Summary…..……………………………………………………………82 8.2 Evaluation…………..…………………………………………………..83 8.3 Interpretation……………………………….……………….………….83 9. Bibliography……………………………………………………....…85 9.1 Literature……………………………………………………………….85 9.2 Tweets………………………………………………………………….98
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1. Introduction
Communication is the backbone of the postmodern political society, from face-to-face conversations, to international news coverage, to online posts by all types of actors. No matter the means, communication has always contributed to “shaping the character and scope of their society, its economic life, politics and culture.” (Lorimer & Scannell, 1994: 1). Moreover, communication is an important key within global politics to manage relations between countries, as it is recognized as “the established method of influencing the decisions and behaviour of foreign governments and peoples through dialogue, negotiation, and other measures short of war or violenc e ” (Freeman & Marks, 2016). It is the communication between two states to arrange global politica l practices such as diplomacy and foreign policy. This includ es goals, agreements, or adjustments, by using various tactics and strategies to accomplish them (ibid). Such progress between political actors are usually done behind closed doors, later for the results to be revealed to the public through various mediums. Traditionally, diplomacy is based on person-to person communication between diplomats sent by politica l leaders to promote the interests of their nation-states and to make compromises. While it mainly is bilatera l, it can even be done on a multilateral level, in which international political actors and institutions would hold conferences and summits to discuss their interests (Verrekia, 2017: 12). The goal of diplomatic relations is to strengthen nation-states, organizations and institutions, and even to resolve issues without using force or causing resentment, as means to preserve peace. However, there are times in which disputes and coercive threats are involved in diplomatic negotiations, leading to ultimatums, disrupting alliances, and even war. However, diplomacy overall strives for sustainable peace through cooperation and nonviolent resolution between nation-states (Freeman & Marks, 2016). The way to keep peaceful negotiations is through traditional diplomatic language. Researchers such as Simunjak and Caliandro (2019) have outlined the ways such a language and communication of political actors should be kept. These ways include ; being courteous, marked by respect for and consideration of others, constructive and positive, balanced and moderate, vague and open to interpretations, and deliberate, masterful, carefully and prudently drawn up. They additionally address the avoidance of dramatic communication, as well as superior,
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indifferent, controlling, or offensive behavior towards other actors, including no insults, uncivil wording, naming, and shaming (ibid, 2019: 14). Moreover, mass media, such as television, radio, and news articles has played an informative role for the public by presenting traditional diplomatic communication and behavior as friendly and polite, for example, showing foreign leaders shaking hands or having calm press conferences (Gilboa, 2001). Nowadays, however, factors such as new technologies and influential actors using them have altered such communication on media, affecting diplomatic behavior (Archetti, 2011: 182-183). Media has significantly changed over time, since the start of the Internet, and later on with the change from Web 1.0 to Web 2.0. For instance, with the update of the World Wide Web, its new technological applications have created more participatory and collaborated platforms to produce content, also known as user-generated content (Kaplan & Haenlein, 2010: 60-61). This content has led to social media platforms such as Facebook, Twitter, YouTube, etc., which are online infrastructures that allow user-generated content to be created and exchanged by individuals. Moreover, the increase of online access through new technologies like portable computers and smartphones has changed the way various populations access entertainment and information. Not only have these new inventions increased the networks and capacities of human knowledge, but they have additionally changed the norm – meaning the accepted standard behavior – of what is private versus public (van Dijck, 2013). van Dijck explains further about the changed norm, stating “patterns of behavior that traditionally existed in offline (physical) sociality are increasingly mixed with social and sociotechnical norms created in an offline environment, taking on a new dimensionality.” (van Dijck, 2013: 19). This new form of online sociality, especially through Twitter – a social media platform for individuals to post micro-blogs – has led to more types of speakers and interactions that have both positive and negative effects, especially within the diplomatic sphere of how political actors engage in online public conversations with each other, calling it “Twip lo mac y” (Burson-Marsteller, 2020).
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1.1 Research Question and Aim
Twiplo mac y has become a growing diplomatic sensation through which politicians are able to reach both domestic and foreign audiences through an increasingly direct interaction (Hughes, 2020). This can benefit political actors, institutions, organizations, and even citizens to engage in various views, interests, and perspectives on specific policy issues and other discussions (Duncombe, 2018: 93). The use of Twitter by political actors has become a new phenomenon, which has led to new studies by scholars such as Constance Duncombe (2019), and Radhika Chhabra (2020) who focus on the positive results of political actors moving towards an online medium. However, there is a lack of research on the negative consequences of political actors’ Twitter behavior. Moreover, as scholars like Bridget Verrekia (2017) additionally trace the evolution of diplomacy through online platforms and how it benefits themselves as political actors, there is lack of investigation of Twiplomacy’s vivid effects on relations between countries. This presents an issue in which a political actor may cause conflict from an online post, notably when the President of the United States (U.S.), Donald J. Trump, a much-known user of Twitter, erratically posts his comments and opinions of other national leaders, both positive and negative (Simunjak & Caliandro, 2019: 15). Furthermore, Trump’s language in his tweets contradict the traditional diplomatic communication norm with name-calling, threats, and dramatic comments. An example of this includes Trump’s frequent name-calling of North Korea’s leader Kim Jong Un as “Little Rocket Man”. In other words, he tends to offend and defame others as a tactic to make him look competent (Kristiansen and Kaussler 2018: 29, in Özdan, 2020). Such an example demonstrates how Twiplomacy could cause tensions between countries rather than amities. This presents the central research question:
“Is President Trump altering the norm of traditional Twiplomacy?”
In other words, the thesis speculates that Trump’s alternative way of communication through Twitter may cause other foreign leaders to follow the same path in such diplomatic communication.
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There is existing literature that focuses on Trump’s behavior and rhetoric on Twitter, but not on the way he frames other foreign leaders and vice versa, as well as any consequences. These issues listed present a large research gap, which this study means to fill. Therefore, the aim of this study is to examine how Trump frames various countries and their leaders and whether the framing changes from different factors. It will also observe whether foreign leaders are following the same path as Trump in their diplomatic communication and interaction on Twitter. In addition, it will further examine whether any changed frames of a country and/or its leader has led to diplomatic consequences. The paper argues that Trump’s tweets and his framings of other foreign leaders and countries are a combination of his narcissistic personality along with an extreme version of American forceful foreign policy, approaching foreign leaders as if it were the hegemon of a unipolar system that attempts to coerce other countries to follow American principles. It further argues that foreign leaders of major powers that Trump has framed negatively, has so far led to minor conflicts in which most foreign leaders discount his tweets and proceed to continue with traditional diplomatic communication. The research uses the single case study design with comparative elements, meaning that the study compares Trump’s framings as a concept and engagements with a number of countries, based on Trump’s relations with certain foreign leaders, and how he comments about them in his posts. Moreover, the research additionally includes longitudinal elements. This way, the study grasps an in-depth research analysis of a specific phenomenon over time with different types of data. It attempts to connect certain developments of foreign policies and summits to Trump’s portrayal of countries and foreign leaders involved. It also observes Twitter communication from other national leaders, as well as responses from Trump’s tweets to review any change in their diplomatic communication. The methodology chapter will discuss specifically the different elements briefly mentioned in this section. The research uses a combined International Relations (IR) theory, realist constructivism, as a theoretical lens, as well as framing theory, including related concepts such as social norms, political context, events, and enemy images. Data used includes tweets from Trump, and national leaders from the listed countries: Germany, Canada, France, Russia, North Korea, China, Iran, Syria, Venezuela, Mexico, the United Kingdom (U.K.), Brazil, Saudi Arabia, Israel, Japan, and
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India. Qualitative content analysis is used to categorize and analyze the Twitter posts. Additional data from other mediums is collected to represent those leaders who do not use Twitter, to further support the findings. This allows us to understand possible change in diplomatic communication, and the effects of Trump’s framing of other national leaders.
1.2 Research Contribution
This research focuses on a relatively new topic, as there has not been much academic attention directed towards the effectiveness of Twitter being used as a political tool, until Trump’s presidential campaign in the 2016 election and consequently his presidency. Findings of how any new change in diplomac y through framing via Twitter could academically contribute by further explaining power relations – meaning the political forces that affect the hegemonic discourse between states (Daldal, 2014: 152) – through social media platforms, and more specifically on Twiplo mac y. The thesis argues that if one political actor of a superpower can gradually change an internatio na l diplomatic norm through social media communica tio n, it will most likely increase and extended throughout other international elite actors and areas. Moreover, the study would also show how events and political contexts can have an effect through social media, leading to possible change in relations. Such factors between states and its leaders can change the perception of each other and therefore present another frame to the public, which could possibly lead to negative consequences. Publicly framing a national leader could lead to threats, new allies, and the worst being war. Thus, the concept of Twiplomacy requires much more academic and public attention to fully understand more modernized forms of communication between political actors, as well as the effects of it.
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1.3 Relevance to Political Science and Global Politics
Although there is much debate about defining politics and political science, it is mainly agreed that it focuses on “the way power is accumulated, used and controlled in modern society” (Guild & Palmer, 1968: 6 in Sharma & Sharma, 2000: 4). Social media is thus an increasingly used tool for those political actors who want to communicate to a wider audience in order to gain or control political, social, and economic power (Hughes, 2020). This is performed through public engagement of numerous politica l movements, issues, and summits/conferences to gain positive public opinion (Duncombe, 2018: 93). By the use of Twitter, political leaders can communicate directly to the public, rather than through news outlets to post about their engagements. (Simunjak & Caliandro, 2019: 15). Moreover, Kaarbo and Ray (2010) define global politics as “the relations among different actors in the world, the characteristics of those relations, and their consequences. It also has to do with the nature of those actors, how they have changed over time, and how their interactions have changed over time” (2010: 3). This is precisely what the study is attempting to examine, by monitoring any changes in power relations, from when Trump took office till the end of 2019, based on all leaders’ Twitter framings of others. Furthermore, it studies whether Trump’s specific Twitter behavior is powerful enough for other leaders to be influenced to the same manner, which could also result in altered relations between countries. Finally, connecting theories and concepts related to IR and political science to social media use, demonstrates that more modernized mediums can also be in the realm of political science.
1.4 Outline of Thesis
After this introduction chapter, there will be a background chapter, which focuses on providing historical and conceptual information required for an overall understanding of the factors and actors of the case study. This will be followed by a literature review to examine previous research related to the study’s topic. Afterwards, a theoretical framework is presented by including the important theories and concepts needed for observing various frames and changes
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from powerful actors worldwide. The next chapter describes the methodology of this thesis, along with reliability and validity reflections. It will also include an outline of the data collection, its interpretation, and general advantages and limitations. The sixth chapter provides the analysis findings, followed by a discussion chapter which connects the findings to the theoretical and conceptual framework. Lastly, the eighth and final chapter concludes the entire study.
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2. Background
2.1 The U.S. as a Superpower and its Negotiating Behavior
Throughout the history of the U.S., the country has formed a ‘world leader’ attitude. It from rebelling from Britain’s monarchy into a new ‘free’ republic, to embracing the riches from free trade domestically and internationally, later leading to an industrial boost for an economy; rejecting ‘old world’ European diplomacy; and its mission to spread American influence across the globe after the Great War to advocate peace and good-doing based on Woodrow Wilson’s promotion of America’s role of world leader. Such assumed values and ideas have determined today’s American foreign policy approach, striving to shape events and areas based on their principles (Herring, 2008: 2-3). The ideological pragmatism initially was offsetting for the international public, leading the country towards unilateralism (isolationism). This eventually created an attitude or moral superiority, patriotism, and sensitivity towards foreign threats during the world wars (ibid: 5-7). Moreover, it has always been somewhat hostile towards international politics and institutions, deriving from its separation of the European political regime. This had also an effect on its foreign policy by exploiting their rivals for their own sole interests (ibid: 8- 9). Even though relations between powers are hypothetically seen as a multipolar system or uni-multipolar system – meaning the U.S. as the superpower, but still requiring other major powers such as Germany, China, France, Brazil, etc. to combine action for international issues – the U.S. hypothetically prefers a unipolar system in which it would be the hegemon, and therefore its officials tend to behave as if it were, lecturing other countries to follow American practices and standards (Huntington, 1999: 36). However, the other major powers prefer a collective multipolar system leading to less pressures and coercions of more powerful countries (ibid: 37). When countries refuse to be coerced by the U.S., the country attempts to use economic sanctions and at the worst case, military interventions such as launched bombings or missile attacks, which could lead to an international backlash. Economic sanctions work when other
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countries support them, otherwise they do not use them in which they become symbols of American weakness (ibid: 39). This can also be reflected onto their diplomatic behavior, as it is claimed that U.S. negotiators and diplomats are “forceful, explicit, legalistic, urgent, and results-orie nted”, with the regard that the U.S. is a world hegemon (Quinney, 2002: 1). Moreover, cultural and structural factors play a part in their negotiating behavior, in which their language is blunt and related to American culture such as “labor relations, Christian theology, and sport”, while also setting various pressures such as earlier deadlines and exerting different resources to show the benefits of agreeing with the U.S. and the costs of not reaching an agreement with them (ibid). The examples provided in this section plays a large role in the diplomatic behavior of American political actors such as President Trump. Tougher coercion with various countries for American interests has somewhat always occurred during the country’s existence (Huntington, 1999; Art, 2003). Therefore, framings of various national leaders through Twitter for example, might be one version of American diplomatic forcefulne ss when they are not in accordance with American princip les.
2.2 Donald J. Trump and His Presidential Behavior
Various researchers such as Eugene B. Kogan, Ilias Kapoutsis and Roger Volkema, and Asaf Siniver and Christopher Featherstone have studied Trump’s ways of negotiation, his personality traits, and grounds for his decision-mak ing. Not only have psychologists suggested that he could have a narcissistic personality, a large number of accounts from his associates, adversaries, and third-party observers like journalists report that his behavior falls into the category of hypercompetitive, demonstrating “heightened self-worth fluctuating with underlying low self- esteem, high levels of neuroticism, decreased need for others, and interest in admiration and recognition from others” (Kapoutsis & Volkema, 2019: 48-49). Moreover, his background as a millionaire from Manhattan allowed him differentiate himself from other Republican candidates during the 2016 election, as well as making numerous controversial and politically incorrect
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statements which made him seem like a “hard-core toughie” and relatable to the public (ibid: 50, 56). This behavior is also seen in his ways of negotiating, in which Eugene B. Kogan (2019) describes Trump’s style:
First, Trump is an observer: he begins a negotiation with an assessment of his counterparts’ strengths and vulnerabilities. Second, he is a performer: he is perennially aware of – and seeks – media attention in order to use publicity to maximize his leverage in a negotiation. Third, he is a controller: his top-down leadership style aims for bureaucracy-free efficiency. Finally, he is a disrupter: gut-driven, action-oriented, and risk-tolerant, he draws strength from adversity. (ibid: 67).
Even though Kogan presents his negotiation style in a very formal manner, Trump’s behavior is much more controversia l in which accounts and studies have shown that he is quick tempered, has a short attention span, and has a poor impulse control (Drezner, 2020: 384). His attempts to erode presidential constraints are worrisome, in which his psychology could possibly lead to negative consequences. Various subordinates and supporters have characterized him as if he were acting like a child, having no interests in trade organizations or policy issues, which hurts his decision-making (ibid: 386-387). Moreover, his deficit in knowledge and short attention span has led to missing out shifts in countries’ stance on an issue, breaking diplomatic protocol which disrespects foreign leaders, and constant delaying implementations of policies (ibid: 389). His emotiona l impulse control has led to decisions and threats such as the trade war with China or threatening to close the Mexican border, which he later was not committed to. Not only has this left American citizens to distrust him, but also foreign leaders to discount many of his threats (ibid: 390). Trump’s behavior has led to the inability to negotiate, bargain, settle disputes, and other deals, which in turn has impaired his presidency. Trump’s behavior and decision-mak ing additionally comes from a plutocratic (money- first) worldvie w, in which political and diplomatic issues are treated as economic endeavors or business opportunities (Siniver & Featherstone, 2020: 2). This is seen in his administration, with a cabinet of millionaires and billionaires, as well as his choice of destinatio n of his first visit
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being Saudi Arabia instead of the typical Mexico or Canada, due to the country’s business deals of hundreds of billions of dollars (ibid: 4-5). Moreover, his only involvement in the North Atlantic Trade Organization (NATO), is whether alliances have met the target spend of 2 per cent of their GDP on NATO. Otherwise, Trump lacks interest in other political, national security, or diplomatic issues, in addition to be confrontational and breaking international norms (ibid: 5- 6). This demonstrates that his influences come from money and business deals, rather than from international policy making and collaborative efforts with other states, leading to heavy critiques for foreign leaders. The sections in this chapter provide relevant background information, which provides an understanding of Trump’s tweets later in the analysis. The discussed factors go hand-in-hand by explaining how there is more to Trump’s tweets, as the U.S. has already demonstrated its distinctive diplomacy, affecting different relations. The next chapter presents previous research to elaborate on specific works related to the study.
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3. Literature Review
3.1 Digital Diplomacy Literature
For more diplomatic purposes, several works have looked at both positive and negative ways in which Twitter and social media in general have become a diplomatic tool. Bridget Verrekia’s (2017) studied the advantages and challenges of digitalization within diplomacy. By interviewing four former diplomats or individuals working for organizations that involved diplomacy, the research discusses various dynamics of digital diplomacy. This includes the change within public diplomacy, from monologue to dialogue, meaning instead of informing the public via radio, articles, and television, social media platforms allow the public to interact with the political actor (ibid: 17). Social media has also extended diplomatic networks through digital accessibility, allowing non-state actors to become more valuable and beneficial for diplomats and world leaders (ibid: 19). Additional positive factors include such new platforms and technologies to allow political actors show their activities so that public are included in such processes, as well as decreasing financial and environmental costs with less travel (ibid: 21). However, challenges discussed involve many world leaders either not taking advantage of the new digital diplomatic communication or are misled or confused about using social media platforms like Twitter. This could possibly hurt their political representation when not extending their influence (ibid: 22-23). Another disadvantage is the threat of cybersecurity, which involves leaked information, accounts being hacked, or anonymous misinformation and disinformation, causing dangers within diplomacy (ibid: 24-25). Verrekia concludes that even with the positive effects of digita l diplomacy, humans are still needed in the field for various diplomatic activitie s such as negotiating confidential matters. The second study is a brief by Radhika Chhabra (2020), which also reviews positive and negative aspects of digital diplomacy, but rather the communicational aspect in which the author points out that diplomacy involves constantly continuing relations between states and non-state actors (ibid: 3). The brief mainly looks at Twitter as a communicative tool and reviews the different communicative dynamics from the platform. One of the advantages is the ease of
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communication between actors of all levels, encouraging actors to take part in debates and discussions revolving foreign policies and decision-making processes, thus escaping bureaucratic processes (ibid: 4). Moreover, online interactions between states enhance mending relations, and develop trust and even alliance with each other. Another advantage of Twitter diplomacy is the crisis response mechanism, which effectively reduces the time to respond to crises and extend support to citizens in need of help worldwide (ibid: 5-6). The final positive aspect is image enhancement recognition, meaning how a state is recognize by others. Social media platforms are thus used as a tool to cultivate a positive state identity representation. Such image management has the goal to be more included in diplomatic engagement with other states in order to increase their influence. It also allows individual political actors to manage a positive perception of themselves to the public (ibid: 6-7). One disadvantage that Chhabra mentions, is that the ease of communication among political actors can undermine the effect of traditional diplomacy (ibid: 7). Moreover, tweets can often be misleading and create a vague atmosphere. Another negative aspect is the escalation of conflict, when irresponsible Twitter exchanges create a ripple effect of misunderstandings and distrust, leading to unnecessary conflict (ibid: 8). Chhabra even uses Trump’s hostile tweets about North Korea as an example. The author concludes by questioning the effectiveness of using Twitter as a tool for diplomacy. The two works above demonstrate that there currently is a growing number of political actors turning towards social media, which produces both positive and negative outcomes. What the studies lack, however, is the examination of changes in framing from political leaders’ tweets, as well as studying any change in Twitter behavior from leaders influenced by another leader such as Trump. Therefore, this study aims to fill those gaps. Maja Simunjak and Alessandro Caliandro (2019) pursue to understand how Trump is using Twitter for diplomatic purposes and which political actors engage with him on Twitter, leading to question whether there is a new code of diplomatic communication via social media developments (ibid: 13). The two authors outline traditional diplomatic communication and compare it to Trump’s controversial language and behavior on Twitter, leading to concerns of his presidential communication after taking office. Either his style of communication would disrupt
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diplomatic practices and possibly cause international conflicts, or it would break the traditional diplomatic pattern of communication (ibid: 15-16). Simunjak and Caliandro use the Digital Methods (DM) approach to manage and map out online structures, and additionally used content analysis and discourse analysis. Data collected included Trump’s tweets of the first month of his presidency using a Python software to collect and narrow down tweets, along with additional tweet from national leaders that mention Trump. The authors then discussed which national leaders Trump tweeted more about than others, and vice versa, followed by showing his twitter interactions. This resulted in 5 categories, displaying the countries that engage or not with Trump, as well as whether the conversing from each side was negative or positive, thus showing any change in formal diplomatic communication. Simunjak and Caliandro additionally study Trump’s Twitter language. With American allies he uses courteous language, whereas for other countries he does not use positive and constructive language (ibid: 20-21). For Iran and Mexico, Trump portrays the countries unfavorably through negative connotations, along with being superior to them. However, he additionally used negative language for friendly countries like France, Australia, and Sweden due to various events. Russia has been portrayed both negatively and positively, but mainly about Trump’s personal relationship with the country, not formally like the others. However, the truthfulness appears somewhat vague when Putin’s and Trump’s statements contradict each other’s. In general, his vocabulary and phrase structure try to portray these countries with numerous problems as unsafe. The authors conclude briefing about Trump’s controversial behavior and rhetoric on Twitter, and how it contradicts the traditional diplomatic code of communication. Moreover, the only national leader who responded in a similar manner was the President of Venezuela, the rest has never responded to Trump’s attacks. However, the authors stress that their study should be replicated in a longitudinal form. This study attempts to do so, while also using framing as an important aspect. It will additionally examine whether Twitter engagement between leaders will affect power relations, which Simunjak and Caliandro’s (2019) study lacks.
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3.2 Framing Literature
The next two studies provide separate examples of framing. As it is generally used by the media to provide meaning and a perspective to the public, it can also change the meaning of an object, tactic, or phenomena. Muhammad Rashid and Moazzam Naseer (2019) demonstrate how two different news channels, namely Al Jazeera English and Al Arabia, can frame situations and events from the conflict between Saudi Arabia and Qatar. The two countries have gone back and forth between peaceful and hostile, and Al Jazeera tends to be critical of Saudi Arabia, while Al Arabia criticizes Qatar (ibid: 6). Using critical discourse analysis of news reports from both channels, the authors found that Saudi Arabia is portraying Qatar as a supporter of terrorism and an ally of Iran (a rival of Saudi Arabia) through the media channel Al Arabia. Qatar, however, uses Al Jazeera, which has acquired a large audience within and outside the region (ibid: 19). Saudi Arabia considers itself to be the hegemon of the Muslim countries, and after being criticized by Al Jazeera, the medium has been blocked by Saudi and other Arab countries. However, Al Jazeera has a larger audience, and therefore has the confidence to heavily criticize Saudi Arabia’s authoritarian mannered government, their support of terrorist groups in order to contain their rivals, and their human rights violatio ns (ibid). Thus, the results show that both countries are framing each other as an enemy through their own controlled news channel, but also showing how Qatar is ‘winning’ due to its channel’s large and wide-ranged audience. The next piece of literature focuses on changing the perspective of the use of landmines in a multilateral summit through framing. Miguel de Larrinaga and Claire Turenne Sjolander (1998) discuss how the use of landmines during the 1997 Ottawa Process has been put on the international agenda. Those who were for landmines would frame it as a legitimate weapons of war, and how they are a necessity for state security and preservation (ibid: 130). To challenge such framing requires tackling the masculine hierarchy of authority and privilege that ignores civil society over ‘protection’ of the state, by de-politicizing landmines (ibid: 130-131). Thus, the counter discourse involved themes such as the threat to human security, showing that the primary victims of landmines are civilians (ibid: 132). Moreover, arguments additionally involved the end of the Cold War, stressing decrease of security of the state and focusing more on the security
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of humanity (ibid: 133). Humanitarianizing landmines, by showing its consequences of its victims – mainly women and children – through words and images, allows the framing of the use of landmines as a legitimate security tool to move to an enemy towards civil society. Such change of framing thus resulted in anti-landmine treaties and movements at the end of the Ottawa Process. The literatures above demonstrate that framing can be used by various actors and mediums, for different purposes. It benefits this study by showing how conflicts, events, and change in politicized objects or phenomena can alter the way one frames something or someone. Framing through a social media platform, however, is a new form that has not been investigated enough. This study, therefore, attempts to investigate the same concept through a new medium, namely that of Twitter. The next chapter provides a theoretical framework that benefits the research to conceptualize the analysis along with the background information.
3.3 Explanatory Model for Political Agenda and Power Relations
This section explains how various elements can be translated into a conceptual framework to explain power relations as well as a country’s own politica l agenda. Johan Eriksson and Erik Noreen (2002) attempt to create an explanatory model from various concepts that form threat images and political security agenda. The concepts include identity, cognition, framing, events, political context, institutional context, and opinion, all based on perception and the hierarchical status of the country. This means that more elitist countries make more security decisions based on more amounts of perceived threat. They additionally demonstrate the model with the concepts in their figure below.
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(ibid: 19)
The authors apply their explanatory model onto various examples such as the September 11 attacks, an event that has drastically changed American opinion and identity through cognitio n to frame terrorism as priority to tackle as their politica l and institutional agenda (ibid: 6-19). Another example is the relations between the Baltic states and Russia, in which the event of Russia withdrawing their occupation of the Baltics has led to developing their own identity. However, their opinions and political context still show that they perceive Russia as a threat, to which their priority is become members of NATO and to continue to frame Russia as untrustworthy (ibid: 13-16,19-20). The final example includes Sweden’s political and institutional context, in which its various political parties represent different identities and thus opinions of what is a threat, such as the Green Party viewing military threats as non-existent and environmental threat as a top priority (ibid: 15, 18, 20). Although this work focuses more on security, Eriksson and Noreen’s (2002) explanatory model introduces concepts that can be possibly reflected onto world leaders’ tweets, which will be looked at in the next chapter. Felicia Schillström (2020) executes an in-depth case study of the U.S.’s enemy image towards North Korea during Trump’s presidency, and how it has affected foreign policies concerning peace between the two countries, by using the same explanatory model by Eriksson and Noreen (ibid: 10-11). The author analyzes four events from 2017 to 2019 using both traditional and comparative case study design, focusing on the changed discourse of the U.S. enemy image of North Korea (ibid: 17). The events involved a detainee, nuclear tests, and summit-meetings, which were used to see whether they had an impact on Trump’s framing of 21
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North Korea and the relations between the two countries. Materials collected include public speeches and news articles describing the events. When applying the concepts from the explanatory model to the four events, the analysis revealed that Trump is framing North Korea as a country and the relationship between the two through his rhetoric on Twitter and from speeches. The rhetoric between 2017 and 2018 had changed from hostile to more negotiable, in which the two countries attempted to cooperate through the summit-meetings (Schillström, 2020: 21-23). The cognitive aspect is from the disapproval of the ideology of communism from the U.S, whereas North Korea has been striving for since the Korean War (ibid: 23-24). National identity is important to include since the two countries’ core values clash with each other (ibid: 24-25). As for the political context, Trump’s speeches show how North Korea was a threat only towards the U.S., but still was striving for strategic bilateral agreements for the interests of both countries (ibid: 28-29). Schillström concludes that Trump’s enemy imaging of North Korea has slowly downplayed from negotiation but has become unclear since the Hanoi Summit-Meeting. Schillström’s study shares similarities to this specific study, by showing Trump’s changes in framing a country and its leader. However, this study focuses on Twitter posts by Trump and many other additional leaders. Moreover, Schillström lacks an important factor in which Trump practically taunts Kim Jong Un through name-calling on Twitter, and additionally does not examine whether North Korea responded to such tweets. Thus, this study contributes to the scholarship by investigating further into leaders’ changes of framings of others through Twitter.
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4. Theoretical Framework
4.1. Realist Constructivism as an Approach
Realism and constructivism are generally seen as two separate entities within the sphere of IR and global politics. Realism focuses on power politics, more specifically that the state is the main actor in international politics that uses power – meaning the interests and agency of the state – of its social institutions, that structures relations between other foreign states (Barkin, 2010: 17-18, 20). Constructivism, on the other hand, focuses on the effect of constructed ideas and beliefs on world politics rather the material agents, in addition to that reality is constantly changing along with meanings (Theys, 2017: 37). Samuel Barkin (2010) has therefore combined the two, calling it a realist constructivism. This not only focuses on the relations between countries and their powers, but also the change in international politics through social structures (ibid: 169). This approach can help further explain any tensions between countries from developing new policies by seeing how countries have to compromise and negotiate various terms that might contradict their national identity (ibid: 170-171). Sterling-Folker (2004) explains that power and values go hand-in-hand, using tribes as an example to demonstrate the importance of tribal morality, as it is both socially constructed but controls its practices in relation with other tribes. This is reflected into the modern-day global system of how human experience has an impact on groupings and power relations (ibid: 342). However, it can also function the other way around, in which power is complex enough to have an impact on social relationships (Bially Mattern, 2004: 345). Thus, a variety of factors combined take an effect on political processes. As the concepts of this study involve power hierarchies, framing, and social norms, it is important to have an approach that overlaps each other. Realist constructivism demonstrates that perceptions of events, countries’ values and interests, and policy agreements, can lead to changes of relations between countries through leaders’ framings on media. The combined theories additionally show that the influence of a leader of a superpower could possibly alter the social norm of formal diplomatic communication, which perhaps could eventually lead to shifts in
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power relations and alliances between countries. If it does not alter, however, it still proves how a social norm does not diffuse as well as how foreign leaders choose to not engage on Twitter like Trump as a survival tactic for their state.
4.2 Framing Theory
Framing is claimed to be a process of agenda-setting, but can also focus on “the essence of the issues at hand rather than on a particular topic” (Davie, 2011), meaning that there is more behind an event, person, or object. The actual theory involves the media focusing “attention on certain events and then places them within a field of meaning” (ibid). More specifically, a frame is something that can be presented in different ways, depending on the audience, as well as the interests of the controller of the media. It can therefore have a large influence on a specific public by presenting something in a way that benefits the social players. There are two types of structures of framing – or ‘frameworks’ as Erving Goffman (1974) refers to – that both play a role of letting individuals process data and differ by functionality. The first type is natural frameworks, which is the most basic framework in that physical phenomena are literally identified without any social forces involved. Second, are social frameworks, which base communication processes from socially driven events. Both frameworks influence people to interpret information to form opinions and attitudes and make decisions (Goffman, 1974, in Davie, 2011). In addition, framing includes various techniques, which are used by social actors controlling a type of media, to draw the public’s attention towards a specific topic that has been framed according to the goal of the social actor. Such techniques are displayed in the table below:
Metaphor: To frame a conceptual idea through comparison to something else. Stories (myths, legends): To frame a topic via narrative in a vivid and memorable way.
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Tradition (rituals, ceremonies): Cultural mores that imbue significance in the mundane, closely tied to artifacts. Slogan, jargon, catchphrase: To frame an object with a catchy phrase to make it more memorable and relate-able. Artifact: Objects with intrinsic symbolic value – a visual/cultural phenomenon that holds more meaning than the object itself. Contrast: To describe an object in terms of what it is not.
Spin: To present a concept in such a ways as to convey a value judgement (positive or negative) that might not be immediately apparent; to create an inherent bias by definition. (Fairhurst and Sarr, 1996). These techniques above can be seen in ways Trump tweets about different countries and/or its leaders, using nicknames, phrases, humor, etc., all to draw attention and to develop a perspective on that specific country and leader. One example includes Trump’s catchphrase-like nickname for North Korean leader Kim Jong Un as ‘Little Rocket Man’, based on North Korea’s nuclear weapons testing (Keating, 2017). In a more politica l view, when individuals already have a definable set of political beliefs about certain topics or issues from their stored memories. This makes it more diffic ult for social actors like politicians to establish frames to encourage people to think about such issues differently. Therefore, the strategy of “frame in communication” is required to highlight certain features or the topic’s relationship to and individual’s values to provide meaning (Chong & Druckman, 2007: 105-106). The problem with framing is that “they can be built around exaggerations and outright lies playing on the fears and prejudices of the public ” (ibid: 111). Overall, many different framings and techniques are used by leaders on social media platforms to show the public their relations with other countries based on political, social, and economic ideologies. More specific concepts affecting frames are outlined in the following section.
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4.3 Conceptual Framework
This section outlines four concepts in relation to the theories above in order to further explain constructed behaviors and power relations affecting frames. The second and third concepts are acquired from Eriksson’s and Noreen’s (2002) explanatory model.
4.3.1 Social Norms
Karl-Dieter Opp and Michael Hechter (2001) claim that norms are cultural phenomena that prescribe specific behavior according to the circumstance, and even considered to regulate social behavior (ibid: xi). Although there are institutional norms such as laws, social norms are more spontaneous and enforced informally, like an expected behavior according to the social circumstance. In other words, norms are a cooperative pattern of action that produces meaning, in which individual interpret a given situation based on the collective behavior (Horne, 2001: 4; Fine, 2001). When a norm is formed, there must be a group agreement with some level of consensus in regard to the validity of the rule in order for it to be enforced (Horne, 2001: 5). If only one individ ua l starts a rule, it is not a norm but only their personal temperament. When many people start engaging in the same manner frequently and consistently, “that behavior comes to be associated with a sense of oughtness” (ibid: 6). Individuals then start complying to the according behavior. However, whenever norms start to innovate, individuals choose to either comply or ignore them for the risk of gaining or losing “social approval”. Therefore, actors involved in that norm innovation must come up or change strategies for its diffus io n. A change in norms can also receive different effects from the public due to various motivations. This means that some people will only follow behaviors because of their popularity (ibid: 9). Individuals also have different or conflicting understandings of a new situation, which leads them to negotiate their cognitive interpretations with themselves in order to act in
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accordance with the old or new norm (ibid: 11). Moreover, their decisions also depend on their self-interests, whether their new behavior will lead to benefits or consequences. However, an individual usually complies when group members do the same. Therefore, networking and higher social positions in society are important to distribute a new norm (ibid: 19, 21). As Jose van Dijck (2013) briefly stated in the first chapter, Twitter created a new norm of online sociality. Not only have selecting and presenting personal information become an emerging shared rule and expectation, a new form of communication structure of shorter meanings and less formal language has also contributed to the new norm of demonstrating personal authenticity to a large audience (Schmidt, 2014: 8-10). As for political leaders, seeing the positive effects of social media and its popularity leads them to comply as a way for them to interact directly to the public and to other foreign leaders for their own benefit. However, the question raises of whether a leader from a superpower such as Trump can influence other political leaders to comply towards his Twitter behavior as a new norm.
4.3.2 Events
Events, mainly dramatic ones, can arguably be a concept for explaining certain frames of actors or countries on media. Usually events seen as crises or external shocks lead to extraordinary measures taken involving proposals, resources, and programs (Keeler 1993; Kingdon 1995; Stern 1999; Hermann 1990: 12, in Eriksson & Noreen, 2002: 12-13). The classic example is the 9/11 terror attacks in the U.S., causing the world to prioritize counterterrorism. It additionally caused negative framing on Middle Eastern countries, in which the network responsible for the attacks, al-Quaida, was located. However, dramatic events can even contribute to more peaceful changes like de-securitization and eliminating enemy images. An example of this includes the withdrawal of Russian troops in the Baltic countries in the early 1990s, which led to downplayed security conditions as well as a downplayed threat image of Russia to the world (Eriksson & Noreen, 2002: 12-13). Events as a concept is important to consider when attempting to understand Trump’s various Twitter posts involving a positive or negative image of a foreign leader or country.
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4.3.3 Political Context
Johan Eriksson and Erik Noreen (2002) argue that any political context can be used as a concept, as it can develop a political actor’s decision-making through its knowledge of the context as well as the event occurred, along with the actor’s interests, rather than power-based arguments other persuasive measures (ibid: 15-16). A political context between two countries can include their ideologies, past negotiations, alliances, coalitions, and preferences (ibid). Such factors are taken into consideration when developing a new policy. This concept helps us understand the difficulty of establishing new foreign policies between countries depending on the issue. This includes environme ntal issues, security and terrorism, threats, economic issues, etc. Therefore, strategic maneuvering along with the sharing of information (secret or public) is required to reach any foreign policy agreement. However, when political leaders are still not in agreement, conflicts such as sanctions or enemy images could arise, which is discussed in the subsequent section. Thus, factors from a political context between two countries and can influence the attitudes and framings of each other through the leaders’ tweets.
4.3.4 Ene my Images
This concept takes place in a situation where perceptions of an individual or group create a negative evaluation, seeing them as bad or evil (Eckhardt, 1991: 87). Attitudes and beliefs are involved in the processing of the image, meaning that if one already believes a specific individual or group has contradicting values, an enemy image presented will enhance the negative perception of that group. Willia m Eckhardt describes how politica l actors create enemy images, claiming:
One of the chief ways of making enemy images is simply to condemn or denounce some person or some group for not wanting or respecting certain values which, it is generally assumed, almost every self-respecting and value-respecting person should want or respect (ibid: 88).
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This has already been witnessed during many events in which the U.S. public ly accuses another country for not acting accordingly to ‘global’ (American) principles, thus threatening them with sanctions or even violence. Such public portrayals could then affect a country’s relations with others (Huntington, 1999). Even though enemy images are mainly considered for the psychological preparation of war or genocide, as it is propaganda, it is important to use this concept in less dramatic situations, like diplomatic matters (ibid: 94). Using the U.S. as an example, when foreign countries are not agreeing to their policy requirements, American politica l leaders aim to denounce such countries through media and sanctions until the country finally agrees or comes to a compromise. Enemy images can thus be recognized as a power relations tactic (Boulding, 1959), and even a tool to negatively frame countries and its leaders through social media.
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5. Methodology
5.1 Content Analysis
For this case study, to grasp an in-depth understand of the leaders’ diplomatic uses of Twitter, qualitative content analysis is applied as the technique of identifying characteristics, themes, categories, and other inferences within messages and other forms of communication (Holsti, 1969: 14; ibid: 290). This method not only examines the message itself, but also the sender(s) of the message and the audience as well, or in other words, “to provide knowledge and understanding of the phenomenon under study” (Downe-Wamboldt, 1992: 314). The method thus allows us not only to see the language and features used in the tweets, but also why they choose to tweet in that manner. Qualitative content analysis comes in three different approaches: conventional, directed, and summative (Hsieh & Shannon, 2005). This specific research uses directed content analysis, in which the goal is to validate and/or extend the theoretical framework of the study (ibid: 1281). This approach becomes more deductive and structured by already providing predictable variables, meaning that the key concepts become initial coding categories and the theory leads to the operational definitions of each category (ibid). In order to avoid biases and increase trustworthiness, it is important to properly identify categories and even subcategories before coding (ibid: 1282). Therefore, for this research, categories with codes related to state relations and framing have been prepared as part of the analysis, in which the findings will later support or contradict the theory. Content analysis on miniblogs or tweets rather than speeches has to be carried out differently, in which small details online such as the use of capital letters, or specific punctuation marks like exclamation points can express anger or importance. Moreover, online platforms also allow users to upload pictures, videos, or reposts of other users’ utterances, which further demonstrates their type of behavior through such characteristics (Einspänner, et. al, 2014: 98). In short, the Internet has developed a massive array of information with meaning, but it can also be overwhelming to doing research on online behavior. Therefore, it is important for this study to
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narrow down on specific data to do content analysis on the rhetoric and characteristics of Twitter posts from various national leaders according to the theoretical framework.
5.2 Longitudinal and Comparative Elements
Alan Bryman (2012) states that qualitative research is in risk of being too subjective or too difficult to generalize and replicate (ibid: 178-179, 405-406). It is important then, when using content analysis as a method, to have findings that accurate and replicable for the results to be valid and reliable. To do this requires longitudinal design elements, meaning collecting data over a longer period of almost three years to observe any development of a specific phenomenon. Moreover, as this study attempts to examine multip le national leaders’ online behavior and responses to Trump’s framing and comments on Twitter, comparative elements are additionally required to observe any changes and/or patterns, and effects of communication. These two elements will therefore benefit the study by observing and analyzing different patterns, specific characteristics, and change over a longer time period to have accurate and replicable results (ibid). The specifics of the data collection and interpretation will be reviewed later in the chapter.
5.3 Data Collection
Although the data collection is mainly purposive, meaning that the study specifically selects certain units or cases that represent the purpose of the research (Teddlie & Yu, 2007: 80), it sometimes required convenience sampling (drawing easier accessible data (ibid: 78)) for a more flexible approach when attempting to search for more difficult accessed data. What needs to be stressed is how to avoid subjectivity throughout the collection of data, which is a concern when using the purposive sampling technique.
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5.3.1 Primary Sources
Primary data include s Trump’s tweets from the start of his presidency in January 20, 2017, to December 31, 2019, from both his personal and presidential Twitter account, both found from an archival source online called Trump Twitter Archive (2020). The website not only holds all of Trump’s tweets (including retweets), but also has a search engine with techniques that allows an individual to find a specific tweet based on keywords, dates, time, and even devices. The number of tweets will be narrowed down by finding specific tweets of 16 countries (Germany, Canada, France, Russia, North Korea, China, Iran, Syria, Venezuela, Mexico, the United Kingdom (U.K.), Brazil, Saudi Arabia, Israel, Japan, and India) and their national leaders, used from the archive’s search engine, in which names of the countries and/or their leaders are typed into. The tweets are then shown in chronological order. These countries/leaders were chosen based on events, changed relations, and opinions from Trump during his time in office, as well as being the most tweeted countries by Trump, apart from Ukraine. This is due to Trump’s Ukraine tweets focusing on an unrelated issue from this study’s topic. Tweets from the aforementioned countries’ leaders are collected from their twitter accounts on the actual Twitter website, using Twitter’s advanced search where one can narrow down an account’s posts from a specific time frame and keywords. Thus, the collection of data from other national leaders is as similar as to collecting Trump’s tweets. One disadvantage, however, is that the tweets are presented in a non-chronological order, which entails having to spend additional time organizing all posts. An additional issue is the language barrier, in which several tweets from a leader about the U.S. or Trump is written in their native tongue. This requires even more time spent on translation via Google’s Translate. However, the number of tweets from such leaders are far from the amount of Trump’s posts and many of those tweets have an English version of the same tweet.
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5.3.2 Additional Material
Leaders such as Kim Jong Un from North Korea and Xi Jinping from China do not have Twitter accounts, and Angela Merkel has not used her official Twitter account since 2017. However, they still respond to events and comments from Trump. News articles, briefings, and other mediums which include such documented and even translated responses, will be used as additional data to contribute to the findings and analysis. Moreover, to understand the political context and events between the U.S. and another country, and even between Trump and another foreign leader, news and academic articles are additionally required. Such information was then connected to Trump’s tweets and why he frames the country and/or its leader in a certain way.
5.4 Data Analysis and Interpretation
Bryman states that, “qualitative content analysis comprises a searching-out of underlying themes in the materials being analyzed” (2012: 557). Thus, this study requires the use of a coding scheme, meaning “a translation device that allows investigators to place utterances into theoretical categories” (Poole & Folger, 1981: 367). As this study not only examines how and when Trump frames another state and/or its leader, but also whether such leaders are tweeting in the same manner as Trump, the analysis needs basic clear categories to code themes in accordance to the theoretical concepts of political context, events and enemy images reviewed in the previous chapter. This is due to the large amounts of data, mainly from Trump’s Twitter account. Before coding, it was additionally required to collect background information for each chosen country with its relations with the U.S., to create an informational timeline of their relations. The timeline begins from Trump’s presidential inaugura tio n, January 20, 2017, to December 31, 2019. This was to have a strong understanding of the political context between the U.S. and another country, along with specific events that could have altered its relationship, to fully understand all the leaders’ Twitter posts and decrease any coding issues. The choice of codes was based on themes and patterns related to interstate relations.
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The coding process came in two phases. The first phase entailed identifying three basic main categories, which were color coordinated as followed: positive (yellow), negative (red), and neutral (green). These categories are based on the context and language used in the tweet to describe a situation, country, or its leader based on its codes:
Positive: agreement, support, friendship/alliance, condolences, appreciation, congratulating, other Neutral: informative, sarcasm, other Negative: concern/disappointment, threats, taunts, condemnation, accusation, other
The code ‘other’ in each category represent tweets and phrases that are vague or unidentifiable. Moreover, for some occasional tweets from a few foreign leaders, and for many of Trump’s tweets, more than one category was identified, which was additionally recognized in the analysis. Many tweets from all leaders included features such as images and videos, hashtags (#), punctuation marks (?, !), use of capital letters (“CHINA HAS…”), hyperlinks to articles and websites, retweets, answering of tweets, and emojis. These features play a major role in the analysis by showing emotions or informing the audience about a certain topic, event, country, or its leader in a particular way. The second phase of the coding process involved identifying codes in relation to the theoretical and conceptual framework. More specifically, this entailed looking for patterns from foreign leaders’ tweets that are similar to Trump’s tweets, as well as finding tweets that include patterns from framing techniques and concepts such as enemy images, events, and political context. Because a tweet is only a small amount of limited characters, there was no need for qualitative software programs. Instead, each tweet along with its features was categorized into Excel spreadsheets to identify the amount of each codes and features. To reduce any validity issues through the analysis, it is important to implement a few strategies from John W. Creswell (2014: 201-203). The most important one is reflectivity of any bias, in which every tweet needs to be seen as equal. This needs to be even more stressed for Trump’s tweets, as he is much involved in the controversy of the concept of truth, post-truth politics, and denial of truth (‘fake news’) (Agostinone-Wilson, 2020). As an American citizen, it
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is even more important that the author views and categorizes Trump’s tweets the same as any other leaders’ tweets without any attitudes or judgement that could harm the analysis. Another strategy is cross-checking tweets to see if they are in the correct category and to find any missed features. The final strategy is peer debriefing of the analysis from colleagues to review the categories to find any mistakes or shifts in the coding structure for more accurate findings. Such strategies will strengthen the study to be valid and reliable for similar future studies.
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6. Findings
6.1 Overview
This chapter presents the findings of the data analyzed. It first describes the data from Trump’s characteristics and patterns found in his Twitter behavior, followed by an outline of the other leaders’ characteristics and differences. This is done to demonstrate the common patterns found from the majority of the leaders – as well as those leaders that stand out from the majority – to later compare to Trump’s Twitter patterns. All combined tweets totaled to 1,770; in which 658 tweets belonged to 13 foreign leaders since there were no tweets from Germany, North Korea, and China. Trumps tweets totaled to 1,012, where he comments on all 16 countries.
6.2 Trump’s Twitter Findings
This section presents President Trump’s characteristics and features, followed by a display of differe nt groups will be presented based on the amount of positive and negative categories.
6.2.1 Language What can be found first and foremost about the language in his tweets is the informality, through words and phrases directly or indirectly towards leaders and the audience which are not identified from the other leaders’ tweets (Ahmadian et. al, 2017).
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One example is identified in the final sentence of the tweet below.1
Apart from being infor ma l, the language in his tweets is conversational towards the audience. This means that he uses questions and phrases to engage with the audience, along with countries and actors, rather than solely being informative of a situation. Four examples of this can be seen below.2
1 Trump, 2018. 2 Trump, 2017, 2018, 2019, 2019. 37
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Tweets that included question marks totaled to 40, much more than the other leaders used in their tweets combined. Some tweets indicated questions being stated, but did not use question marks, thus they were not included. 591 tweets were identified that included exclamation points, being more than half of his combined tweets. As these marks are supposed to usually indicate excitement, Trump frequently uses them in negative tweets to show anger, frustration, and even threats, also in neutral tweets (334). This even goes for the use of capital letters for certain words or even all words in a tweet, which was identified in 139 tweets. Many of Trump’s tweets also present contexts and situations that are either hypothetical or uncertain, using words such as could, maybe, if would, etc. Moreover, 12 tweets end with phrases that indicate uncertain fore comings or for the audience to wait for upcoming information, such as, “We will see!”, “Stay tuned!”, and “Let’s see what happens!”, very similar to phrases heard in television programs. The tweet below reveals such a phrase.3
It is unclear whether these tweets show lack of knowledge from Trump, or if he is intentionally making the audience interested in the upcoming events, or even both. It could be related to a former profession of his as a television host for a reality television program called The Apprentice (Hall, et al, 2016: 76). Harsh words, insults, and name-calling were additionally identified, mainly found in the negative category. As the name-calling was towards enemies of the U.S., Trump would use even harsh and even insulting descriptions towards allies such as Canada and France. Moreover,
3 Trump, 2018. 38
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Trump would also frequently discuss various events, subjects, and actors – domestic and international – in one tweet, making it diffic ult to categorize and code. Therefore, many of his tweets have two to three codes. An example of this is viewed below.4
Some of the leaders’ tweets include parts of a speech that they want to emphasize. As Trump also does so, he also quotes many actors from television shows from Fox News, which either praise him or discuss issues about other countries. Those tweets that praise him, along with his own tweets that show self-praise totaled to 55. An example can be seen below.5
4 Trump, 2018. 5 Trump, 2019. 39
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In addition, the study also counted the number of tweets he used ‘I’ versus ‘we’ and ‘us’, meaning the U.S. and its administration. It was found that there are almost 100 more tweets that he uses ‘I’ than ‘we/us’, while many of the ones that had ‘we’ came from one of the fore coming phrases ‘we will see’. Subsequently, his tweets reflect much more narcissism compared to the other politica l leaders. Examples are displayed below.6
6 Trump, 2017, 2019, 2019, 2019. 40
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6.2.2 Features
As leaders used various features to inform the public about actors and events, Trump would use other features for similar but also different purposes. Very few hashtags and emojis were found in his tweets, in which most emojis found were from tweets about the UK and Japan, and the most hashtags were from tweets about Iran. However, instead of linking another account’s tweet to his own tweet, Trump is the only leader that retweets, with a total of 128. These retweets come from personalities from Fox News, other television actors, employees from his administration such as diplomats and the vice president Mike Pence, far-right actors in the U.S. and abroad, his children, and himself. These tweets are similar to those which he quotes from Fox News hosts and other actors that either praise him, agree with his decisions, or discuss a country. Even though some retweets include actual news clips to inform the audience, there are a few retweets that have been removed due to content that represents disinformation, such as anti-Muslim video clips. Trump is also the only leader that repeats a tweet, totaling to 34 tweets that have been posted a second time or even three times. Some of the tweets have been removed at first, and then written again due to spelling mistakes or incorrectly tagging the wrong account in a tweet, which occurred when he once attacked former British Prime Minister Theresa May but tagged another account with the same name (Meixler, 2017). However, the rest of the repeated tweets are used minutes, days, or weeks later, which could either show that he is attempting to keep the audience constantly informed, or if it is another narcissistic factor in which there is a certain pride in those tweets that he wants them to be seen again.
6.2.3 Trump’s Frame d Groups
Here the following subsections are groups of countries according to the number of positive and negative tweets from Trump. It is presented from the group of countries with mainly positive tweets (friendlies) towards the countries with mixed tweets (mixed relationships), and finally
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towards those with mostly negative tweets (non-friendlies). The names of the groups are influenced from Simunjak and Caliandro’s (2019) study.
6.2.3.1 Friendlies
This group represents the countries with very few (less than five) tweets in the negative category, namely: Japan, India, Saudi Araba, Israel, and Brazil. Only two countries had zero tweets in the negative category, which were Israel and Saudi Arabia. The tweets that were categorized as negative for all countries in this group were so because of Trump complaining either about devaluation of currencies or high tariffs on American goods, as seen in the example below.7
However, Trump would negatively portray the country rather than the leader. The neutral category was mostly coded as informative, telling about Trump’s own whereabouts, decisions, and meetings, and those coded as other are either his opinions and wishes on various people, deals, and situations, statements of what other officials said, or vague statements.
7 Trump, 2019. 42
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The positive category included tweets that mostly coded appreciation and congratulating, meaning that he is thanking leaders for visits or deals made and congratulating leaders on victories or other events in their countries. Another frequent code was other, which was generally his highly anticipated meetings with leaders, followed by retweets that praise him or his own opinions on countries or their leaders. Such a tweet with the code can be viewed below.8
6.2.3.2 Friendlies with Negative Tweets
The U.K. and France are in this particular group since Trump has mostly posted tweets about them in the positive and neutral category, but with more negative tweets identified than the previous countries. The neutral category was frequently coded informative and those that were coded other were mostly hypothetical statements or speculations about actors and events. The positive category included all the codes but most frequently was expressing friendship or alliance, congratulating, or saying that he ‘looks forward’ to meeting the leaders. The negative category coded mostly accusation, followed by taunt and other. With regard to France, Trump negatively tweets when receiving information about trade or military that he disapproves, or terrorist attacks and protests which he uses to describe how bad France is and that the U.S. must not become like that.
8 Trump, 2018. 43
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Moreover, Trump also tweeted negatively about Macron five times, two of them coded as taunts. One of them is displayed below.9
As for the U.K., Trump not only attacks Theresa May, but also Kim Darroch, former U.K. ambassador to the U.S., and even Sadiq Khan, mayor of London, which resulted in five taunt coded tweets. Trump criticized over the U.K.’s immigration, terrorism, Brexit, and actors who have critic ized him. Examples are displayed below.10
9 Trump, 2018. 10 Trump, 2017, 2019, 2019. 44
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6.2.3.3 Mixed Relationships
Venezuela, North Korea, and Canada belong to this group, in which there are about the same number of positive tweets as negative tweets (Canada: 18 positive, 22 negative; Venezuela: 9 positive, 9 negative; North Korea: 23 positive: 23 negative). The tweets categorized as neutral share the same codes and characteristics as the previous two groups. Positive tweets about Venezuela mainly coded support, as Trump was expressing support for the Venezuelan people and for the interim President Juan Guaido. The negative tweets were only about Nicolas Maduro and his government as a dictatorship. However, Trump would use Venezuela as a negative comparison to socialist ideas and actors – mainly democratic opponents – in the U.S, seen in the example below.11
North Korea’s positive tweets were mostly about Kim Jong Un and how Trump was ‘looking forward’ to meeting him, followed by Trump thanking Kim keeping their agreements, meeting each other, and letters sent. However, positive tweets did not start until the end of March 2018, when the two countries agreed to a summit. Beforehand, Trump’s first 41 tweets about North Korea included 24 negative, with frequent codes of threat, accusation, and taunt, with
11 Trump, 2018. 45
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much name-calling such as ‘Madman’, ‘Rocket Man’, and ‘Little Rocket Man’. Two examples are shown below.12
Positive tweets about Canada had various codes, mostly other, in which those tweets Trump would state his opinion or compliment on Trudeau, Canada, or the new trade deal with Canada and Mexico. Negative tweets largely entailed critical accusations towards Canadian tariffs on American goods or the previous trade agreement between Canada and Mexico (NAFTA), as seen below.13
12 Trump, 2017, 2018. 13 Trump, 2018. 46
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A few tweets had been coded taunt, in which Trump uses demeaning words to describe Justin Trudeau, like ‘indignant’, ‘meek’, and ‘mild’. What is perplexing though, is a couple tweets seen below have been partially coded negative and the other positive, which raises the question of sincerity. Two examples of such tweets are shown below.14
6.2.3.4 Non-Friendlies with Positive Tweets
This specific group is based on the larger number of negative tweets than positive. This even applies to countries which are primarily seen as allies, such as Mexico and Germany, but whom Trump has attacked. The other countries for this group include Russia, China, and Iran, who have not had good relations with the U.S. Positive tweets about Iran were only about the people and their civil protests, whereas positive tweets about Germany and China mainly were about their leaders. Such tweets were mostly complimenting and delighted anticipations about meeting Merkel and Xi Jinping, although most codes of friendship were found for President Xi. Mexico and Russia’s positive tweets varied, in which tweets about Mexico were about gratitude for the border control, the USMCA deal, and congratulating the newly elected president Andrés Manuel López Obrador. Tweets about Russia mostly involved Trump ‘looking forward’ to meetings with Putin, but also about the 2018 world cup in Russia, and Russia’s developments with Ukraine.
14 Trump, 2018, 2018. 47
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For the neutral category, Russia and China had more frequent codes of informative, whereas the rest had more frequent codes of other. Both codes reflected the same pattern as the tweets from the previous groups. Germany had the most negative tweets, with 25 out of a total of 41 tweets. All but one were accusations about migration and crime, not paying enough of its GDP to NATO, Germany’s gas deal with Russia, and having a less interest rate than the U.S. Negative tweets about China first were about how they were accused with not helping the U.S. enough with North Korea, and later became all about the trade war with the U.S. In many tweets, demonstrated in three tweets below, Trump would accuse China for ‘ripping off’ the U.S. in various harsh forms.15
Russia and Iran’s negative tweets mostly described Trump’s criticism over their involvement in the Syrian civil war. However, negative tweets about Russia are also about
15 Trump, 2019, 2019, 2019. 48
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Trump’s disapproval of their missiles and currency devaluation, along with other blunt accusations. As for Iran, the tweets were about Trump’s disapproval of nuclear testing along with the government’s response to the civil protests. There were additionally more frequent tweets with codes of taunt and threat, as seen below.16
Finally, Trump’s negative tweets on Mexico are most frequently coded as accusation (39 out of 49 tweets), which Trump frequently accuses Mexico for not helping enough with Central American migrants coming to the U.S., for ‘abusing’ the U.S. for their drug and human trafficking across the border, and alleged trade deficits. Threat codes have additionally been identified, in which Trump has frequently threatened to close the U.S.-Mexico border. An example is shown below.17
16 Trump, 2018, 2019. 17 Trump, 2018. 49
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6.2.3.5 Non-Friendlies
Syria is the only one that Trump has tweeted solely neutral and negative, in which the negative category has twice as many tweets as the neutral one. Out of the eight neutral tweets, only three were informative, while the rest as other, as such tweets were indirectly about Syria or Trump’s beliefs or suggestions about the war in Syria, and one even was a removed retweet due to its misinformative content. The negative tweets mostly were coded as accusation and concern over attacks over the Syrian people and has even name-called President Assad ‘Animal Assad’, as seen in the two tweets below.18
Although most of these negative tweets are about Syria in general or Assad, a couple were additionally about Syrians as migrants, but portrayed in a negative way. One was another removed tweet that posted disinformation – more specifically, a retweet from one of the accounts from new station Fox News, stating that grateful Syrians will name their children Donald (Trump Twitter Archive, 2020). It thus becomes confusing whether Trump’s concerning tweets are genuine.
18 Trump, 2018, 2018. 50
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6.3 Findings from Foreign Leaders’ Tweets
Here, the analysis will be grouped in the following: friendlies (India, Japan, Brazil, Canada, the U.K, France, Israel, Saudi Arabia), mixed relations (Russia, Venezuela, Mexico), non-friend lies (Iran, Syria), and those who do not have Twitter accounts or have not posted anything about the U.S (Germany, North Korea, China). Similar to the section above, they have been grouped is in accordance with the amount of codes about the U.S. and Trump in their tweets, also grouped as ‘friendlies’, ‘mixed relationships’, and ‘non-friendlies’. It is important to note that some countries have both a president and a prime minister, which both of their tweets have been analyzed. This allows us to recognize whether one leader’s Twitter behavior differs from the other leader, thus showing any effect on different social and political values between actors in the same country. Moreover, some countries have elected new leaders to take office, meaning that both of their tweets during their time in office are additionally analyzed.
6.3.1 Friendlies
These countries indicate the best relations between the U.S., with mostly positive tweets and very few negative. Even though Saudi Arabia’s King, Salman bin Abdulaziz Al Saud, only tweeted once, and the U.K.’s former prime minister Theresa May only three times, they were only positive. All countries’ positive tweets totaled to 253 with a 31.6 average, much higher than the neutral tweets, totaling to 97 with a 12.125 average, and only 8 negative tweets (7 from France and 1 from Canada). Those who have tweeted the most is Israel’s prime minister Benjamin Netanyahu with 139 tweets, followed by the president of France, Emmanuel Macron, with 46 tweets, and third being India’s prime minister Narendra Modi with 37 tweets. Starting with the positive tweets, apart from King Salman and Theresa May who only posted positive tweets, the ones who posted the most positive tweets about Trump and the U.S. was both the prime minister and the president of Israel. President Reuven Rivlin tweeted 15 times, all being positive, and Netanyahu’s positive tweets were 124 out of 140. Afterwards is Prime Minister Modi, with 30 positive tweets out of 37. The rest had around half of their total
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Kajsa Hughes 19940526-2867 Political Science: Global Politics tweets as positive. The code that was the most frequent in total was appreciation, with 83 tweets, which entailed leaders giving thanks to another in their tweet, seen in the tweet by India’s Prime Minister below.19
The second most frequent code was alliance/friendship, with 70 tweets, where leaders describe the good relations between themselves and the U.S. What can be seen from Macron’s tweet
above20 is that a photo has been included, which is very common for such leaders to use in their tweets. Many of the photos include leaders shaking hands or embracing each other, smiling,
19 Modi, 2017. 20 Macron, 2018. 52
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having meetings, infor ma l talks, ceremonies, deal signings, and even playing golf, as prime minister of Japan Shinzo Abe tweets on some occasions, as seen below.21
Tweets including photos totaled to 100, whereas those with videos were 32. The videos were somewhat similar to the photos, showing visits to the U.S. or welcoming Trump to their country. They were mainly however showings of press conferences or meetings. 35 tweets included hyperlinks to videos of speeches or press conferences, government websites with briefings, and to other tweets from Trump and other American officials, and even their own tweets but in their native language. For instance, Justin Trudeau, prime minister of Canada, tweeted most hyperlinks to their government page that would inform the audience about certain events, statements, and decisions.
21 Abe, 2017. 53
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This can be seen in one of his tweets below.22
Hashtags were also used in 26 tweets, where leaders would tell about summits like G7, events, places, deals, and even friendship with the U.S. Moreover, emojis, which are “small pictures used on smartphones, tablets, and other electronic devices to convey emotion or represent an object or symbol more succinctly than a text statement” (Webopedia, 2020), were used in 44 tweets, mainly as pictures of their flag with the U.S. flag. Jair Bolsonaro, president of Brazil, would occasionally use a ‘thumbs up’ or handshake emoji to additionally show good
22 Trudeau, 2018. 54
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relations with the U.S to the public. Two examples of tweets with emojis and hashtags are displayed below.23
51 tweets (33 from Israeli leaders) included exclamation points establish excitement. However, only four out of eight countries (Israel, Brazil, India, Japan) used exclamation points, as traditional diplomacy is not supposed to create dramatics. Furthermore, no country used capital letters for an entire word or sentence in their positive tweets. Another frequent code was agreement, with 43 tweets, in which the two leaders have agreed on a decision, deal, or strategy through discussions. Other codes such as condolences and support would arise, in which leaders would send their sympathy to the U.S after natural disasters, mass shootings, and even the death of a former U.S. president. Leaders would also send their congratulations, which was another code, mainly for Trump’s presidential inauguration, or they would tell about the congratulations received from Trump after winning an election. Finally, the 20 tweets that were coded as other involved welcoming of Trump and/or
23 May, 2019; Bolsonaro, 2019. 55
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other U.S. officials, positively anticipating a meeting with Trump, or other ways of describing good relations with the U.S., seen in an example below.24
The neutral tweets only had two codes, the most frequent being informative with 77 tweets. Such tweets are made to inform the audience about a leader’s travel to a country, along with descriptions of their visit, meetings with Trump and other American officials, summits involving the U.S. and other countries, decisions made with the U.S., and even issues between the countries that they are trying to solve. Tweets that are coded as other involve statements that are not informative but are presented as comments and beliefs from leaders on Trump and the U.S., and even some that reflect obscurity, as seen in Macron’s tweet below.25
24 Salman, 2017. 25 Macron, 2018. 56
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The neutral category continued to include pictures, videos, hyperlinks, and hashtags, but were fewer than the positive category. Moreover, these features included were similar to the ones in the positive category, meaning to inform the audience of agreements, events, and so on. Bolsonaro, however, has two tweets including hyperlinks to video clips from television news stations, one which was from Fox News, an American conservative news station. Furthermore, Bolsonaro is the only leader that has used an emoji in this category and is the only one who has stated questions in a tweet from this group. Lastly, the only leader to use an exclamation point – an unusual feature for this category – is Israel’s Prime Ministe r, Benjamin Netanyahu, used when informing the audience of the U.S. embassy opening in the newly declared capital of Israel, Jerusalem.26
Canada and France share tweets that express disappointment with President Trump’s decision to withdraw from the Paris Agreement, an agreement that deals with tackling greenhouse-gas emissions (unfccc.int, 2020). Yet, the language from the tweets still prevent formality, as seen in an example below.27
26 Netanyahu, 2018. 27 Macron, 2018. 57
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However, one tweet from President Macron in 2018 shows possible sarcasm, when using the hashtag #makeourplanetgreatagain, a phrase that derives from Trump’s campaign slogan ‘Make America Great Again’. Other negative tweets from Macron continue to express disappointment and concern from decisions by the U.S. government such as declaring Jerusalem as the Capital of Israel, starting a trade war with France, and withdrawing from the Joint Comprehensive Plan of Action (JCPOA), an agreement involving Iran’s nuclear program (European Council, 2020). One of Macron’s tweets expressed an indirect taunt or passive aggressiveness about Trump during the 2018 G7 Summit, telling how Trump is isolating the U.S. from the other members for its own believed advantage.28 The translation is found in the footnote below. 29
The tweet includes a photo of the two leaders, yet it shows no smiles, handshakes, or embraces, as seen in many of the photos from the other categories, and additionally uses dark lighting, which generally represents a darker mood (Luhtasela-el Showk, 2020). However, the language in Macron’s tweets do not express any aggression nor dramatics by still being informative, but with more of a serious tone. Two of his tweets additionally include videos of him speaking to the public, as well as using a couple of hashtags, such as #parisagreement.
28 Macron, 2018. 29 Translation: “At # G7Charlevoix, President Trump saw that he had a united front facing him. Finding yourself isolated in a concert of nations is contrary to American history.” 58
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6.3.2 Mixed Relationships
This group shows the countries (Mexico, Russia, and Venezuela) with a diverse politica l situation with the U.S. To begin with the basic information, most tweets fell into the ‘negative’ category with a total of 57 tweets (2.6 average), followed by neutral tweets totaling to 54 tweets, and 41 positive tweets. The leader that has tweeted the most is contested president of Venezuela Nicolás Maduro with 36 tweets, followed by President Vladimir Putin of Russia with 34 tweets. Mexico, with solely one negative tweet, is in this group based on its relations with the U.S. Even though the two countries are well established trading partners with each other, illegal immigra tio n and ille ga l drug traffick ing from Mexico to the U.S. has caused differences (mainly from the U.S.), which enhanced during the 2016 U.S. presidential election (Becker, 2016). Enrique Peña Nieto was president until the end of 2018, when Andrés Manuel López Obrador was inaugurated. The only indirect negative tweet is from López Obrador, he expressed concern over the tariffs that Trump wants to impose on Mexican goods due to the inflow of Central American migrants that have passed through Mexico into the U.S. (Shear, et. al, 2019). The tweet is still formal and presents itself as still informative. Peña Nieto posted two positive tweets, one coding condolences for the 2017 Las Vegas mass shooting, and the other expressing agreement with the USMCA deal. López Obrador posted eight, coding agreement and friendship also about USMCA. Neither of them included hyperlinks, and no emojis nor exclamation points were used for any category. Peña Nieto used a hashtag also to inform about the new deal, and López Obrador uses a few pictures of various meetings and discussions with other actors. The neutral category included mostly informative codes about various meetings with American officials, telephone conversations, and even one with a hyperlink to a letter to Trump about the imposed tariffs. Russia has both a president, Vladimir Putin, and a prime minister, Dmitr ij Medvedev. Putin’s Twitter account is presented as if it is written by staff members and is presented more as a news medium, as it is pointed out in the description of his account “Offic ia l Kremlin news” (President of Russia, 2020), whereas Medvedev’s account provides a more personal representation. There were only six positive categorized tweets, only one from Medvedev
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expressing condolences over the death of former U.S. President George Bush, while the rest from Putin’s account found codes of agreement, condolences over various tragedies, and one coded as other found below, seen as a type of compliment.30
The tweet above is the only one that has a hashtag included in the category, and no emojis, exclamations points, videos, and pictures were used. Each leader used one hyperlink that sends to the government websites. Putin’s Twitter account had the most neutral posts, in which most of them were informative regarding conversations with Trump. Neutral tweets from Medvedev were more coded as other, in which they express his thoughts or his instructions to the audience, or further vague statements. One example is shown below.31
30 Putin, 2017. 31 Medvedev, 2019. 60
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More hashtags were used for this category to show different forums, deals, and persons, and even an emoji of some sort of a ribbon or sash was used in a tweet from Putin. No videos nor exclamation points were included for this category, but more pictures of themselves or Putin friendly engaging with Trump, as well as hyperlinks to the government websites and their own Facebook posts. Medvedev posted almost twice as many negative tweets, compared to Putin’s account, mainly coding concern and disappointment over decisions made by Trump and his administration such as imple me nting policies that would benefit the U.S., implementing sanctions on Russia, declaring an interim president for Venezuela, violations of treaties, and withdrawals of agreements. Although all negative tweets were formal as primarily being informative through hyperlinks and hashtags, Medvedev posted a few tweets showing some taunting, and has even stated a question, something that is not commonly found from leaders’ tweets. Such tweets can be seen below.32
In the case of Venezuela, the country’s government situation is more complicated than the rest as the elected president Nicolás Maduro, is no longer recognized as president by some countries and supranational organizations (Reuters, 2019). The Trump administration has even recognized an interim president Juan Guaido in January 2019 (Pompeo, 2019). Thus, both leaders’ Twitter accounts have been used for the analysis.
32 Medvedev, 2019, 2019. 61
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Starting with Maduro, he did not mention the U.S. nor Trump until the beginning of 2018. His two positive tweets express the friendship between Venezuela and the U.S. people, whereas the U.S. government is the enemy. These tweets included videos of him speaking to the audience. His neutral tweets are mixed, meaning that they either inform of meetings and speeches with a couple pictures and a video, condemning horrific actions in an American state, informing of historical events, or asking Trump for dialogue.33,34
The tweet above also hides some negative coding, in which he indirectly shows that the Trump administration prioritizes aggression over dialogue. No emojis, hyperlinks, and exclamation points were included while few hashtags describing news or locations were used. His most frequent tweets (31) were categorized as negative, which most codes found were concern and disappointment over the American intervention. He uses much more exclamation points to express solidarity and patriotism for the people of Venezuela and include s many more pictures and videos of him speaking or demonstrating. After the U.S. recognized Guaido as president, Maduro’s tweets become somewhat more aggressive, expressing that American imperialist government is contrary to Venezuelan values and is unwanted. He even
33 Translation: “@RealDonaldTrump campaigned promoting non-interference in the internal affairs of other countries. The time has come to comply and change his agenda of aggression for one of dialogue. Dialogue in Caracas or Washington DC? Time and place and I'll be there.” 34 Maduro, 2018. 62
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uses hashtags such as #HandsOffVenezuela and #NoMoreTrump, and even phrases like “Yankee Go Home!”, in which yankee is considered an insulting name-calling (Fornwalt, 2013). Juan Guaido has posted no negative tweets, but mostly positive ones that mainly express gratitude for the support and humanitarian aid from the U.S. The other very few codes were alliance, one agreement, and one congratulating the U.S. for their national holiday. No emojis were used for any category and only a couple of pictures were used, but many hyperlinks to tweets from other U.S. officials and hashtags were used to still be informative towards the audience. A few exclamation points were used to express excitement over the aid received.35,36
Lastly, his six neutral tweets were all informative and also included a few pictures, videos, hyperlinks and hashtags of actors, dates, and phrases about supporting the Venezuelan people.
6.3.3 Non-Friendlies
This group (Iran and Syria) has two different political histories with the U.S., but both share the idea that that the U.S. government is either an enemy or disagreeable. Moreover, no positive tweets were found from either country. The Twitter account of Bashar al-Assad, president of
35 Translation: “We thank the Speaker of the #USA Congress, Nancy Pelosi @SpeakerPelosi, for her support in restoring democracy in Venezuela and #Humanitarian Aid for our Nation. By recognizing our work, he exalts the noble struggle of millions of Venezuelans. We continue!” 36 Guaidó, 2019. 63
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Syria, is similar to Vladimir Putin, meaning that his tweets are written like news reports through his comments, as seen in the tweet below. All his tweets include hashtags of his name and the news mediums he has been in contact with, as well as other actors involved such as countries and leaders. Only four neutral tweets were found from Assad, three of which were coded as other due to the statements being more speculative countries and leaders, as seen in an example below.37
The last neutral tweet was coded informative, with a hyperlink to a YouTube video of his press interview. The negative tweets were mainly coded as accusation, as Assad claims in many of his tweets that the U.S. is responsible for the support of ISIS, a terrorist organization formerly located in Syria and Iraq. He additiona lly claims that the U.S. and other Western countries are destabilizing Syria, and not fighting against terrorism enough. Some of the tweets in a similar fashion were coded as taunt, in which he claims frequently that Trump and the U.S. are being a bully and playing a game with Syria while other Western countries are following the lead, seen below.38
37 Assad, 2017. 38 Assad, 2017. 64
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None of the tweets included exclamation points, and only one picture of himself speaking to the press was included. Iran has not only a president, Hassan Rouhani, but also a supreme leader, Ali Khamenei. Rouhani only posted 11 tweets, whereas Khamenei posted 111 times. Rouhani posted four neutral tweets, in which only three were coded as other due to the statements reflecting a suggestion of negotiations and bilateral talks with different parties. However, one was coded as informative, but included a sarcastic message.39
The sarcastic message involves the withdrawal of the U.S. from the Iran Nuclear Deal, as well as other members of the deal not complying to Iran’s conditions, leaving Iran to pursue their own goals against the deal. The tweet above shows the only one with an attached link to an earlier tweet, and only two include hashtags about the deal and the UN General Assembly. Khamenei’s neutral tweets also totaled to four, with similar codes to Rouhani’s tweets, meaning mainly suggestions. No sarcasm was identified, and only two pictures with other leaders were included.
39 Rouhani, 2019. 65
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As for the negative tweets, Rouhani’s mainly coded as accusations, with claims over various matters from disrespecting Palestine to violating international laws. One tweet condemns the U.S. missile strike towards Syria, and another expresses disappointment over Trump’s UN General Assembly speech. The only dramatic tweet of his was another accusation involving a U.S. official, using both an exclamation point and question mark40.
Khamenei’s negative tweets are also mainly coded as accusations, but finds much more taunting, exclamations points, and questions asked. Like Assad, Khamenei claims that the U.S. is responsible for ISIS and other terrorist groups, in addition to being a bully towards other
40 Rouhani, 2018. 66
Kajsa Hughes 19940526-2867 Political Science: Global Politics countries in the region. However, Khamenei takes a more dramatic step in attacking Trump and his officials through many of his tweets as seen in three examples below.41
Not only does Khamenei use name-calling but describes the U.S. along with Trump and his administration as untrustworthy and arrogant. Moreover, he also frequently points out the discrimination of immigrants and African Americans in the U.S., showing that the country is hypocritical towards human rights issues. Pictures show himself giving speeches or meeting with different leaders and actors, while the few hyperlinks and videos are informative. Finally, Khamenei uses many hashtags to shine light on countries, actors, organizations, events, and agreements to still inform the audience about various subjects.
41 Khamenei, 2019, 2019, 2019. 67
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6.3.4 Leaders without Twitter
As explained earlier in the previous chapter, leaders of China, Germany, and North Korea do not use Twitter, as the platform is blocked in China and North Korea (Bamman, et. al, 2012; Talmadge, 2016), and Germany’s Chancellor Angela Merkel has not tweeted since January 16, 2017, prior to Trump’s inauguration. Therefore, the study has used news articles in which leaders from these countries have responded to Trump’s tweets about them in order to continue using directive content analysis to avoid additional methodological issues. Merkel has made some comments at a couple of instances through meetings with press and a speech. First, is from Trump’s series of tweets during the 2018 G7 summit, heavily criticizing multiple countries including Germany, as well as stating his withdrawal of G7 agreements via Twitter. Merkel commented on his behavior as “sobering and a little depressing” (Eckhardt, et al. 2018; Deutsche Press-Agentur, 2018). Another instance, also in 2018, when Trump attacked both France and Germany after French president Macron called for a European army, to which Merkel supported Macron through a speech to the European Parliament (Chazan & Brunsden, 2018). Other instances of Trump attacking Germany included their immigration policies and alleged trade deficits, but there were no public responses from Merkel. Responses from North Korea and its leader Kim Jong Un have a different story to Germany. Trump started name-calling Kim Jong Un as a ‘madman’ and ‘Little Rocket Man’ in September 2017, followed by threatening North Korea in his speech at the UN General Assembly and imposing further sanctions on the country. This led to a statement from Jong Un, saying “I will surely and definitely tame the mentally deranged U.S. dotard with fire,” and that the U.S. would “pay dearly” for the sanctions, in which the term dotard means “a word used to describe an elderly person in a state of senile decay” (Faulders, 2017; bbc.com, 2017). Another one of Trump’s tweets later in 2018 threatened North Korea by claiming that his nuclear button is bigger than theirs, followed by a statement from the country’s state-controlled news agency, calling Trump a ‘lunatic’ and a ‘loser’ (Noack, 2018). Other responses towards Trump’s tweets and statements came from North Korean officials. Trump has additionally criticized China over Twitter frequently by not taking more action over North Korea in 2017. Like North Korea, the official state-controlled news agency of
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China, Xinhua, made a statement, saying “Trump is quite a personality, and he likes to tweet, but emotional venting cannot become a guiding policy for solving the nuclear issue on the peninsula”, and that the U.S. should not “stab China in the back” (Maizland, 2017). During Trump’s trade war with China, later in 2019, he posted a series of tweets announcing that he is drastically raising tariffs on Chinese goods. The government responded with a strong opposition statement calling the move a “unilateral approach” and a “trade-bullying tactic” (CNN; 2019). Like Angela Merkel, China has been mostly quiet and irresponsive to Trump’s tweets. However, it has been increasingly recognized that Chinese officials abroad are starting to tweet in a Trump- like manner, meaning more aggressive and directive (Kuo, 2019; Toosi, 2019).
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7 Analysis
7.1 Political Context
The findings have shown that the political context between the U.S. and other countries, during and even before Trump’s presidency, has influenced the language used in every leader’s tweet. As discussed earlier, alliances and similar ideologies have positive effects on the political context between countries, which shows how the Western countries have mostly neutral and positive tweets about the U.S. Moreover, non-Western countries such as Japan, India, Israel, Brazil, and Saudi Arabia have shared negotiations, coalitions, and similar preferences, which has led their leaders to also tweet mainly in positive and neutral categories. However, one of U.S.’s allies, France, with President Macron elected shortly after Trump’s inauguration, has already been critical about his administration and policies, to which there are more negative tweets identified from Macron. The tweets revealed that Macron believes in international coordination, while Trump focuses much more on protectionism and isolation of the U.S., which leads to two ideologies clashing. The clash in ideologies and strategies are found in many tweets from Venezuela’s Nicolas Maduro, Iran’s leaders, and Syria’s Bashar al-Assad. Maduro claims that the U.S. is imperialistic, which is the opposite of Venezuelan and Bolivarian values. Supreme Leader Khamenei claims that the U.S. is racist and anti-Muslim, and Assad believes that the U.S. is not helping Syria enough and has created ISIS. Trump’s tweets about all countries and its leaders are much more varied in codes, but one can still identify certain patterns linked to traditional U.S. political context, as well as his own. His protectionist trade ideology reflects much onto his decision-making and statements on his tweets, which is why he even attacks his closest allies. Moreover, he believes that certain allied countries have issues with migration, and that it is linked to terrorism and crime, which is another reason for negatively portraying those countries to show that the U.S. cannot be the same.
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By analyzing Trump’s tweets, it can be concluded that he favors far-right ideologies, which may explain why he is on friendlie r terms with leaders such as Brazil’s Jair Bolsonaro, who shares similar ideological beliefs, and has been heavily criticized by other world leaders (Chagas-Bastos & Franzoni, 2019). He is very negative towards Maduro’s ‘dictatorship’ and criticizes Iran and Syria for attacking their people. Yet, he has been friendly with dictator Kim Jong Un, as well as former enemies such as Russia, and even countries with poor human rights conditions such as Saudi Arabia. It can therefore be suggested that Trump’s tweets are based on who he personally likes or dislikes.
7.2 Events
Leaders have expressed mainly positive codes when having meetings or summits that include the U.S., the only time allies have expressed negative codes are solely from events such as decisions from Trump and his administration to leave various agreements, such as the Paris Agreement. However, such change in codes are very brief and leaders continue to tweet in a neutral or even positive manner.
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Whenever Trump has received information about any event, this can immediately cause any change in codes in his tweets. The biggest change is with his relations with North Korea’s Kim Jong Un, which started from threats and taunts to gratitude and friendship, tweets of peace (seen in the tweet below42) after their first summit in June 2018.
More common instances are when Trump ‘hears of’ nuclear weapons/missile testing and attacks from countries with poor relations, which lead to even more dramatic tweets. Moreover, Trump frequently tweets in negative manners after witnessing statements by other leaders – both friend or non-friend – or receiving information about joined agreements and coalitions made by countries. Thus, it shows that events are more of a sensitive matter to Trump than the other leaders.
42 Trump, 2018. 72
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7.3 Enemy Images
Trump has in a way made the other countries and its leaders appear like enemies in his tweets, apart from Saudi Arabia and Israel with no negative tweets. Allie s with trade policies and practices, coalitions with other countries, and statements that are disapproved by Trump, are portrayed as somewhat unfair or even betrayal to the U.S. Moreover, whereas Trump claims to be concerned about the citizens in Iran and Syria, as well as having a good relationship with Mexico, his tweets about migrants from those countries seem like enemies. Examples are shown below.43
Nicolas Maduro of Venezuela and President Rouhani along with Supreme Leader Khamenei of Iran both share the pattern of making the U.S. their enemy by claiming in their tweets how American values, attitudes, and measures are harmful to their own values. Khamenei, however, even though his frequent tweets show threats and accusations of evil towards Trump and his administration, at the same time he tweets show that Trump is not an enemy but a clown. This was similar to North Korean responses about Trump’s tweets, stating that he is a delusiona l old man. China additionally does not seem to take him seriously in their responses, calling his tweets ‘emotional venting’. However, China did call the U.S. a bully because of their trade policies against China. Russia similarly portrays the U.S. the same in both Putin and Medvedev’s
43 Trump, 2017, 2017. 73
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tweets, explaining the sanctions against them and U.S. pressures on other countries. This shows that Trump is not necessarily portrayed as an enemy, but rather the U.S..
7.4 Change in Social Norms?
To know whether Trump has changed the traditional Twiplomac y norm requires a review between his behavior compared to the others. Based on the background information and previous literature reviewed earlier, combined with the findings of most world leaders’ tweets, the patterns of expected behavior generally include formality and politeness in their language. Moreover, even though most leaders attempt to inform the audience of their whereabouts, meetings with other leaders and/or officials, deals or issues with other countries, etc., there is much vagueness in their stated tweets in order to keep a neutral stance with other leaders and to not give too much confidential information away. Trump, however, is almost the opposite by expressing impoliteness, dramatics, informal and shorter language, and frequent bursts of accusations and disinformation. However, this online behavior is a common online sociality norm discussed earlier in the paper in which people have become informal, personal, and emotional on social media. Because Trump has already had a personal account on Twitter since 2009 and started managing his own tweets sometime after 2011, he has long before his presidential campaign tweeted according to that norm (Harris, 2016). Moreover, his previous work before running for president has been occasionally reflected in his tweets, even as president. Therefore, Trump is a unique case compared to other world leaders through their tweets. According to Sarina Theys (2017), states conform to a specific identity and comply with the norms associated with that identity based on an expectation of a certain behavior or action acceptable by the perceived majority (ibid: 38). Moreover, Theys explains the lifecyle of a norm, arguing that a norm becomes a norm when it is “an expected behaviour when a critical mass of relevant state actors adopt it and internalise it in their own practices” (ibid). The U.S. throughout its history has been influential to other countries through trading, international cooperation, aid, etc., so it only is expected that other foreign leaders would comply to the leader of an influential
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superpower. However, due to Trump’s uniqueness, there are not many signs pointing towards compliance and social approval. The only leaders showing aggressiveness slightly similar to Trump are Iran’s leaders and Venezuela’s Nicolas Maduro, and the only leader with the frequency of posting tweets similar to Trump is Israel’s Benjamin Netanyahu. However, as presented in the findings, Chinese officials have been recognized from their informal and impolite tweets. This could be a reflections of a social norm starting from new motivations. As these leaders have witnessed Trump, and as they are allowed to used Twitter outside of China, this allows them to promote their policies through tweets in such a manner. However, these examples are the very few out of all the findings of leaders who continue to tweet in their perceived expected behavior.
7.5 Framing Theory and Its Techniques Applied
The concepts applied in the findings above are connected to framing and how Trump and the other leaders want the audience to see each other. The loudest leaders on Twitter frame others negatively for their own benefit of embracing their values. President Macron of France values cooperation with other countries and strategies to tackle environmental issues, thus negatively frames Trump and the U.S. for doing the opposite. This could be a tactic so that the audience – both leaders and citizens of other countries – might exclude the U.S. and cooperate with others elsewhere. Supreme Leader Khamenei of Iran frequently frames the U.S. as a failure for Iran’s Revolution, and that U.S. measures towards Iran will not weaken them, for the purpose of keeping its citizens happy with the Iranian government.
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Such a tweet can be seen below.44
Trump’s tweets about unfair trading practices with many countries demonstrate his protectionist values for the benefit of American workers. Although this could be a personal tactic for re-election. Moreover, Trump tends to scapegoat other countries for his own mistakes, such as blaming Germany and France for not helping Ukraine more when he was impeached for alleged abuse of power by using the Ukrainian president for his own benefit (Fandos & Shear, 2020). One those tweets is displayed below.45
44 Khamenei, 2018. 45 Trump, 2019. 76
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All framing techniques listed earlier in chapter four have been identified in various tweets. Trump would use problems in different countries as a metaphor for things that the democrats want, as seen in the previous chapter when Trump would compare certain democrats to Venezuela’s ‘socialist regime’. Moreover, Khamenei would use Trump and his administration as a metaphor for the evil in the U.S., while Maduro would compare the American involvement in Venezuela to the Vietnam War. Both are seen in the tweets below.46
The telling of stories was also identified in certain tweets, in which leaders would describe historic moments that have great importance to their country. Khamenei would frequently tweet about the Iranian Revolution and the freedom from the U.S. due to its historic importance. Maduro also posted tweets of historic socialist movements against the American imperialism, thus showing the significance of socialism as a value in Venezuela.
46 Maduro, 2019; Khamenei, 2019. 77
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Both Trump and Macron tweeted during their visits in each other’s countries to show their historical alliance along with how both countries fought for freedom during their respective revolutions, as seen below.47
Historical alliances with the U.S. have also been embraced in tweets such as the U.K., Israel, Canada, and Japan. Thus, stories can frame a country negatively and positively. Traditions and artifacts were only seen in tweets from Israel’s prime minister, Benjamin Netanyahu, who takes pride in Israel as the ‘original’ homeland for the Jewish people, which has been a long fight with Palestine.
47 Macron, 2018, 2018. 78
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With the help of U.S. support, such tradition has led to declaration of land and capital cities in Israel’s favor, thus motivating Netanyahu to frame the U.S. positively in his tweets, as seen in the example below.48
Trump’s much wanted border wall between the U.S. and Mexico is also seen as an artifact since it shows a symbol of Trump’s far-right values of anti-immigration. Finally, slogans and catchphrases were found in Trump and Nicolas Maduro’s tweets. Maduro expresses anti-American involvement in Venezuela, such as “no more trump” and “yankee go home”. This negatively frames Trump and his administrators in a memorable way through aggression and name-calling as a way to show unwanted American intervention in a country, which could thus take an effect on other countries that are also intervened by the U.S.. Trump uses both repetitive nicknames and phrases that have become a component of his presidency. This again includes Kim Jong Un’s “Little Rocket Man” nickname, along with Bashar al-Assad’s “Animal Assad”. However, Trump occasionally calls Benjamin Netanyahu “Bibi”, as a way of expressing friendship. Trump additionally uses phrases for two types of situations in his tweets. The first is when he is expressing U.S. trade protectionism, by claiming that certain deals or countries are
48 Netanyahu, 2019. 79
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being ‘unfair’ to the U.S. or are ‘ripping off’ the country. The second involves the U.S.-Mexico border in which he frequently states about ‘closing the border’ and how the U.S. ‘needs wall’, indicating his wanted border wall between the two countries. Not only are these phrases memorable because of their frequency, but the dramatics in his language as well as the grammatically constructed way he tweets could even be relatable to people who agree with him.
7.6 Realist Constructivism Revealed in Tweets
It can be discussed whether or not there is more to the pattern of these leaders’ tweets, such as the balance of power. From a realist perspective, the ‘showing off’ of alliances through Twitter could be a tactic to warn other countries to not start a conflict with their ally. Trump has also warned Gaza to not attack Israel through a tweet, further demonstrating the power of alliance. Moreover, the imagined world hegemony that the U.S. perceives itself to be in, described by Huntington (1999), is also reflected in Trump’s tweets about trade. According to his tweets, trade enemies include China, Mexico, Canada, and France, to which whenever Trump receives information that the U.S. is doing better than its trade enemies (true or false), he will boast about it on Twitter to show that the U.S. is ‘winning’, as if it were a game. This is an example of the forceful hegemonic attitude Huntington and Herring (2008) explained. It can be also a reason why most of the other leaders do not tweet in the same manner as Trump towards the U.S. in risk of creating a conflict with a major power, especially when most of their Twitter accounts are managed by a staff member. However, the way that Iran’s Khamenei has tweeted about Trump and his administration has not really escalated in any conflict. The U.S. has sanctioned Iran, but for other reasons. Showings that there needs to be constructivists elements involved as well. Such elements have also been identified in Trump’s framings of other countries and their leaders, as well as the change in online diplomatic behavior. Countries that are based on ‘un-American’ principles are already perceived as something negative and can affect foreign policy agreements and media framings such as Trump’s Twitter posts, thus showing the intersubjectivity clash between politica l leaders.
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As reviewed earlier, realist constructivis m describes the change in social structures depending on leaders’ decisions according to their political values. Trump’s politica l values and new friendships with leaders of countries with either extreme far-right values or poor human rights conditio ns, all reflected in his tweets, have changed relationships with traditional allies, as well as isolating the U.S. even further from the rest of the world.
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8. Conclusion
8.1 Summary
This study aimed to explore any changes in framing in Trump’s and other leaders’ Twitter posts, to see what factors cause such changes, as well as comparing the online behavior between Trump and the rest of the leaders to see if Trump has created a new norm that challenges traditional Twiplo mac y. It is necessary to study such a topic that can have a negative impact on power relations, such as escalating threats and even armed conflicts. The previous literature that has been reviewed provided the research knowledge about diplomacy through social media, framing, and concepts that affect political agendas, yet did not specify on the areas of diplomatic consequences from changes of frames, nor social norm changes on Twitter. Theories of realist constructivism, social norms, and framing, along with concepts of political contexts, events, and enemy images, created a wider-ranged framework to reveal the complexities of various powers communicating about others. Directed content analysis of the tweets presented a vast number of findings, revealing the patterns of the leaders’ Twitter characteristics and framings. It showed that, apart from Trump, most leaders except for three (Maduro, Khamenei, and Assad), mainly tweet in a formal and informative manner, with barely any negative codes. Leaders unfavorable of Trump and the U.S. showed in their tweets many accusations, disapprovals, and threats, yet their language continued to mainly show formality. Tweets from President Trump revealed a uniqueness in which his perspective of informing the audience has been blurred with entertainment and self-admiration, through dramatics and retweets. The findings support the theories and concepts, showing that all concepts having an effect on current and changed framings. Furthermore, although the findings from Trump’s tweets reflect the imagined hegemonic attitude of U.S. diplomac y, the rest of the leaders choose to continue to tweet in the same formal and informative manner, proving no change in social norms but also as a lesser power tactic. This concludes that the answer to the central research question is that Twiplomacy is so far not powerful enough to alter power relations, even Trump’s unique Twiplomacy, and requires more factors such as meetings, coalitions, disagreements, speeches,
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and even press conferences to do so. However, it could mainly depend on who is elected in the future and whether everyone will choose to have Twitter, as a handful in this study cannot or chose not to have a Twitter account. Therefore, the results have revealed that Twitter seems to not be taken as seriously by most of the leaders for now, which could eventually change in the future.
8.2 Evaluation
Even with the large amounts of find ings, a couple of limita tio ns still arose. Firstly, there is much difficulty to know who is tweeting. Various works and information on Twitter have revealed whether it is the leader itself, the staff, or both who are creating the posts. This becomes an issue in which one does not know whether to base this study off the actual social human behavior of these leaders or not. Knowing whether the leader itself or its staff members are writing the tweets can help us further understand the behavior and political agenda of a specific actor. Second, those leaders included in the study that lacked a Twitter account could have revealed different findings if they did have an account. At the same time though, it proves that Twiplo mac y is not popular enough for leaders to start tweeting in the same manner as Trump. These limitations stress that there is a need for more research on this topic to gain more knowledge of any changes in Twiplo mac y.
8.3 Interpretation
When comparing to the studies from the literature review, the results from this specific study provided more detailed insights to the use of Twitter by political actors, their framings through the platform, and various concepts effecting their tweets. The digita l diplomacy literature provided basic information about the benefits and disadvantages of using social media as a new diplomatic tool to inform the public (Verrekia, 2017; Chhabra, 2020). Moreover, Simunjak and Caliandro’s (2019) study of examining leaders’ engagement on Twitter has created a base for
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this specific study to provide an in-depth continuation. This has led to more leaders studied, as well as not only looking at the language of tweets, but also the features used and change of framings due to various factors. The previous literatures on framing have displayed examples of how it can be used in media and conferences, as well as framing a country or an object to show that both have meanings. This research has continued to show how framings can be used on a social media platform, along with framing countries, its political issues, and the leaders themselves. It thus reveals much information about the values and meanings of a country and its leader, and how it contradicts with another power. Finally, the literatures involving concepts for political agendas have provided another base for this specific research. Eriksson and Noreen’s (2002) explanatory model has showed concepts initially for security studies but has reflected a realist constructivist framework involving concepts of human perception and political factors affecting decision-making. Schillström’s (2020) study presented an example of how those concepts are used in U.S.-North Korea enemy framings, which this specific study has continued to examine, but through many other power relations and only using one medium, namely Twitter. All of these works have helped develop this research into an in-depth examination of how the use of a social media platform by political actors is bigger and more complex that just a micro-blog. Although the study has shown that Twiplomacy is not as powerful to change relations between various powers, it still has shed light on a relatively new and hardly investigated topic. As this phenomenon is still growing, it is still important to recognize any diplomatic change through social media. This study can provide a foundation for future studies to continue examining change in power relations through their behavior on not just Twitter, but other social media platforms.
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9. Bibliography
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https://www.state.gov/recognition-of-juan-guaido-as-venezuelas-interim-president/ (Accessed July 2, 2020). Quinney, N. (Nigel) ‘U.S. Negotiating Behavior’, United States Institute of Peace (online ) Availab le at: https://www.usip.org/publications/2002/10/us-negotiating-behavior (Accessed: August 7, 2020). Rashid, M. and Naseer, M. (2019) ‘Diplomatic Conflict and Media Framing: Reporting of Al Jazeera and Al Arabia Channels Related to Saudi-Qatar Conflict’, SSRN Electronic Journal. DOI: 10.2139/ssrn.3432617. Reuters (2019) ‘Guaido vs Maduro: Who is backing whom in Venezuela?’ (online) Available at: https://www.reuters.com/article/us-venezuela-politics-support-factbox/guaido-vs- maduro-who-is-backing-whom-in-venezuela-idUSKCN1S62DY (Accessed: July 2, 2020). Rogers, Z. (2013) ‘Realism and Constructivism as Compatible Epistemologies ’. E-International Relations (online) Available at: https://www.e-ir.info/2013/10/30/realism-and- constructivism-as-co mpatib le-epistemologies/ (Accessed: July 2, 2020). Schillström, F. (2020) ‘The United States’ Enemy Image against North Korea during the Presidency of Donald J. Trump: Decision-Making at the Elite-Level’. Linnaeus University (online) Available at: http://www.diva- portal.org/smash/record.jsf?pid=diva2%3A1385273&dswid=-994 (Accessed: March 26, 2020). Schmidt, J.H. (2014) ‘Twitter and the Rise of Personal Publics’ (ed.) Weller, K et. al (2014) Twitter and Society. Peter Lang Publishing, Inc.: New York. Sharma, U. and Sharma, S.K. (2000) Principles and Theory of Political Science. Atlantic Publishers & Distributors (P) LTD: New Delhi. Shear, M.D., Swanson, A., and Ahmed, A. (2019) ‘Trump Calls Off Plan to Impose Tariffs on Mexico’. The New York Times (online) Available at: https://www.nytimes.com/2019/06/07/us/politics/trump-tariffs-mexico.html (Accessed: July 2, 2020). Simunjak, M. and Caliandro, A. (2019) ‘Twiplomacy in the age of Donald Trump: Is the diplomatic code changing?’, INFORMATION SOCIETY, 35(1), pp. 13–25.
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Siniver, A. and Featherstone, C. (2020) ‘Low-conceptual complexity and Trump’s foreign policy’, Global Affairs, DOI: 10.1080/23340460.2020.1734953 Sterling-Folker, J. (2004) ‘Realist-Constructivism and Morality’. International Studies Review. 6, pp. 337-352. Talmadge, E. (2016) ‘North Korea blocks Facebook, Twitter and YouTube’. Global News (online ) Available at: https://globalnews.ca/news/2616449/north-korea-blacks-facebook- twitter-and-youtube/ (Accessed: July 15, 2020). Teddlie, C., & Yu, F. (2007). ‘Mixed methods sampling: A typology with examples’, Journal of Mixed Methods Research, 1(1), pp. 77-100. Theys, S. (2017) ‘Constructivism’. In: McGlinchey, S., Walters, R. and Scheinpflug, C. (2017) International Relations Theory. (online) Available at: https://search-ebscohost com.proxy.mau.se/login.aspx?direct=true&db=cat05074a&AN=malmo.b2382439&lang= sv&site=eds-live (Accessed: 1 April 2020). Toosi, N. (2019) ‘In response to Trump, China gets mean’, Politico (online ) Available at: https://www.politico.com/news/2019/12/08/china-tr ump-twitter-077767 (Accessed: June 10, 2020). van Dijck, J. (2013) The Culture of Connectivity: A Critical History of Social Media. Oxford University Press: Oxford. Verrekia, B. (2017) ‘Digital Diplomacy and Its Effect on International Relations’, Independent Study Project (ISP) (online) Available at: https://digitalcollections.sit.edu/cgi/viewcontent.cgi?referer=https://scholar.google.se/&ht tpsredir=1&article=3619&context=isp_collection (Accessed: March 26, 2020). United Nations Climate Change (2020) ‘The Paris Agreement’ (online) Available at: https://unfccc.int/process-and-meetings/the-paris-agreement/the-paris-agreement (Accessed: July 2, 2020).
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9.2 Tweets
Abe, S. (2017) 5 November. Available at: https://twitter.com/AbeShinzo/status/927060645727440897 (Accessed: August 13, 2020). al-Assad, B. (2017) 10 February. Available at: https://twitter.com/Presidency_Sy/status/830016639391453184 (Accessed: August 13, 2020). al-Assad, B. (2017) 3 June. Available at: https://twitter.com/Presidency_Sy/status/871039759728115713 (Accessed: August 13, 2020). Bolsonaro, J. (2019) 28 June. Available at: https://twitter.com/jairbolsonaro/status/1144479756055744514 (Accessed: August 13, 2020). Guaidó, J. (2019) 8 February. Available at: https://twitter.com/jguaido/status/1093957484996374528 (Accessed: August 13, 2020). Khamenei, A. (2018) 7 September. Available at: https://twitter.com/khamenei_ir/status/1038141870273179648 (Accessed: August 13, 2020). Khamenei, A. (2019) 9 January. Available at: https://twitter.com/khamenei_ir/status/1082943349210972162 (Accessed: August 13, 2020). Khamenei, A. (2019) 8 February. Available at: https://twitter.com/khamenei_ir/status/1093792237782208513 (Accessed: August 13, 2020). Khamenei, A. (2019) 9 April. Available at: https://twitter.com/khamenei_ir/status/1115554812769259520 (Accessed: August 13, 2020).
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Khamenei, A. (2019) 4 June. Availab le at: https://twitter.com/khamenei_ir/status/1135972076458795008 (Accessed: August 13, 2020). Macron, E. (2018) 23 April. Availab le at: https://twitter.com/emmanuelmacron/status/988521461542543366 (Accessed: August 13, 2020). Macron, E. (2018) 25 April. Availab le at: https://twitter.com/emmanuelmacron/status/989232282446778369 (Accessed: August 13, 2020). Macron, E. (2018) 8 May. Available at: https://twitter.com/emmanuelmacron/status/993920765060878336 (Accessed: August 13, 2020). Macron, E. (2018) 7 June. Available at: https://twitter.com/emmanuelmacron/status/1004804636056924161 (Accessed: August 13, 2020). Macron, E. (2018) 10 June. Available at: https://twitter.com/emmanuelmacron/status/1005571057728802816 (Accessed: August 13, 2020). Macron, E. (2018) 11 November. Available at: https://twitter.com/emmanuelmacron/status/1061719875612299266 (Accessed: August 13, 2020). Maduro, N. (2018) 19 February. Available at: https://twitter.com/NicolasMaduro/status/965720565876224010 (Accessed: August 13, 2020). Maduro, N. (2019) 30 January. Available at: https://twitter.com/maduro_en/status/1090677832966115331 (Accessed: August 13, 2020). May, T. (2019) 4 June. Available at: https://twitter.com/theresa_may/status/1135916883142537218 (Accessed: August 13, 2020).
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Medvedev, D. (2019) 24 January. Available at: https://twitter.com/medvedevrussiae/status/1088452852345794563 (Accessed: August 13, 2020). Medvedev, D. (2019) 20 September. Available at: https://twitter.com/MedvedevRussiaE/status/1175103845002858496 (Accessed: August 13, 2020). Medvedev, D. (2019) 5 December. Available at: https://twitter.com/MedvedevRussiaE/status/1202592282752569345 (Accessed: August 13, 2020). Modi, N. (2017) 14 August. Available at: https://twitter.com/narendramodi/status/897126399311347712 (Accessed: August 13, 2020). Netanyahu, B. (2018) 14 May. Available at: https://twitter.com/netanyahu/status/996013352022355968 (Accessed: August 13, 2020). Netanyahu, B. (2019) 25 March. Available at: https://twitter.com/netanyahu/status/1110251865248317442 (Accessed: August 13, 2020). Putin, V. (2017) 14 December. Available at: https://twitter.com/KremlinRussia_E/status/941314216769843200 (Accessed: August 13, 2020). Rouhani, H. (2018) 24 September. Available at: https://twitter.com/hassanrouhani/status/1044331137529729025 (Accessed: August 13, 2020). Rouhani, H. (2019) 6 November. Available at: https://twitter.com/hassanrouhani/status/1192019480307744769 (Accessed: August 13, 2020). Salman, A.A. (2017) 20 May. Available at: https://twitter.com/kingsalman/status/865875516334772224 (Accessed: August 13, 2020).
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Trudeau, J. (2018) 1 October. Available at: https://twitter.com/justintrudeau/status/1046784377521410053 (Accessed: August 13, 2020). Trump, D. (2017) 3 February. Available at: https://twitter.com/realdonaldtrump/status/827478751931924480 (Accessed: August 13, 2020). Trump, D. (2017) 12 February. Available at: https://twitter.com/realdonaldtrump/status/830747067379232769 (Accessed: August 13, 2020). Trump, D. (2017) 23 June. Available at: https://twitter.com/realdonaldtrump/status/878013639613186049 (Accessed: August 13, 2020). Trump, D. (2017) 4 July. Available at: https://twitter.com/realdonaldtrump/status/882061157900718081 (Accessed: August 13, 2020). Trump, D. (2017) 30 November. Available at: https://twitter.com/realdonaldtrump/status/936037588372283392 (Accessed: August 13, 2020). Trump, D. (2017) 30 November. Available at: https://twitter.com/realdonaldtrump/status/936209447747190784 (Accessed: August 13, 2020). Trump, D. (2018) 2 January. Available at: https://twitter.com/realdonaldtrump/status/948355557022420992 (Accessed: August 13, 2020). Trump, D. (2018) 8 April. Availab le at: https://twitter.com/realdonaldtrump/status/982966315467116544 (Accessed August 13, 2020). Trump, D. (2018) 11 April. Available at: https://twitter.com/realdonaldtrump/status/984017894240604161 (Accessed August 13, 2020).
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Trump, D. (2018) 11 April. Available at: https://twitter.com/realdonaldtrump/status/984022625440747520 (Accessed August 13, 2020). Trump, D. (2018) 13 May. Available at: https://twitter.com/realdonaldtrump/status/995746011321597953 (Accessed: August 13, 2020). Trump, D. (2018) 15 May. Available at: https://twitter.com/realdonaldtrump/status/996368474556583937 (Accessed: August 13, 2020). Trump, D. (2018) 1 June. Available at: https://twitter.com/realdonaldtrump/status/1002539852171304960 (Accessed: August 13, 2020). Trump, D. (2018) 8 June. Available at: https://twitter.com/realdonaldtrump/status/1004846478253273088 (Accessed: August 13, 2020). Trump, D. (2018) 11 June. Availab le at: https://twitter.com/realdonaldtrump/status/1005988633747312640 (Accessed: August 13, 2020). Trump, D. (2018) 13 June. Available at: https://twitter.com/realdonaldtrump/status/1006690543403855872 (Accessed: August 13, 2020). Trump, D. (2018) 23 July. Available at: https://twitter.com/realdonaldtrump/status/1021234525626609666 (Accessed: August 13, 2020). Trump, D. (2018) 1 September. Available at: https://twitter.com/realdonaldtrump/status/1035850173224824832 (Accessed: August 13, 2020). Trump, D. (2018) 30 October. Available at: https://twitter.com/realdonaldtrump/status/1057249169507803137 (Accessed: August 13, 2020).
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Trump, D. (2018) 12 November. Available at: https://twitter.com/realdonaldtrump/status/1062047641889095684 (Accessed: August 13, 2020). Trump, D. (2018) 13 November. Available at: https://twitter.com/realdonaldtrump/status/1062311785787744256 (Accessed: August 13, 2020). Trump, D. (2018) 26 November. Available at: https://twitter.com/realdonaldtrump/status/1067015026995879937 (Accessed: August 13, 2020). Trump, D. (2019) 12 January. Available at: https://twitter.com/realdonaldtrump/status/1084074865496334336 (Accessed: August 13, 2020). Trump, D. (2019) 1 February. Available at: https://twitter.com/realdonaldtrump/status/1091326078323486722 (Accessed: August 13, 2020). Trump, D. (2019) 10 May. Available at: https://twitter.com/realdonaldtrump/status/1126833126179840000 (Accessed: August 13, 2020). Trump, D. (2019) 13 May. Available at: https://twitter.com/realdonaldtrump/status/1127715742898692097 (Accessed: August 13, 2020). Trump, D. (2019) 3 June. Available at: https://twitter.com/realdonaldtrump/status/1135332642851893250 (Accessed: August 13, 2020).
Trump, D. (2019) 3 June. Available at: https://twitter.com/realdonaldtrump/status/1135453891326238721 (Accessed: August 13, 2020).
Trump, D. (2019) 8 June. Available at: https://twitter.com/realdonaldtrump/status/1137329348409778177 (Accessed: August 13, 2020).
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Trump, D. (2019) 25 June. Available at: https://twitter.com/realdonaldtrump/status/1143529903238893568 (Accessed: August 13, 2020). Trump, D. (2019) 9 July. Availab le at: https://twitter.com/realdonaldtrump/status/1148573632869875712 (Accessed: August 13, 2020). Trump, D. (2019) 9 July. Available at: https://twitter.com/realdonaldtrump/status/1148559442885185536 (Accessed: August 13, 2020). Trump, D. (2019) 11 July. Available at: https://twitter.com/realdonaldtrump/status/1149320643818729472 (Accessed: August 13, 2020). Trump, D. (2019) 1 August. Available at: https://twitter.com/realdonaldtrump/status/1156933712761753600 (Accessed: August 13, 2020). Trump, D. (2019) 7 October. Available at: https://twitter.com/realdonaldtrump/status/1181227885841002496 (Accessed: August 13, 2020). Trump, D. (2019) 12 December. Available at: https://twitter.com/realdonaldtrump/status/1205156716054241285 (Accessed: August 13, 2020).
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