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Framing of the Ukrainian Crisis in Russian Television Media

Vira Diukanova (11571721)

Political Communication

University of Amsterdam Graduate School of Communication

Thesis supervisor: Linda Bos

Word count: 7,475

Date: 29.06.2018

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Abstract

Television, as the primary news source for Russian people, has become a powerful instrument for information warfare, with the Ukrainian Crisis as a clear illustration. My work gives a nuanced picture of how the warfare narratives find reflection in mainstream Russian media outlets, tailored to the National audience. The work focuses on two popular television channels – federal Russia1 and commercial NTV. A quantitative content analysis was conducted, using broadcasts from the peak moments of the Ukrainian Crisis, and the events surrounding them (N=312). Through the prism of divided communities, a standard technique in the war discourse, my paper demonstrates the differences in the portrayal of the in- and outgroup. Five generic frames: human interest, conflict, morality, responsibility and economic consequences and two issue-specific frames: violence and Great Patriotic War were studied to access the information warfare narratives. The emotionally-charged frames that utilize powerful symbols of the past are commonly employed by the Federal channel, rather than by the commercial channel to frame the current events in Ukraine. Surprisingly, sensational elements, such as editing techniques, sounds, and visuals causing emotional arousal have become an information war instrument more

frequently used by the state-controlled television channel than by the commercial television channel. The results confirmed that the following characteristics of information warfare: ‘blaming and accusing’ while and ‘denying any involvement in the conflict’ were present in Russian mainstream television media.

Keywords: Quantitative content analysis, framing, divided communities, protest paradigm, information war, sensationalism, legitimation, marginalization, dehumanization, violence, Russian media, Ukrainian Crisis.

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Introduction

North Atlantic Treaty Organization (NATO) commander, United States General Philip M. Breedlove, famously said on the 4th of September 2014 about the Ukrainian Crisis “[This is] the most amazing information warfare blitzkrieg we have ever seen in the history of

informational warfare, using all these tools to stir up problems that they can then begin to exploit with their military too” (Pilon, 2017, p. 40). Although the key elements of the Russian reflexive control techniques, have often been called ‘Information Warfare,’ little has been done on a scientific level to formulate an analytical framework for this concept. The societal relevance of my research is to validate the claim of ‘Information Warfare’ through a systematic quantitative content analysis of news programs on mainstream Russian television channels, and to single out the common frames and patterns attributed to it. This leads to the following central research question:

RQ: Which key elements of Information Warfare are present in the framing of the Ukrainian Crisis by Russian mainstream television media?

Analysis of the scientific literature demonstrates that the absolute majority of scholars identify different issue-specific frames to describe the Ukrainian Crisis (Gaufman, 2015; Lichtenstein, Esau, Pavlova, Osipov, & Argylov, 2018). However, the high degree of issue– sensitivity complicates the generalizability and comparability, and, consequently, further theory-building. The absence of comparability has led researchers to “too easily finding evidence for what they are looking for” and to contribute to “one of the most frustrating tendencies in the study of frames and framing [being] the tendency for scholars to generate a unique set of frames for every study” (Hertog & McLeod, 2001, pp. 150–151). To analyze the information war narratives, I’ve added the new angle to the generic frames, indexing them by the divided

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communities. At the same time, my research incorporates findings of framing research on the Ukrainian Crisis by bringing in the cultural frame, which exploits symbols of the collective memory of the Great Patriotic War. Additionally included is the ‘violence’ frame, following from a protest paradigm that tends to trivialize and marginalize protesters, as well as presenting the protests as a violent freak show, and overestimates the role of far-right movements in the protests (Detenber, Gotlieb, McLeod, & Malinkina, 2007). In this way, my research contributes to the war studies in general, adding the divided communities angle to the general frames, and in particular to the Ukrainian Crisis framing research, adding the nuanced country-specific frames. The largest body of research regarding the framing of the Ukrainian Crisis is done on the basis of the two federal channels: Channel One Russia and Russia1 (Khaldarova & Pantti, 2016;

Lichtenstein et al., 2018; Pasitselska, 2017). The analysis of the content on the third biggest Nashe Televideniye (NTV) channel in attribution to the Ukrainian Crisis is missing. I am going to fill this gap by comparing the content of the nation-wide mainstream channels: federal channel to the commercial television channel.

Theory Informational Warfare

The critical elements of the Russian reflexive control techniques have often been called ‘Informational Warfare’ and the Ukrainian Crisis triggered the claim that Russia has raised the information war to the next level as stated by Porche, Paul, York, Serena, and Sollinger (2013) defined informational warfare as the “conflict or struggle between two or more groups in the

information environment” (p. 18). Some scholars further the concept of informational warfare to ‘the hybrid war’ when it comes to Ukraine: “The ‘hybrid’ aspect of the term denotes a

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information” (Kofman & Rojansky, 2015, p. 2). At the same time, many scholars agree that the Russian information warfare is not a new concept, as many similar strategies were developed

during the Soviet era. Modern information warfare is simply a continuation of the narratives of

the Cold War, such as stressing the division between the Eastern and Western Blocs (Kofman & Rojansky, 2015; Snegovaya, 2015). Furthermore, many scholars have even referred to the

Ukrainian Crisis as the ‘new Cold War’ with a sense that, when the pro-European Union (EU) protests started in Ukraine, Russia launched information warfare in order to win Ukraine back

from the West and keep it in its orbit (Monaghan, 2015; Ojala & Pantti, 2017).

Specifically, Snegovaya (2015) points out the key elements of Russian information warfare:  Denial of any involvement with the conflict, such as culpability of ‘little green men’ in

uniform without insignia in Crimea;

 Concealing the real goals and objectives of the Kremlin in the conflict;

 Deception by spreading the conspiracy theories, for example fabricating evidence of Ukraine’s involvement in the Malaysian Airlines Flight 17 attack;

 Blaming and accusing the West of stirring the Ukrainian conflict and of military involvement in it;

 The deployment of a vast and complex global effort to shape the narrative about the Ukrainian conflict through official and social media. (p.7)

The previous research on the information war, however theoretical by nature, only contains descriptive elements of the information warfare narratives, and has never been adequately

assessed empirically. My research offers a comparative analysis of the aspects of the information war on mainstream Russian television channels

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Divided Communities

War discourse studies emphasize creating divided communities as a strategy employed in order to justify war (Hodges, 2015; Oddo, 2011). Identities are intentionally produced, not presented, and are the result of discursive tactics that play in different ways on sameness and difference. Sameness among in-group members is highlighted, while downplaying differences to create unity. At the same time, differences are made salient through the articulation of various forms of distance between the in-group and outgroup, whether social, cultural, political, geographical, or moral (Hodges, 2015). This leads to the following strategic narratives on the basis of sameness, which is defined as ‘Us,’ and difference, which are defined as ‘Them.’ (see Table 1)

Table 1: Narratives attributed to ‘Us’ and ‘Them’

Us Them

Representation of the opinions of the group belonging to ‘us’

Misrepresentation or underrepresentation of other’s opinions (Chilton, 2004)

Positive self-presentation Negative ‘others’ presentation

Legitimation on the cultural ground De-legitimation on the cultural ground Legitimation on the economic ground De-legitimation on the economic ground Legitimation on the basis of bringing peace De-legitimation for its violence

Denying and defending, which serves to promote one group

Blaming – serves to disqualify the other group (Wodak, 2006)

Personification, including putting a human face to one group

De- personification, which includes the dehumanizing of the other group (Haslam,

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2006).

Glorification of the one side Demonization on the other side

Carnivalization- mocking of the one group Decontextualization.- portraying of the protesters as marginal groups of society

Victimization-portraying one side as a victim

Perpetrator- portraying the other side as an aggressor

Framing

Under the conditions of war conflict between countries, when the elites of the involved

parties actively seek to influence the public opinion through the media content, framing theory

offers the framework on how the crisis gets presented to the audience. Framing theory is based

on the idea that media do not simply cover the current political events, instead, they structure

them into frames, which help to explain or contextualize information and make it accessible to a

larger audience. Robert Entman first used this definition that has become a commonly accepted standard in framing research: “some aspects of a perceived reality and make them more salient in a communicating text, in such a way as to promote a particular problem definition, causal

interpretation, moral evaluation, and/or treatment recommendation” (1993, p. 52). Framing researchers agree that the national political elite highly impact media framing. The greater the ability of a government to mobilize and maintain a high level of political consensus in support of its policies, the more likely it is that the news media will play a supportive role in a conflict or peace process (Wolfsfeld, 2014). Frames identify problems, establish their causes, offer moral judgments, and recommend solutions. “Instead of telling the audience what to think about, frames tell them how to think about something” (Scheufele & Tewksbury, 2006, p. 14.). How

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something is framed has been shown to shape the public’s choice of whom to blame for social, political, and economic problems (Iyengar, 1990).Entman (2004) points out that culturally constructed news frames are most influential on public opinion, and that they tend to employ “words and images highly salient in the culture, which is to say noticeable, understandable and emotionally charged” (p. 6).

De Vreese & Semetko (2002) have defined generic frames as those attributed to the most news topics, the overarching frames that transcend thematic limitations, and can be identified over time and across different cultural contexts. Scholars identify five generic news frames Semetko & Valkenburg (2000), which are conflict, human interest, responsibility, morality, and economic consequences frames. Other frames allow a high degree of issue-sensitivity and are pertinent only to specific topics or events. Such frames are commonly labeled issue-specific frames (De Vreese, 2005).

Framing theory can be used to access the information war rhetoric (Dimitrova & Strömbäck, 2005). I suggest using generic news frames, with the key addition that, regarding all communication within the information war, only one side of the divided communities gets the most prominent attention, while the other side is underrepresented or misrepresented. Misrepresentation is conducted through the process of ‘indexing,’ which means presenting only the frames of issues that match the views of political elites – opinions that do not align with elite support are left out, a considerable disadvantage (Bennett, 1990).

I suggest attributing the following war frames to the Ukrainian Crisis. First of all, the conflict frame emphasizes the conflict between groups or institutions (Valkenburg, Semetko, & De Vreese, 1999) and refers to a journalistic practice of reporting stories of clashing interpretations (De Vreese, 2005). Although Russian media extensively cover the Ukrainian

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Crisis, through the paradigm of divided communities, they rather framed it as a conflict between Russia and the West over Ukraine (Snegovaya, 2015). Second, the responsibility frame presents an issue or problem in such a way as to attribute responsibility for causing or solving a problem to the government or to a group (Valkenburg et al., 1999). From a Russian perspective, it is the West and Ukraine in charge of the conflict while Russia denies any responsibility (Snegovaya, 2015). Third, the human interest frame brings the human face or emotional angle to the events (Valkenburg et al., 1999). In the context of information war and in line with the theory of divided communities only the side in control is depicted with the human face, and the other side gets depersonalized and dehumanized, as it happened with Anti-Maidan vs Maidan protesters (Pasiletska, 2017). Next, the morality frame interprets an event or issue in the context of religious tenets or moral prescriptions (De Vreese, 2005). The conflict in Ukraine was portrayed as a clash of forces of good and evil, and a noble struggle of Russia, the carrier of moral values, against the ‘fascist’ Western-sponsored Ukrainian nationalist intent on carrying out ‘genocide’ of Russians in Ukraine (Gaufman, 2015).

In addition to these general frames, I would like to bring up the following issue-specific frames for analysis. The news stories about protests like those that marked the beginning of the Ukrainian Crisis are commonly framed to emphasize deviant behavior, violence, and

confrontations between police and protesters and over-emphasize the presence of the far-right movements, even if the majority of the protesters have been peaceful (McLeod and Hertog, 1999) leading to the violence Frame. Concerning issue-specific culturally constructed news frames, according to Entman (2004), the post-Soviet Russian collective memory is a crucial factor for actively using the emotionally-charged Soviet Great Patriotic War lexicon, enabling Russian media portrayal of the Ukrainian Crisis as a struggle against ‘fascism’ (Gaufman, 2015).

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For that reason, I would like to introduce a new ‘WWII’ frame, which would accommodate all references to the symbols of the Second World War.

For my research, I will analyze the generic frames as well as the two issue-specific ‘violence’ and culturally constructed ‘WWII’ frames, through the lenses of ‘Us’ and ‘Them'. I expect significant differences in the framing of the conflict depending on the attribution to the particular community (Gaufman, 2015; Pasiletska, 2017):

H1: The framing of the conflict will differ significantly depending on attribution to ‘Us’ or to ‘Them.’ ‘Us’ will be portrayed positively. ‘Them’ will be portrayed negatively.

Specifically, in the war context, I expect that certain frames will be explored in attribution to ‘Us’, while others in attribution to ‘Them’. The ‘violence’ frames generally pursue the idea to

discredit the adverse party for its violence:

H1.1: The violence frame will be attributed more often to ‘Them’ than to ‘Us.’

The human interest frame aims to put the human face to the story, so that the audience can feel for and relate to the ‘Us’ side of the conflict. In the war discourse, only one side has a human

face attached to it, while the other is dehumanized and portrayed as a violent crowd.

H1.2: The human interest frame will be attributed more often to ‘Us’ than to ‘Them.’

The Russian information war strategy often denies any involvement in the conflict while blaming

the opposing side of initiating it. Hence, the next hypothesis:

H1.3: The responsibility frame will be attributed more often to ‘Them’ than to ‘Us’.

Russian Media

The Russian media system is often defined as an authoritarian or semi-authoritarian neo-Soviet dichotomous media system Oates (2007), Toepfl (2013) and Toepfl (2014), “where some outlets, notably national TV, are very tightly controlled, while others, including the Internet, are

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allowed a substantial degree of freedom” (Dunn, 2014, p. 1425). In 2013, Russia was ranked 148th out of 180 countries in the World Press Freedom Index from the Reporters Without Borders. In the 2015 Freedom House report, Russia was awarded a score of 83 (100 being the worst), primarily because of the new laws introduced in 2014 that further extended the state control over mass media.

According to public opinion polls, approximately 60% of citizens of Russia believe that the events in Ukraine have been covered by Russian media objectively, impartially, and without bias (Levada Center, 2015; VCIOM, 2014). 70% of elites in Russia get their news through television, according to (Hoskins & O'Loughlin, 2015). Over 90% of Russians cite television as the main source of information according to Levada Center (2014).

Three major television channels, namely Channel One Russia, Russia1, and NTV, account for approximately 80% of all the television news consumption, with around 65% and 48% watching Russia1 and NTV, respectively. (Russia profile, 2015).The owner of Russia1 is "All-Russia State Television and Broadcasting Company," which belongs to the Government of Russia. The NTV channel belongs to "Gazprom Media Holding," the largest media holding in the country (Gilmanova & Fatihova, 2015).

Since all the national broadcasters in Russia are state owned or state controlled Belsey & Prat (2006), the coverage of the Ukrainian Crisis for both federal and commercial television channels should convey government’s war frames. In my research, I am going to evaluate the extent to which the commercial television channels apply the war conflict frames. As the State media are directly controlled by the government, while commercial media experience an indirect control, I do expect the State media will convey stronger war frames than the commercial media outlet:

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H2: There will be less reliance on the war frames in Commercial television than in State television channels.

McManus’s theory of news production states that because of increased

commercialization, private media rather than public, offers more entertainment, sensational, and infotainment elements on the coverage of the same political events (Croteau & Hoynes, 2006). Commercial channels depend heavily on advertisers and sponsors, and since ‘melodrama sells,’ it is relied upon. Public service broadcasting is at least partly financed by the government; consequently, maximization of audience attention is financially more important to commercial broadcasters (d’Haenens & Saeys, 2001). The concept of sensationalism refers to those content features and formal features of messages that have the capability to provoke attention or arousal of emotional responses in viewers (Grabe, Zhou, & Barnett, 2001).

In the context of war discourse, Griffin (2010) makes the following point:

“Private media often had to say about which war images reached the public…they stayed on the script to foster uncomplicated images of ‘good and bad', ‘us and them', ‘right and wrong’. It is not just that private media tended to promote flag-waving patriotism, which they did, but that they so effectively managed a nuanced combination of propagandistic journalism and fictional reconstruction, using an often seamless stream of pictures in both the news and entertainment media” (p. 12).

Based on the research indicating that commercial media contains more sensational elements than the state media, my hypothesis is as follows:

H3: The newscasts of the commercial NTV channel will contain more sensational elements than the newscasts of the state Russia1 television channel.

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Method

To test the hypothesis, a quantitative content analysis of two mainstream Russian

television channels was conducted between the 13th and 29th of May, 2018. The sample consists of 312 news items covering the peak periods of the Ukrainian Crisis. More specifically, there were 184 items from the Russia1 state television channel, which represents 59% of the sample, and 128 items from the commercial NTV channel, which makes up 41% of the sample. The news items were selected by their relevance to the 2014 Ukrainian Crisis, including the Russian

reaction, as well as the events surrounding the Crimea Annexation.

The coverage consists of the six peak periods of the Ukrainian Crisis, 40 days in total. The first five peak periods were the same as in Ojala and Pantti (2017) and Sakwa’s (2015) existing literature on the topic. The sixth period was taken from Marson and Cullison’s work (2014). When it was not possible to access the main news program of the day (8 o’clock news for Russia1 and 7 o’clock for NTV, or on the weekends, when there was no 7 o’clock news on NTV), I analyzed the newscast for the other time slots: 11 a.m., 1 p.m. or 11 p.m., depending on the availability. The newscasts were accessed through open sources, such as the Russia1 website, NTV website, and YouTube1.

The units of analysis, the news items, were identified in the following way: they were marked by the news anchor intervention, accompanied by the topic change and format change, by sound cues and visual cues such as news topic changes onscreen. Change of location of the reporting was another indication of the topic change; for example, one story was reported from

1

Russia1: https://www.youtube.com/watch?v=AAbFpl1YByA

Russia1: https://russia.tv/video/show/brand_id/5402/episode_id/986592/ NTV: http://www.ntv.ru/peredacha/segodnya/issues/23700/?page=870

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Kiev, another from Kharkov, both by different correspondents. The length of the items in

seconds varied from 18 to 1,305 seconds (M = 211.54, SD = 172.03). The first three to five items related to the events were included in the sample. Due to the time constraints, coding five items for every newscast was not feasible, so for some newscasts I have coded four or three items. However, the overall sample was big enough and contained the top news, which makes it

representative of the whole population of news on the topic. The breakdown of the data analyzed is presented in Appendix 2.

Measures

I have derived the five generic frames scales from Semetko & Valkenburg (2000), those are the Responsibility, Morality, Human Interest, Economic Consequences, and Conflict frames.

A sample question from the five-item scale for a Responsibility Frame was: ‘Does the story suggest some level of the government is responsible for the issue/problem?’ A sample question for the five-item scale on Human Interest Framing was: ‘Does the story provide a human example or “human face” on the issue?’ A sample question for the three-item scale of Morality Frames was: ‘Does the story contain any moral message?’ A sample question for the four-item scale for a Conflict Frame was: ‘Does the story reflect a disagreement between

parties-individuals-groups-countries?' A sample question for the three-item scale of Economic Consequences Framing was: ‘Is there a mention of financial losses or gains, now or in the future?’ The full list of the generic frames questions is provided in the codebook (Appendix 1).

Furthermore, I have analyzed two issue-specific war frames. I have constructed the ‘Violence’

frame based on the Protest Paradigm (Detenber et al., 2007). Within the protest paradigm, the protest coverage focuses on violations of social norms and laws, accentuating the protesters’ deviance, and delegitimizing and marginalizing the protesters. Negative portrayals of social

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protests focus on the violent actions of the few, while ignoring the peaceful actions of the majority. The measures of the Violence frame I developed are as follows:

1. Are any groups in the story presented as legitimate/illegitimate? 2. Does the story suggest there is a victim/perpetrator in the news item? 3. Does the story refer to any violent actions?

4. Does the story refer to any marginal groups of society?

5. Does the story use derogatory language toward some actors (groups of actors)? 6. Does the story try to explain/give meaning to the event?

I also developed the scale for the culturally constructed frame, Great Patriotic War (GPW)2, basing it on Gaufman’s work (2015). The idea behind it, is that the Russian media frame the Ukrainian Crisis as a modern struggle against ‘fascism,’ employing the collective memory of Russian people. The battery of questions for the GPW frame are as follows:

1. Does the news item contain references to the symbols of the Great Patriotic War? 2. Does the news item contain references to the Victory Day in WWII?

3. Is there any mentioning of fascists, Nazis, occupiers or perpetrators (karateli) in the story?

4. Is there mentioning of junta in the story?

5. Does the news item contain the reference to nationalistic battalions (UPA, OUN), ‘banderites’ or their leaders?

The strength of each frame was constructed on a scale from 0 to 1.

Additionally, the coders were asked to define the actors attributed to each of the frames based on the idea of divided communities (Hodges, 2015& Oddo, 2011), and the positive or

2 The designation ‘Second World War’ is hardly used in Russia, being instead replaced with the title ‘Great Patriotic War’ of 1941–1945, This is in part explained by the attempt to gloss over the period of cooperation between Nazi Germany and Soviet Union that took place between 1939 and 1941.

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negative mentions of particular actors in the war discourse. Examples of the questions defining actors for each frame were as follows: ‘Which actors are presented positively in the item?’ ‘Which actors are presented negatively in the item?’ ‘Which authority is presented as responsible for the issue?’, ‘Who is presented as moral?’, ‘Who is presented as a victim?’, ‘Who is presented as a perpetrator?’, ‘Who is mentioned in reference to nationalistic battalions of the WWII in the modern context?’ Those questions offer the option to choose actors from a drop-down list. The drop-down list of the actors were taken from Pasiletska (2017) and are specific to the Ukrainian Crisis.

Table 2: ‘Us’ and ‘Them’ actors by Pasiletska (2017).

Us Them

Russia, Russian people/citizens, Russian speaking Ukrainians, Crimean citizens, anti-Maidan protesters, Yanukovich government supporters in Ukraine, special police force ‘Berkut’.

Euromaidan protesters, USA, USA politicians supporting Euromaidan, European politicians supporting Euromaidan, Euromaidan

supporters in Ukraine

In addition, I included extra actors belonging to 'Us' or 'Them' in the drop-down list for selection. It was also possible to write down a unique actor as an open answer for each defining question. Those actors were not marked as ‘Us’ and ‘Them,’ but will be further recorded and indexed as such and analyzed accordingly. The strength of the group representation in each frame has been measured on a scale from 1 to 5.

The sensationalism measures were taken from Grabe et al. (2001), and included features that have been linked to provoking sensory stimulations. Some examples include:

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 Special camera techniques, such as zoom movements and eyewitness cameras.

 The editing pace, defined as a number of shots per minute, further recoded into a scale.  The dramatizing visual and sounds elements, coded as present or not.

 The overall level of emotional reporting, measured on a scale from one to nine, with nine being extremely emotional reporting.

The complete descriptions for sensationalism are provided in Appendix 3.

The intercoder reliability tests overall indicated an appropriate level of reliability, (see Appendix 4) measured by three different coefficients (percentage agreement, Cohen’s Kappa, and Krippendorff’s Alpha). It was based on 30 randomly selected news items, which represent 10% of the sample. The second coder, a native Russian speaker, was recruited through the personal contacts. The second coder received a proper coder’s training. The most stringent one (Krippendorff’s alpha) ranged from .01 to 1.00 The low coefficients for some variables can be explained by the overall complexity of analyzing video content, which requires a high degree of attention. Another explanation is that nominal variables usually score lower intercoder reliability (Lombard, Snyder-Duch & Bracken, 2002).

Results

To address the research question, first I have analyzed which frames are employed by the mainstream Russian television channels. The comparative analysis of the means of the five generic and two issue-specific frames demonstrate that the Conflict Frame is the most prevalent in the news coverage of the Ukrainian conflict by Russian television, next are and Human interest, and these are followed by Morality, Violence and Responsibility frames. The least used are the Great Patriotic War and Economic consequences frames, see Table 3.

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Broad caster Responsibi- lity Human

interest Conflict Morality

Economic consequences Violence GPW N M (SD) M (SD) M (SD) M (SD) M(SD) M (SD) M (SD) Russia1 184 .36(.27) .42(.35) .56(.27) .33 (.38) .07 (.24) .42 (.26) .15 (.22) NTV 128 .36 (.22) .50(.32) .53(.29) .58(.39) .11 (.27) .39 (.27) .07 (.17) Total 312 .36(.25) .45(.34) .55(.28) .43(.40) .09 (.25) .41 (.26) .12 (.21)

Based on the theory of divided communities, I have assigned the most attributable actors to ‘Us’ and ‘Them’ categories accordingly. The mean scores indicate that ‘Us’ actors are presented more positively than ‘Them’ actors. ‘Us’ actors are almost never presented negatively, while ‘Them’ actors are portrayed negatively significantly more, see Table 4.

Table 4: Positive/Negative presentation of ‘Us’ and ‘Them’ in the Russian media. Who is presented positively? Who is presented negatively?

Us Them Us Them

M 1.17 .37 .01 1.41

SD .75 .58 .08 .99

N=313

To answer the first hypothesis, I have conducted the paired sample test. The data demonstrate, that for positive representation, t(312) = 15.84, p < .000, MDifference = .89 95% CI [.70, .90], d = .90, which is large. For negative representation, t(312) = -25.34, p < .000, MDifference =-1.40 95% CI [-1.51, -1.29], d=95, which is strong. The first hypothesis, therefore, is supported.

The frequency analysis (see Table 5) lists the details on positive portrayal. While, naturally, Russia is presented positively, the Russian media are very sympathetic to the pro-Russian or presumably pro-pro-Russian population of the Southeast of Ukraine and, in general, to the Russian-Speaking Ukrainians, as well as Russian-friendly Yanukovich government, and Anti-Maidan protesters. The Crimean people who predominantly favor closer ties with Russia are also portrayed positively, except for the Crimean Tatars for their pro-Ukrainian position. On the

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opposite side, the USA, EU countries, and Ukraine, led by pro-EU Turchinov and Poroshenko's government are all portrayed negatively (see table 5).

Table 5. Frequency table of positive and negative portrayals of actors in the Russian TV media Who is presented positively? Who is presented negatively?

Us Them Us Them

Actor n Actor n Actor n Actor n

Russia 76 International investigators of MH17 crash 7 Yanukovich government representatives 1 Ukraine 117 Pro-Russian separatists’ rebels 70 Ukraine military (volunteer corps) 4 People of Crimea 1 Ukrainian nationalists/radicals 74 People of Crimea 48 Ukrainians 3 Turchinov government representatives 63 Pro-Russian civilians on the East of Ukraine 38 Crimean Tatars 3 USA 38 People of the occupied territory on the East of Ukraine 33 Ukraine 2 Ukraine military (volunteer corps) 32 Antimaidan

protesters 17 European Union 22

Yanukovich government representatives 18 Euromaidan protesters 10

Special police force ‘Berkut’ 12 Poroshenko government representatives 5 Russian speaking

Ukrainians 7 Crimean Tatars 4

Russian

people/citizens 6 NATO 3

Customs Union

countries 5

Refugees from the East of Ukraine to Russia 3 Total, portrayed positively, ‘Us’ 333 Total, portrayed positively, ‘Them’ 19 Total, portrayed negatively, ‘Us’ 2 Total, portrayed negatively, ‘Them’ 368

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The paired sample test was conducted to test the hypothesis H1.1. The comparative table for the mean scores (Table 6) demonstrates that for all the questions from the ‘Violence' frame, the mean values are much higher for ‘Them’ than they are for ‘Us.’ ‘Them,’ as a group, are rather presented as illegitimate, violent, perpetrators, like those from marginal groups of society, and are ridiculed. At the same time, the ‘Us’ group is never presented as a perpetrator or as violent. The results demonstrate that ‘Them’ have been portrayed violent significantly more often than ‘Us’. The paired sample t-test for equality of means shows that t(312)=-20.51, p<.000,

MDifference = -2.21 95% CI [-2.42, -2.00], d = .95, which is medium to small. The H1.1 is, therefore, supported.

Table 6 Violence Frame descriptive statistics

Violence frame scale Group M SD Who is presented as

illegitimate?

Us .03 .18

Them .40 .04

Who is presented as the perpetrator?

Us .00 .00

Them .64 .04

Who is presented as violent? Us .00 .06

Them .66 .66

Who is presented as a marginal group of society?

Us .00 .00

Them .32 .51

Who gets mocked/ridiculed? Us .01 .08

Them .23 .50

Total, Violence frame Us .04 .22

Them 2.24 1.89

N=313

To address the H1.2, I compared the mean scores for the questions that compose the Human

Interest Frame scale. The comparative table for the mean scores (Table 7) demonstrates that for all the questions from the ‘Human Interest' frame, the mean values are much higher for ‘Us’ than they are for ‘Them.’ The results show that, for all of the questions from the battery, ‘Us’ are

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rather personalized, while ‘Them’ are more depersonalized and dehumanized. The paired sample t-test shows that t(312) = 6.59, p<.000, MDifference = 0.93 95% CI [.65, 1.21], d = .37, which is medium to small. Therefore H1.2. find support in the data.

Table 7: Human Interest Frame descriptive statistics

Human Interest Frame scale Group M SD

Who is presented with the ‘human face’ on the issue? Us .44 .63

Them .19 .43

Who are the adjectives or personal vignettes that generate feelings of outrage, empathy-caring, sympathy, or compassion directed to?

Us .55 .58

Them .32 .59

Who is affected by the issue/problem? Us .58 .56

Them .42 .64

To whose private or personal life the story goes into? Us .10 .32

Them .04 .24

Who is described on the visual information that might generate feelings of outrage, empathy caring or compassion?

Us .42 .54

Them .20 .46

Total Human Interest Frame Us 2.10 2.01

Them 1.17 1.71

N=313

To address the H1.3, I compared the mean scores for the questions that compose the

Responsibility Frame scale. The comparative table for the mean scores (Table 8) demonstrates that for all the questions from the ‘Responsibility' frame, the mean values are much higher for ‘Them’ than they are for ‘Us.’. Although, for some questions, the mean score for ‘Us’ is higher than the mean score for ‘Them’; this is present, for example, in ‘Which actors (groups of actors)

are presented to be able to solve the problem?’ Overall, we can see that responsibility for ‘Them’

is more on the authority rather than on the individual. The results demonstrate that ‘Them’ have

been held responsible significantly more often than ‘Us’. The paired sample t-test gives the following result: t(312)=-10.65, p<.000, MDifference = -0.85 95% CI [-1.01, -.69], d = .60, which is medium. Meaning that H1.3 is overall supported.

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Responsibility Frame scale Group M SD

Who is able to alleviate the conflict? Us .12 .32

Them .22 .46

Which authority is responsible for the issue/problem? Us .03 .17

Them .63 .67

Which actors (groups of actors) are presented to be able to solve the problem?

Us .30 .52

Them .23 .57

Who is presented as individually responsible for the issue-problem?

Us .01 .10

Them .22 .46

Total Responsibility Frame Us .45 .68

Them 1.30 1.38 N =313

I conducted an independent samples t-test to examine whether the coverage of the Ukrainian Crisis differs between the state and commercial TV channels to test the second hypothesis. The

results are both displayed in Table 9 as well as discussed thoroughly in this section.

Table 9: Independent T-test for frame used by the state and commercial television channels.

T-test Russia1 M(SD) NTV M(SD) t df MDifference p(two tailed) Responsibility .36(.27) .36 (.22) -.03 298 .00 0.974 Human interest 42(.35) .50(.32) -2.12 309 -.08 .035* Conflict 56(.27) .53(.29) 1.16 310 .04 .246 Morality .33 (.38) .58(.39) -5.71 310 -.25 .000** Economic consequences .07 (.24) .11(.27) -1.08 249 -.03 .280 Violence .42 (.26) .39 (.27) .82 309 .03 .413 GPW .15 (.22) .07 (.17) 3.34 307 .07 .001**

Note. N= * Indicates significance at the 95% confidence interval level ** Indicates significance

at the 99% confidence interval.

The results of the test show that the Morality frame has been more employed on the NTV

commercial television channel (M = .58, SD = .39) than on the Russia1 state television channel

(M = .33, SD = .38). The Levene’s test for Equality of Variances, F =.24, p = .63 shows that the

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The t-test for equality of means results in t(310)=-5.71, p < .000, MDifference = -0.25 95% CI [-.34, -.16], d =.66 which is a medium to large effect size. This indicates that the mean difference for Morality frame use between those two television channels is moderately large, meaning the use of Morality frames has been significantly more prominent on the NTV channel.

The Human Interest frame, had also been more employed by the commercial television channel (M = .50; SD = .32) than on the state television channel (M =.42, SD = .35). The Levene’s test for Equality of Variances, F =1.97, p = .162 demonstrates that the assumption of

homogeneity of variances was not violated so, I do not reject equal variances. The t-test for equality of means results were t(309)=-2.12, p = .035, MDifference = -0.08 95% CI [-.16, -.01], d = .24, which is small.

The opposite is true with the Great Patriotic War Frame. The results demonstrate that the state television channel employs references to WWII, to draw parallels to the contemporary Ukrainian Crisis significantly more (M = .15; SD = .22) than the commercial channel (M = .07; SD = .17). The Levene’s test for Equality of Variances, F =39.48, p < .000 demonstrates that the assumption of homogeneity of variances was violated so, I reject equal variances. The t-test for equality of means shows that t(307)=3.34, p = .001, MDifference = -0.07 95% CI [.03, .12], d = .37, which is medium to small.

Overall, there was mixed support for the second hypothesis. The Morality and Human Interest Frames have been employed significantly more often by the commercial channel, while the opposite holds true for the GPW frame, and in other cases there were no differences. Hence,

the second hypothesis is partially supported.

The independent t-test was conducted to address the third hypothesis. Sensationalism was

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included multiple elements, such as special camera techniques, sounds, visuals, and the

frequency of camera shot changes.

Table 10: Sensationalism descriptive statistics

Broadcaster N M (SD)

Sensationalism Russia1 183 3.34 (1.71) NTV 128 2.97 (1.26)

Contrary to the proposed hypothesis, the state television channel, Russia1, used significantly more sensational elements than the commercial NTV channel. For the

Sensationalism scale the Levene’s test for Equality of Variances, F =11.49, p =.001 concludes that the assumption of homogeneity of variances was violated and the statistically significant difference is assumed here. MDifference = 0.38, 95% CI [-.05, .71], t(308) = 2.24, p = .026. d = .25 which is small. The difference between means is significantly different, but is small. The

assumption made in hypothesis three is, consequently, reversed.

Discussion and Conclusion

My work contributes to the studies of war and propaganda, in particular to the Russian information war techniques. The roots of the support of the Kremlin doctrine within the country should be understood, appreciating the nuances and complexities of the media frames by which Russia tries to legitimate its behavior (Hutchings & Szostek, 2015). The most prominent frames in attribution to the Ukrainian Conflict are the emotionally charged frames, such as: Conflict, Human Interest, and Morality. This is as opposed to the least employed rational Economic Consequences frame, which appeals to the future consequences of the chosen set of actions. The emotionally engaging frame of the past, the Great Patriotic War, have been employed higher with the Federal TV media, directly conveying the Kremlin message. Among its narratives is the

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victory, which is seen as the most “sacred achievement” in Russia’s history. Additionally, a ‘fascist’ label attributed to Ukraine is a powerful way of appealing to the values of Russians, who associate World War II with fascist horrors and crimes (Khaldarova & Pantti, 2016). The phenomenon of low presence of rational frames as opposite to emotional frames is often described as a “battle between the television and the refrigerator.” The television stirs Russian spirits, with a story about a great patriotic struggle against a “fascist” Ukraine and a scheming West. However, the refrigerator lowers the spirits, with its increasingly scarce and costly contents (Rachman, 2015).

The news frames in the information war discourse are impossible to consider without making a distinction between ‘Us’ and ‘Them.’ The comparison has been made to the old struggle of Russia against the West: the Russian speaking population of Southeast Ukraine represents the Russian Side, and Ukrainian nationalists, Euromaidan protesters, and the pro-EU Government of Ukraine primarily represent the Western side. In line with the theory of divided communities Hodges (2015) the actors are presented very differently depending on which side they represent. The Violence frame, based on the protest paradigm by Detenber et al. (2007) shows that only the outward group was systematically demonized, was portrayed as a marginal group of society, delegitimized and carnivalized.

Another powerful finding is the significant difference between the presentation of ‘Us’ and ‘Them’ within the Human Interest frame. Dehumanization is a commonly used technique within the war discourse, justifying the in-group’s aggression and providing it with a sense of moral superiority. The depersonalized or de-individualized outgroups are often judged to be highly threatening, because it was perceived as a violent crowd, allowing abstraction from its attendant individuals, whereas ingroup favoritism was unrelated to aggression (Haslam, 2006).

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On the contrary, by putting a human face to the perceived ingroup, often representing the people from the Southeast of Ukraine, (Russian-speaking Ukrainians needing protection from the aggressive action), and the media managed to stir sympathy within Russian people.

In line with the main characteristics of the information warfare by Snegovaya (2015), as demonstrated within the Responsibility Frame, the Russian media were systematically blaming and holding Ukraine and the West accountable, while denying any involvement in the conflict During the Crimea annexation, for example, the people of Crimea were portrayed as initiating the Referendum. Russia was presented as having to interfere to back up the people of Crimea and to ‘solve the problem’ by protecting them from the aggression of Ukrainian radicals and,

potentially, NATO soldiers.

Contrary to the findings of Lichtenstein et al. (2018) my results do not confirm

constructive frames use by the Russian television media. The actors' representation is one-sided

depending on the community they represent, the rational economic consequences frame is hardly

present in the mainstream news. Quite the opposite, I found the strong presence of emotional,

demonizing and blaming language, conflict and violent frames, which is attributable to

information warfare.

I was also interested in the prevalence of the frames in the news by outlet. The commercial television channel employs more Morality, Human interest, and Economic consequences frames, which can be attributed to the fact that the target audience is more interested in business. On the contrary, Russia1 was exploiting the emotionally charged, Kremlin-supported, Great Patriotic War frame more often. In terms of the usage of sensational elements, counterintuitively, the commercial channel used less. Sensational elements are designed to attract attention in the name of high viewership rankings aimed at increasing profit

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(Grabe et al., 2001). The difference can be attributed to the fact that, although financed and directly managed by the government, the Russian state channel also relies on advertising. The high drama not only has the propagandistic effect but also gives the state channel a competitive advantage. The state channels are directly managed by the state propagandists and convey emotionally arousing Kremlin narratives, whereas the commercial channel less so, due to the indirect control by the state.

This study comes with some limitations. Due to time constraints, it wasn’t possible to analyze all of the news items on the topic that, to my surprise, composed the majority of every newscast for the period under review. Five of the newscasts were not accessible via open

sources, and I had to analyze the news for the other time slots. Another limitation is the practical difficulty to categorize the actors to ‘Us’ and ‘Them.’ The actors were not static, for example, Crimean Tatars in some news items were portrayed positively, and negatively in others. Mejilis Crimean Tatars, for example, were most often portrayed as having sabotaged the Referendum and as a marginal, violent minority. The Ukrainian military, which was generally presented as violent aggressors without a human face, instead appeared to be a victim in one news item, forced to fight in the nonsense deadly civil war, abandoned by the government. Another, while generally actors from the European Union were portrayed negatively, the Organization for Security and Cooperation in Europe (OSCE), which monitors on the East of Ukraine, and generally the International Investigators Committee, and especially the Malaysian and British Aviation experts, are portrayed as competent when shedding a light on the catastrophe. Negative portrayal affected only the Ukrainian side, which was presented as hampering the investigation. Hence, there were difficulties in categorizing actors which, in turn, led to low intercoder

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However, despite the limitations, the study adds to the existing literature on the

information warfare and war journalism by being the first study bringing a new angle to the news frames, offering a breakdown to the inward and outward groups, the strategy often employed in the war discourse. Secondly, it provides the quantitative analytical framework to the field, dominated by the qualitative studies. Thirdly, it offers the issue-specific frames, which can be applied in the further studies of the Ukrainian Crisis. Finally, it shows that the mainstream television media in Russia are not as homogenous as some scholars believed (Kiriya & Degtereva, 2010).

Although my work offers just a few fresh approaches, they can be developed further, and some supplementary studies can test my findings. Due to the inconsistency in the results of the current research on the topic Lichtenstein (2018), Pasiletska (2017) and Snegovaya (2015), the future research can test the present findings using the more extended period, from the beginning of the protests in November 2013, up until the Minsk II agreement signing in 2015. This will be a real test of the proposed theories based on the content of the traditional Russian television media. Provided the approach pass the test, the war frames can be used as a standard to access other conflicts. Additionally, I suggest looking at the coverage of the MH17 crash through the prism of divided communities. I find this remarkable, because, contrary to the allocation to outward group by Pasiletska (2017), in this case, MH17 victims, their relatives, and the

international experts were portrayed as if they were belonging to the inward group. I observed a lot of words of compassion toward the victims of MH17, personalizing them and depicting them with a human face. The Western experts were presented positively, competent to hold an

impartial investigation of the real cause of the plane crash, which is potentially attributable to the key elements of information warfare: "denial of any involvement with the conflict” and

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“deception by spreading the conspiracy theories” (Snegovaya,2015, p.7). Overall, my findings have revealed the need for comparative content analysis studies between the different Russian outlets, by the extent they convey State's information war narratives which would contribute to the existing literature on war and propaganda.

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Appendix 1: Codebook

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1) News anchor intervention: when the news anchor starts talking about another subject (next item), usually accompanied by other visual clues that this is happening  New news item

Note: When a stand-up journalist announces an item him/herself (usually that is an item they made themselves), so not by the news anchor, do NOT start a new item.

2) But also: when a second news item about the same topic is announced by the news anchor  new news item.

3) Whenever the way the news is dealing with a topic (the type of reporting) changes. E.g. from edited video to a studio interview  Make two separate news items

4) In a news carrousel (a series of relatively short news items without news anchor intervention, often used for foreign news), each topic is a separate news item.

Note that if a video is finished and the news anchor returns on screen, this does not always have to be the end of the item. In case the news anchor only has a short concluding statement, directly and clearly related to the video that was just shown, this part is considered as part of the news item (so not a short separate one).

In general, in case of doubt, is advisable to split up into more rather than less news items. A1 Coder name

A2. Broadcaster (number) (see below) 1- Russia1

2- NTV

A3. Date (DD/MM/YYYY)

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Code the rank order of the news item (which you will also use in T4 for the last two digits of the ID number). Obviously, this starts with 1. The number of items can vary a lot between news broadcasters, so there is not maximum.

A5. Identification of news story. This is a number built by the following blocks:

First two digits (if the code is smaller than 10, one digit is sufficient. All following digits move one place then, so year becomes 2nd and 3rd digit etc. ): broadcaster code (complete list will follow when the sample is final).

3rd and 4th digits: year (e.g. 14) 5th and 6th digit: month (e.g. 04) 7th and 8th digit: day (e.g. 24)

9th and 10th digit: chronological item number (start with 1, only count the ones you select, e.g. 01).

So in case of this example: 114042401 is the ID number for the news story. Sensational elements

S1. Duration of the news item In seconds.

S2. Story pacing

For this variable you need to code the number of shots. Please count how often the picture changes completely during the news item. Include the news anchor part of the item. Moving or swinging camera = NOT a new shot.

Background changes (video wall, weather forecast, shot of the studio) in one and the same shot do not count as changes. So weather forecasts often have very few shot changes (sometimes only one).

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In case of a split screen (this differs from a background in the way that you have two equally important parts of the screen, e.g. one part with a view on the news anchor, and one part with a view on a stand-up journalist) shot changes in any of the screens are all counted as shot changes. If at exactly the same time, this is only one shot change.

Moving from a split screen situation to a close-up of either one of the screens, or even another one, is always counted as one shot change.

Only the fact that it changes matters, not whether the actual video material or shot position has been in the item before: code every change.

S3. Other special camera techniques (YES/NO)

Includes the following techniques: eye-witness camera (camera as if it was a person, or

following the movements of e.g. an animal, a car or athlete), repeating the same video fragment, slow-motion, fast-forward, fading the picture, added elements on the video (like smoke or other visuals faded in and out of the picture), hidden or unusually placed camera pictures (only if it is clear from the quality of the picture, e.g. from the perspective or because of unusual

elements blocking a full view).

Not: normal camera movements, zooming, unintended, slightly unstable pictures because of circumstances.

It is not necessary that the video material is made by the journalist or broadcaster themselves. In case of doubt, think about whether the pictures indicate any intention of sensationalizing the news with video editing. If insure, code yes and explain in the open field box (mandatory if coded yes!).

Dramatizing elements

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S3. SOUND

S3.1. Background music (added by the reporter – so not concert reports for example, or music that was part of a ceremony. The music that we look for is part of the sound editing of the news item)

S3.2. Dramatic human sounds (crying, shouting) – NOT cheering or applause

People singing and shouting at a protest march, belong under this category, NOT under cheering. Cheering (F23) is reserved for entertainment situations or for supportive applause (which can also additionally be present in such an item, e.g. as reaction to a speech), but when protesters are singing and dancing for protest reasons (happens often!), we consider them as clearly different (so code F22 in such cases).

S3.3 Dramatic human cheering sounds (applause, cheering).

Dramatic human sounds (F22 and F23) can come from a group, but also from a single person. S3.4. Dramatic non-human sounds (thunder, shooting, bombing, sirens)

Includes shooting (also if the guns are not real). Sirens of police or fire cars, or ambulances only to be coded if sufficiently prominent (not just vaguely in the background). Usually if you notice them in the first view, they are sufficiently prominent.

S4.VISUALS (Explicit)

S4.1. Close-up emotions (close-up of a face clearly expressing an emotion like fear, joy, anger or sadness).

Make sure only to code this if:

* the video clearly focusses on a face of a person (one person in one shot).

* The close-up shot should last minimally 3 seconds (movement of the camera is OK, as long as it still is a close-up)

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* you are able to clearly pin-point which emotion it expresses, or is intended to express

* This should be while a person is not communicating like giving an interview (at least it should be clear that the video focusses on the emotional expression of the face). This does not occur in everyday situations like normal interviews.

E.g. Trump looks happy or angry during a speech: only code the close-up emotion if the camera takes a close shot of his face, and when the emotion becomes clear from the facial expression on itself (without any text messages).

E.g. Video of a podium after a sports game. The winner tends to cry or cheer, or both. Only code this if the camera zooms into this sufficiently. So not if there is only a picture of the podium with three crying athletes from a certain distance.

S4.2. Dramatic pictures of (non-close-up) emotional situations (e.g. funeral, angry crowd at protest action, commemoration ceremonies, collective moments of silence, suffering people) NOT cheering crowd or celebrating sports people (that is F28).

S4.3. Cheering crowd or individual (visual) cheering/celebration. This includes sports people celebrating.

S.4.5. Pictures of actual violence or criminal acts (visual!), which includes fighting, bombing, killing etc. Not in sports context.

S.4.6. Pictures of dead people, injured people or suffering people.

Dot not code this one lightly. Getting dirty (like getting a cade in the face) is not sufficient. Footage of a grave, a body bag or a coffin is NOT sufficient to code this one. The deceased person needs to be (at least partially) visible. However, it is sufficient when the dead person is laying on the ground at a crime scene or in a disaster area, covered by a sheet only, in such a way that it is clear that this is a dead person.

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The following variable are to be coded with a slider in Qualtrics.

The slider represents a 9 point scale. It is indicated what is 9 (which is the maximum) and what is 1 (which is the minimum). The definitions and descriptions below will give you an indication about what is meant. This is no exact science. Based on the definitions, you should follow your gut feeling, of course partly based on the examples given.

Most items will not be that extreme, but do not systematically avoid the extremes. Sometimes it is just like that. Also try not to code the middle category 5 as standard, but try to indicate what is dominant, and preferable situate the slider just over or just under the middle. If exactly even, you should of course keep it in the middle anyway.

S5. Emotional (9) –-- Unemotional (1) style of the news item

Here, the journalistic style of a news item as related to the emotional presentation of information is coded. Emotional news items use verbal, visual or auditory means that potentially arouse or amplify emotions among audience members. This can be done, for example, (a) by dramatizing events, i.e. presenting them as exceptional, exciting, or thrilling; (b) by affective wording and speech, e.g. superlatives, strong adjectives, present tense in the description of past events, pronounced accentuation; (c) by reporting on or visually presenting explicit expressions of emotions (e.g., hurt, anger, fear, distress, joy).

Also a very informal journalistic style (e.g. celebrating together with a celebrity or athlete, hugging a politician etc.) count here as making an item more emotional.

(42)

Unemotional news present their information in a matter-of-fact style not using emotionally arousing verbal, visual or auditory means. In between, there is a mix. For an 8 or a 9, verbal, visual AND auditory emotional elements should be present. For a 1 (=very unemotional), the item can only consist out of factual information in a very slow pace and formal style.

Note that we expect you to give a general evaluation of the news item here. You coded some of these elements before (formal characteristics). Your judgment here should be minimally

consistent with what you coded earlier (so you obviously can’t code it as unemotional if you coded close up emotions earlier), but it is a separate assessment that should be made without looking back. It is certainly possible to code an item with a full 9 as extremely emotional, while you did not code all the visual and auditory emotional elements earlier (that is not a

requirement).

However, if you realize at this point in the coding of this item that you really missed (as in: had not noticed) an formal emotional element earlier, you should go back and correct it.

I. Divided communities. The next battery of questions will ask to choose the actors (group of actors) from the following drop-down list:

- Russia

- Russian people/citizens - Russian-speaking Ukrainians - Crimean citizens

- Anti-Maidan protesters

- Yanukovich government supporters in Ukraine - Yanukovich government representatives - DNR/LNR authorities’ representatives

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