My war is your special operation: Engagement with pro- and anti-regimeframing of the war in Ukraine on Russian social media

Authors:Aleksandra Urman, University of Zurich1

Mykola Makhortykh, University of Bern

Abstract: On 24 February 2022, Russia launched a large-scale invasion of Ukraine which sincethen has been consistently referred to by the Russian authorities as a special operation and notwar. The purpose of this specific framing of the Russian aggression can be attributed tomultiple reasons, but among the main advantages it provides to the Kremlin is the emphasis ofpower inequality between Russia and Ukraine as well as minimizing the concerns of the Russianpopulation about the impact of the war on their lives. However, despite all the Kremlin’spropaganda and censorship efforts, it is still unclear what the dominant framing of the war isamong regular Russian internet users and how they engage with different frames used inrelation to it. To address this gap, we conducted an automated analysis of over 6 million publicposts from VK, the biggest Russian social media platform, published between 14 February 2022and 24 June 2022 and related to different ways of framing the war as well as the ways usersengage with these frames. Our analysis reveals that the invasion was predominantly discussedin connection with the losses in the Russian army, and allusions to WW2 were also common.The users who posted about the war were older than average VK users and tuned in topro-regime and pro-war content more frequently.

Keywords: war, framing, Ukraine, Russia, VK, BERTopic

IntroductionOn 24 February 2022, Russia started a large-scale invasion of Ukraine following the eight yearsof the hybrid war which began in 2014 with the annexation of Crimea. In his televised addresson the same day, Russian president, Vladimir Putin (2022), announced the beginning of the“special military operation” aiming to “demilitarize and denazify” Ukraine. Since then, theKremlin and pro-Kremlin media consistently avoid calling the attack on Ukraine a war and referto it as a special military operation. Further, shortly after February 24, the Russian authoritiespassed a law under which what the authorities treat as the fake information about the specialmilitary operation (including its descriptions as a “war”; RFE, 2022) is punishable by up to 15years in prison, followed by numerous administrative and several criminal cases.

The decision of the Kremlin to frame its aggression as a special operation instead of a war canbe attributed to several reasons. Besides the legal (i.e., the declaration of the war demanding

1 Corresponding author’s email: urman@ifi.uzh.ch

more effort and implying adherence to Geneva conventions; Otis, 2022) and the geopoliticalreasons (i.e., the desire to avoid being treated as a side openly declaring war), it can be relatedto the way the Kremlin prefers the Russian population to interpret the conflict. Not only doesthe special operation imply a lesser scale of involvement of the Russian army as well as theRussian superiority (and not equality between the two sides; Gorobets, 2022), but it also avoidstriggering unresolved collective traumas associated with the large-scale military conflicts of the20th century (Otis, 2022). The large human toll of these conflicts, in particular the SecondWorld War, together with the limited possibilities for trauma processing associated with thefrequent instrumentalisation of these conflicts’ memories (Gaufman, 2017), result in strongemotional load of the war-related references in the Russian public sphere.

Under these circumstances, the framing of the invasion as a special operation is likely viewedby the Kremlin as a less risky option. While it does not necessarily enable the large-scalemobilization in support of the invasion as it would be in the case of framing it as an all-outliberation war, it also impedes the counter-framing that could increase the anxiety of theaudience and undermine the public support for the Kremlin’s aggression (e.g., as in the case ofthe Russian invasion in Syria; Makhortykh, 2021). However, to what degree the intentions of theKremlin are realized and whether the framing of the war it desires is shared by the Russianpopulation remains an open question. Answering it is a rather non-trivial task, in particularconsidering the above-mentioned legal barriers and the unreliability of traditional ways ofmeasuring the public opinion (e.g., surveys) in the authoritarian context (e.g., Chapkovski &Schaub, 2022).

Under these circumstances, one possible approach for examining how the Russian publicengages with pro- and anti-regime framing of the war in Ukraine is to rely on social media data.Despite the increasing efforts of the Kremlin for establishing control over the digital platforms inRussia (e.g., Sivetc, 2021; Makhortykh et al., 2022), the censorship mechanisms are still farfrom being fully effective, in particular when dealing with individuals with a small audience (andnot large-scale influencers). Using the large sample of data from the largest social mediaplatform in Russia, VK (also known as VKontakte), we employ a combination of state-of-the-artnatural language processing techniques (i.e., BERTopic) and descriptive statistics to examinethe thematic composition of the pro- and anti-regime framing of the war as well ascharacteristics of the audience engaging with them and the ways it does so. Specifically, weaim to answer the following questions:

RQ1: How was the Russian war against Ukraine represented in VK content associated with thespecial operation and the war frames overtime?

RQ2: What were the patterns of engagement with the content related to the special operationand the war frames on VK?

RQ3: What were the main characteristics of users who engaged with the war or the specialoperation frames in terms of demographics and selective information consumption?

Theoretical backgroundFraming of armed conflictsDefined by Entman (1993) as a process of selection of some aspects of perceived reality andmaking them more salient, framing plays an essential role in how individuals and groupsstructure the social reality in which they live. By providing meaning to specific occurrences orphenomena, frames determine individual and collective attitudes towards them and, thus,shape what is viewed as an acceptable or beneficial course of action (Reese, 2001). Differenttypologies of frames, ranging from issue-specific frames (de Vreese & Lecheler, 2012) togeneric frames (e.g., Semetko & Valkenburg, 2000) were introduced to facilitate analysis offrames and their impact on the audience.

For the reasons noted above, framing plays an important role when dealing with crises such ashealthcare emergencies (Wicke & Bolognesi, 2020), natural disasters (Houston et al., 2012) orarmed conflicts (Makhortykh & Sydorova, 2017). By prioritizing specific interpretations of thecrises, frames can have profound impact on their course by programming the reactions of theinvolved parties and shaping their expectations of the crisis outcome. In the case of armedconflicts it can result in a broad range of outcomes, varying from promoting reconciliation anddiminishing hostilities in order to facilitate peaceful resolution (Bratic, 2008) to encouragingviolence and impeding de-escalating behavior (Hamelink, 2008).

Traditionally, research on armed conflict framing focused on journalistic media which has longbeen treated as major framing actors (e.g., Griffin, 2004; Nygren et al., 2018). However, theemergence of social media platforms turned regular users from simply being the members ofthe audience to “active contributors, creators, commentators, sorters, and archivers of digitalnews content” (Nisbet, 2009, p. 75). It transformed framing into a two-way process, where theusers can not only be influenced by the prevalent frames (Banks et al., 2014), but also exertinfluence on them and adapt their content (Aslett et al., 2022).

In the context of armed conflict framing, the above-mentioned changes have severalimplications. First, it leads to the acceleration of production and dissemination of war-relatedframes that on the one hand increases their impact, but on the other hand makes the processof framing less top-down and consistent (Manor & Crilley, 2014) . The decrease in frameconsistency is also an ambiguous phenomenon: potentially, it can increase societalpolarization, in particular considering the potential for spreading disinformation that is ofparticular concern in the case of armed conflicts where it can lead to demonization of internaland external opponents and amplification of violence, but also can counter state propaganda

and promote anti-war messages. Arguably, the latter scenario is especially relevant inauthoritarian regimes, where online platforms may expose users to alternative framing on thecurrent events that is otherwise not available due to censorship (Tang & Huhe, 2014).

Framing of the war in UkraineSince the beginning of the hybrid war in 2014, the framing of the Russian aggression againstUkraine has attracted substantial interest from the side of the scholarly community. Not only itturned out to be the largest armed conflict happening in Europe in the last two decades, butalso it became a prominent example of the new phase of war mediatization labeled as the“arrested war” (Hoskins & O’Loughlin, 2015). Characterized by the diffused nature of conflictreporting, the shift to the arrested war is attributed both to the rise of online platforms and theincreasing appropriation of the changes in reporting dynamics by mainstream media andpolitical actors that also has profound implications for how the war in Ukraine was framed andhow the audiences around the world engaged with its framing.

The majority of studies (e.g. Ojala et al., 2017; Nygren et al., 2018) so far focused on thejournalistic framing of the war in Ukraine. Ojala et al. (2017) examined the visual framing of thewar in a selection of major Western European newspapers and found their tendency to focuson the humanitarian aspects as well as putting a strong emphasis on responsibility of theRussian political leaders for the war. Nygren et al. (2018) compared framing of the war inUkrainian, Russian, Polish and Swedish TV shows and newspapers and found majorcountry-based differences in tendency to prioritize neutrality over partisanship in relation to thewar.

By contrast, framing of the war in Ukraine on social media remains under-investigated.Makhortykh and Sydorova (2017) compared visual framing of the war on VK usingissue-specific frames and found profound differences between Ukrainian and Russiancommunities with the former promoting the “good war” discourse and the latter emphasizingthe humanitarian aspects of the war. Similarly, Gaufman (2015) looked at textual and visualframing of the war in Russian Vkontakte communities and observed the tendency to utilizereferences to earlier armed conflicts (e.g., WWII) to increase the emotional impact of the framestogether with the tendency for dehumanization of Ukraine and the West as part of the framingprocess.

Besides the generally low number of studies looking at the framing of the Russian aggressionagainst Ukraine on social media, there are additional gaps which are important to address. Thefirst of them is (as far as we know) the absence of systematic examination of framing of the warin the context of the new stage of aggression starting in February 2022. Another gap deals withthe tendency of the existing studies to focus on the (predominantly qualitative) frame analysis,but not engagement with frames, whereas the matter of engagement is essential for evaluation

the impact of specific frames, in particular when there are different frames competing with eachother (e.g. as in the case of “special operation” and “war” frames).

MethodologyPlatform selection: VKThe study of Makhortykh and Sydorova (2017) is one of the few empirical analyses of VK datain the context of political communication. A few other analyses include the examination of pro-and anti-Maidan groups on VK in 2013-2014 (Gruzd & Tsyganova, 2015),; analyses of onlinenews consumption patterns on VK in Russia (Urman, 2019) and Ukraine (Urman & Makhortykh,2021); a study on the effect of VK ban in Ukraine (Golovchenko, 2022) and; an examination ofVK-based communication in relation to protest mobilization (Poupin, 2021). Yet, the platformremains understudied especially given its prominence in the post-Soviet space: VK was one ofthe most popular social media platforms in Ukraine until the Ukrainian government blocked it in2017 (Golovchenko, 2022), and remains the most popular social media platform in Russia withover 50 million Russian users accessing the platform daily as of July 2022 (Yuzbekova, 2022).After the Kremlin blocked access to Twitter, Facebook and Instagram and declared Meta anextremist organization, the audience of these platforms in Russia has dropped drastically(Forbes, 2022). Considering that already before the war VK offered a more representativesnapshot of social media-based discourse in Russia than other platforms (Urman, 2019), whichmakes it particularly relevant for the current study.

Data collectionThe data were collected in July 2022 through VK’s official API using vkr R package (Sorokin,2020). VK API allows searching for public posts based on specific keywords. We collected allthe posts returned by the API for the keywords “война” (“war”) and “спецоперация” (“specialoperation”, as commonly shortened in Russian) in all their declensions (i.e., grammatical formslike “войны” or “спецоперации”, so posts containing those word forms were also included).The data was collected for the period between 14 February 2022 (10 days before the Russianinvasion of Ukraine to serve as a baseline) to 24 June 2022 (4 months since the beginning ofthe Russian invasion). The API normally returns only the 200 most recent posts with arequested keyword for a specified period. Hence, to collect all the posts for the period ofinterest, we had to construct an iterative pipeline based on the following principle: first, thedata collection script collected 200 most recent posts for 24 June, then it detected the time ofthe earliest post in the sample (e.g., 23:45, 24 June), then collected 200 most recent posts fromthis time (i.e., 23:45, 24 June). This procedure was repeated until the data collection scriptreached 14 February 2022.

Using this pipeline, we collected 5,262,383 posts containing the word “war” and 1,153,119posts containing the word “special operation”. The dataset includes publicly available andsearchable posts from individual users and public pages (i.e., the pages to which users can

subscribe; a form of few-to-many communication on VK, structurally similar to Facebook’spublic pages. VK is overall most structurally similar to Facebook in terms of its functionality andinterface). In total in the “war” sample, 49.45% posts came from the public pages and 50.55%from the individual users. There were 1,261,914 unique posters in total, out of those 31.41%were public pages and 68.59% were individual users. In the “special operation” sample,61.31% of posts were from public pages, and 38.69% from individual users. There were203,757 unique posters in total, 37.08% of them public pages and 62.92% were individualusers.

Data analysisRQ1: Representation of the war in Ukraine through the special operation and the war frames.The analysis for RQ1 was implemented in two steps. First, we analyzed the dynamics ofpublishing content containing words “war” and “special operation” for the time period notedabove. Specifically, we looked at the frequency of post publishing. Then, we analyzed thethematic composition of these posts using BERTopic (Grootendorst, 2022), a novel topicmodeling technique that supports dynamic topic modeling for multilingual text corpora anddemonstrates high performance across different domains (Egger & Yu, 2022). We chose topicmodeling for the analysis of frames since this method offers an advantage of mining emergingframes from a body of texts rather than imposing pre-determined classification categories onthe data set, and is thus especially useful in fast-changing and previously unexplored contexts(Groshek & Engelbert, 2013) such as the one we focus on. The resulting topic classification wasvalidated through qualitative examination of randomly selected documents from each of thetop-20 topics. The same examination also showed that the topics were indeed correspondingto the theoretical concept of interest - that is, frames, - as we initially expected based on theprevious research into other topic modeling techniques since our corpora were thematicallyfocused from the beginning (Dehler-Holland et al., 2021; Maier et al., 2018). Additionally, basedon the BERTopic results, we examined the evolution of topic frequency over time for the mostpopular topics. The analysis was implemented separately for the “special operation” and “war”posts to facilitate the comparison between the two samples in terms of the most frequenttopics and their dynamics. To facilitate analysis of the resulting topical composition, wemanually examined the most representative posts for each topic as well as the top keywordsassociated with each topic.

RQ2: Engagement with the content related to the special operation and the war frames.To investigate the patterns of engagement with the content, we first analyzed the temporaldevelopments in the average number of views attracted by the posts that mentioned “war” and“special operation” published on a given day during the observation period. Then, to makeconclusions about the content of most popular posts, we extracted top-20 posts by thenumber of views for each sample and manually examined them. The engagement-relatedanalysis relies on the data about the numbers of views, likes, comments, reposts of each post.

The analyzed data corresponds to these metrics at the time when the data was collected (July2022), and we acknowledge that the respective numbers can slightly change later for eachpost. Nonetheless, we suggest that despite minor post-hoc variations, reliance on the collecteddata allows us to make relevant generalized judgements here.

RQ3: Characteristics of users engaging with the war and the special operation frames.To answer RQ 3, we examined data on user demographics and their preferences for contentconsumption. Preferences for content consumption were analyzed based on the data about theusers’ subscriptions to VK public pages. Since downloading user profile and subscription datathrough VK API is time-consuming, and our user samples are rather large, it was neitherfeasible nor necessary to collect this for the whole sets of users who posted about war or“special operation”. Thus, we randomly selected 10000 user IDs from each sample, andcollected the data only for those. Additionally, to be able to establish the baseline and evaluatehow the information consumption of users who posted with words “war” or “special operation”compares to that of average VK users, we also collected the data for a random sample of10000 VK users.

To do so, following previous studies (e.g., Urman, 2019), we generated a set of random numericuser IDs, and collected the data for those. Hence, we collected the data for 3 randomlyselected samples of users based on IDs: a sample of posters with the term “war”, a sample ofposters with the term “special operation”, and a sample of random VK users. Though weinitially generated samples of exactly 10000 IDs, since some of the user accounts were deletedor set to private. Some public profile data was available for 9992 users in the “specialoperation” sample, 9948 in the “war” sample and 9179 in the random sample. As we note inthe corresponding Results section, there was drastic variation in the share of users who hadspecific profile information available (e.g., information on gender was publicly available moreoften than on the birth year).

After collecting the data, we first compared the user samples in terms of the gender- andage-related composition to establish whether there are demographic differences thatdistinguish the samples of posters who mentioned “war” or “special operation” from each otherand from the random sample of VK users. After this, to evaluate the differences in the patternsof selective information consumption, we first established which pages are the most popular ineach sample (by the share of users in the sample who subscribed to specific pages). Finally,we established which pages are comparatively more popular in each sample compared to theothers - i.e., the pages with the biggest differences in the shares of subscribers across samplespairwise: “war” vs “special operation” sample; “special operation” vs random sample; “war” vsrandom sample.

ResultsRQ1: Representation of the war in Ukraine through the special operation and the warframesFigures 1 and 2 show the daily numbers of VK posts including the words “special operation”and “war” (note the difference in the y-axis scale). There were consistently more postsmentioning “war”: the minimum number of posts on any given day for “war” was 12,478,whereas for “special operation” - 233. The corresponding maximums were 328,485 and 19,494with means of 40,479.72 and 8,802.41, medians of 32,855 and 8,213 and the standarddeviations of 34,784.4 and 3,978.62. It has to be noted, however, that peaks in “war” postscorrespond to 8 and 9 May and 22 June, hence these posts also include content dealing withWWII. Because both “war” and “special operation” can refer to different military conflicts (e.g.,“war” being often used in relation to WWII, whereas “special operation” being used as a formalname for the first and the second Chechen wars), it is difficult to establish whether the highervolume of “war” posts can be attributed to the term being more ambiguous or to the tendencyof VK users to rely on the anti-regime frame. Topic modeling-based analysis, however, helpsshed light on this issue.

Figure 1. The number of posts mentioning “special operation” per day.

Figure 2. The number of posts mentioning “special operation” per day.

Figures 3 and 4 show the dynamic evolution of the top 10 topics in the “war” and “specialoperation” samples. The topics are denoted using descriptive labels that were created basedon the keywords associated with each topic (as returned by BERTopic) and manual analysis ofthe top 15 most representative posts per topic. As demonstrated in Figure 3, the “war” samplewas dominated by the WWII-related posts, not posts about the ongoing war. Since we focuson the latter, we have additionally zoomed into topics related to the war against Ukraine (seeFigure 5) in order to be able to better trace their dynamics and compare them with the “specialoperation” sample (Figure 4) which we found more closely related to the current conflict.

Three main observations emerge from the comparison. First, even for the subsample of “war”posts related to the war in Ukraine there were more posts compared with the “specialoperation” sample, thus suggesting that the “war” frame was more common. Second, thedynamics of publishing posts was rather uneven with the “special operation” sample havingmore fluctuations per topic, whereas the “war” subsample showed higher consistency (with theexception of topic 3 which contains a mix of posts related to the Russo-Ukrainian war and toWWII). Here, the number of posts peaked right after the beginning of the invasion, and thendecreased in the beginning of March and stayed stable after that. We suggest this can beattributed to the law against “fake news” about the war that was passed in Russia in thebeginning of March and de-facto outlawed referring to the Russo-Ukrainian war as “war”.Finally, the “special operation” sample in comparison to the “war” sample is heavily dominatedby news rather than regular posts. This again can likely be attributed to the law against “fakes”which forces the media to use the term “special operation” when referring to the war.

There are several important observations concerning the content of the posts. In the “specialoperation” sample, though it is heavily dominated by news, the most prominent topic in termsof post frequency is the one related to the Russian casualties. Typically, these are posts written

by the relatives of deceased Russian soldiers or by local authorities that contain briefbiographies of the soldiers and describe how they “heroically” died during the “specialoperation”. The prominence of this topic goes against our expectations: since the Russianauthorities have been trying to downplay the scale of the Russian casualties, we did not expectto find many posts about those anticipating that either those would be removed by VK or thatthe relatives would engage in self-censorship afraid of the repercussions from the state.

Another important finding is that the news about criminal and administrative cases are alsoamong the top-10 topics in the “special operation” sample, suggesting that the informationabout state repression is widely circulating on Russian social media and has a broad reach.Despite the widespread repression and related information, topic related to anti-war posts isalso among the top-10 in the “special operation” sample. In terms of post frequency, it peakedin the beginning of April, around the time when the news about Bucha and Irpin massacresappeared. In the anti-war posts, the “special operation” term is mostly used ironically (e.g.,“special operation aimed at the destruction of civilians” when referring to the Bucha massacre).The fact that there is a distinct anti-war topic in the “special operation” sample but not in thewar one also goes against our expectations as we anticipated that anti-war users would moreoften refer to the war as war instead of using the “special operation” term employed andpushed by the Russian propaganda.

Figure 3. Overtime dynamics of frequency of top-10 topics in the sample of posts mentioning“war”.

Figure 4. Overtime dynamics of frequency of top-10 topics in the sample of posts mentioning“special operation”.

Figure 5. Overtime dynamics of frequency of top topics in the sample of posts mentioning“war”, focus on topics related to the Russian war against Ukraine only.

RQ2: Engagement with the content related to the special operation and the war framesFigures 6 and 7 show the average number of views received by posts mentioning “war” and“special operation” and published on a given day. The view averages were higher for the“special operation” posts, however, that is likely attributed to the fewer posts in this samplewith high disparity in the number of views between popular and unpopular posts as shown bythe lower median number of views in the “special operation” sample together with the higherstandard deviation. Specifically, for “war” mean=1314.79, for “special operation” mean =2743.06; median=157 and 86; SD=10971.3 and 17945.53, respectively. Overall temporaldynamics in the average N of views per post is stable with the observed peaks in each samplepredominantly corresponding to the most popular posts (see Tables 1 and 2). The onlyexception seems to be the peak in the N of views per post for the “war” sample right afterFebruary 24th, which can not be accounter for by a small number of popular posts published

around the same date, and likely signals initially high engagement with war-related contentright after the beginning of the Russian invasion of Ukraine.

Figure 6. Average number of views for the posts published on a given day, “war” sample.

Figure 7. Average number of views for the posts published on a given day, “special operation”sample.

Tables 1 and 2 present the summaries of the top-20 most popular posts by the number ofviews in each sample. We do not present the full text of posts out of ethical concerns (many ofthem contain misleading or unverified information, offensive content or personal details ofdeceased soldiers) as well as for the sake of brevity. Instead, we present short summaries thatgive the reader a general overview of the content.

One important observation, in line with the findings related to RQ1, is that the most popularposts in the “special operation” sample often deal with the stories of deceased Russiansoldiers. Those are mostly written from the point of view of relatives - e.g., referring to “my son”or “my brother”, though published and distributed by large public pages - often thematicallyrelated to Russian Orthodoxy - rather than individual users. Such posts mostly glorify thedeceased soldiers calling them “heroes” or stating that they “gave up their life to protect us andour motherland”.

In the “war” sample, in contrast, there is no single most dominant topic. Many of the mostpopular posts there do not directly relate to the Russian invasion of Ukraine and deal eitherwith the WW2 or with “information wars”. Notably, the majority of the most popular posts in thissample that have to do with the Russian invasion of Ukraine were published by the same publicpage that we refer to as “Writer” in the Table 1 out of ethical concerns (see Footnote 2). Whilewe can not provide detailed information on the page, its follower count is large but much lowerthan that of the other pages with most popular posts. Further, the numbers of likes, repostsand comments, as evident from Table 1, are all much lower than for the other popular posts.This suggests that the viewcounts might in fact be artificially inflated in this case, though we donot have a reliable way to confirm or disconfirm this hypothesis.

One common characteristic of the most popular posts in both samples is that they, with theexception of one post by Ramzan Kadyrov - the head of the Chechen Republic - were allposted by public pages rather than regular users. This is in line with our expectations given thatsuch pages typically have a much broader audience than ordinary users.

Table 1. Summary of the content and sources of top 20 posts with the highest number of views(the “war” sample)

Topic of the postcontent

Date posted Poster (user orpublic page)2

N ofviews

N oflikes

N ofcomments

N ofreposts

Russian rapper, Timati,voiced his support forRussia and implied thatthe war was provokedby some third powers

2022-03-04 Public page -timatiofficial(Timati [Timati])

7,208,990 109,611 21,266 12,465

Post citing Soviet actor,Vasily Lanovoy,highlighting the Sovietrole in the WWII

2022-05-07 Public page -blagonravie(Morality[Nravstvennost])

3,321,382 190,684 2,350 36,135

2 For public pages we list a handle (@HANDLE) or a page id (if no handle is available) together with the English translation of thename with a transliteration of the Russian name (in brackets). If a user is a public figure (e.g., Ramzan Kadyrov), then their name isalso mentioned.

Post commemoratingSoviet soldiers whodied in the WWII

2022-05-08 Public page - life(Life.ru [Life.ru])

2,893,396 2,131 28 53

Post calling for the banon Russian musiciansand actors who opposethe war

2022-02-26 Public page -official page of aself-describedwriter, referred tobelow as “Writer”3

2,749,053 1,595 5 246

Post discussing howthe first month of warchanged thecontemporary reality

2022-03-24 “Writer” 2,731,332 1,099 18 113

Post againstpanic-buying of food inRussia

2022-03-15 “Writer” 2,723,632 1,095 8 104

Post against peoplewho oppose the war

2022-03-05 “Writer” 2,693,274 1,391 38 193

Post against publiccritics of the Russianwar strategy

2022-04-11 “Writer” 2,635,173 881 10 87

Post about the militaryparade on 9 May inMoscow

2022-05-08 Public page - life(Life.ru [Life.ru])

2,595,424 10,950 29 1,345

Post describing howRussian business willflourish

2022-03-09 “Writer” 2,584,624 1,193 8 135

Post citing Soviet actor,Vasily Lanovoy,highlighting the Sovietrole in the WWII

2022-05-04 Public page -hristianskaya_mudrost (WiseThoughts,Orthodoxy[Mudrye Mysli,Pravoslavie])

2,566,525 142,717 1921 30,853

Post about fireworks on9 May

2022-05-08 Public page - life(Life.ru [Life.ru])

2,334,031 4,627 14 1,016

Post commemorating 2022-05-07 Public page - 2,101,532 56,507 231 10,603

3 According to the page, the public figure administering the page is underage. While we do not know if that is true, we do notprovide details on them here out of ethical concerns despite the page being public and having a large following.

Soviet soldiers whodied in the WWII

roditeli_i (Parentsand Teachers -Our Children[Roditeli iPedagogi - NashiDeti])

Post recommending amovie about the “civilwar” in Eastern Ukraine

2022-05-26 Public page -horor (HorrorMovies [FilmyUzhasov])

1,960,935 16,364 600 26,284

Post describingstatements of DmitryPeskov, who serves asPutin’s spokesperson,on the ongoinginformation wars

2022-05-17 Public page -znanierussia(Russian society“Knowledge”[Rossiyskoyeobschestvo“Znanie”])

1,849,385 242 0 52

Post discussing howthe West is allegedlyterrified of the skill ofRussian pilots

2022-06-01 Public page -fucking_humor(Killer humor -[Uboynyi yumor])

1,827,368 13,067 1,357 5,051

Post stating that war ispain

2022-02-24 Public page -kisel_band (#Kisel[#Kisel])

1,699,533 2,898 2 353

Post about theinformation war againstRussia

2022-06-22 Public page - life(Life.ru [Life.ru])

1,674,936 155 36 30

Post with a rhetoricalquestion whetherpeople want war

2022-06-16 Public page -kn_rec (Look whatI learned! [Smotri,chto ya uznal!])

1,663,914 1,875 3,171 588

Post commemoratingSoviet soldiers in WWII

2022-04-14 Public page - id50256515 (Thesechildren [Eti deti])

1,632,400 59,359 768 8,172

Table 2. Summary of the content and sources of top 20 posts with the highest number of views(the “special operation” sample)

Topic of the postcontent

Date posted Poster (user orpublic page)

N ofviews

N oflikes

N ofcomments

N ofreposts

Story of a deceased 2022-05-12 Public page - 2,929,185 167,513 12,684 1,894

Russian soldier histmoment(Russian History[Istoriya Rossii])

Story of a deceasedRussian soldier

2022-05-14 Public page -orthodoxpsiholog(OrthodoxPsychology[PravoslavnayaPsikhologiya])

2,257,720 152,627 17,414 1,705

Story of a deceasedRussian soldier

2022-05-13 Public page -orthodoxrussia(Orthodox Rus[PravoslavnayaRus])

2,254,071 136,633 16,084 2,260

News post aboutposters insultinganti-war Russianmusicians

2022-04-28 Public page -toportg (Axe[Topor -Khranilische])

2,166,536 32,015 2,938 8,948

News post aboutUkrainian singer,Svetlana Loboda,who posted that sheis horrified by the war

2022-05-28 Public page -be.beauty (BeautySchool [ShkolaKrasoty])

2,150,137 2,408 1,596 427

Story of a deceasedRussian soldier

2022-06-05 Public page -christian_parables(ChristianWisdom inParables[KhristianskayaMudrost vPritchakh])

2,109,563 110,403 10,932 1,237

Story glorifying awounded Russiansoldier

2022-05-05 Public page -svegienov (FreshNews [SviegieNovosti])

1,877,322 49,739 2,444 907

Story of a deceasedRussian soldier

2022-04-24 Public page -histmoment(Russian History[Istoriya Rossii])

1,861,942 103,284 13,006 1,144

Story of a deceasedRussian soldier

2022-06-20 Public page -horoshyenovosty(News [Novosti])

1,856,076 38,973 7,525 1,246

Story of a Russiansoldier who returnedhome, received amilitary award andproposed to his

2022-06-10 Public page - id188318774(Urgent News[SrochnyeNovosti])

1,761,234 31,496 2,546 452

girlfriend

Story of a deceasedRussian soldier

2022-04-14 Public page -latests_news(World News[Mirovye Novosti])

1,660,135 55,925 6,659 401

Story of a deceasedRussian soldier

2022-05-22 Public page -wisdom_live(Wisdom of Life[Mudrost Zhizni])

1,629,060 66,611 7,437 720

Story of a deceasedRussian soldier

2022-04-18 Public page -svegienov (FreshNews [SviegieNovosti])

1,616,087 29,204 3,199 326

Story of a deceasedRussian soldier

2022-06-04 Public page -histmoment(Russian History[Istoriya Rossii])

1,488,003 92,960 8,288 857

Post glorifying aRussian soldier fromChechen Republic

2022-03-27 Individual user(RamzanKadyrov’s officialpage)

1,483,528 34,895 2843 2,183

News post about anentry ban to Russiafor Nargiz, a singerwho made anti-warstatements

2022-05-26 Public page -toportg (Axe[Topor -Khranilische])

1,431,720 11,158 1,594 2,235

A post citing thehead of RT, MargaritaSimonyan, whomocked MaximGalkin, a Russiancomedian, for hisanti-war statements

2022-04-30 Public page - id170968685(Crying fromlaughter![Plachem otSmekha!])

1,308,359 10,116 2,620 1,876

Story of a deceasedRussian soldier

2022-05-29 Public page -saintrus (Holy Rus[Svyataya Rus])

1,302,942 77,875 7,550 1,059

News post about theUK purchasing 2.6bln. GBP worth ofraw materials fromRussia in January2022

2022-03-12 Public page -kommersant(Konnersant[Kommersant])

1,250,453 277 449 347

Story of a deceasedRussian soldier

2022-04-23 Public page -sunodik (Synod[Sinodik])

1,213,151 92,342 14,239 1,288

RQ3: Characteristics of users engaging with the war and the special operation framesTable 3 summarizes the demographic characteristics in the two random samples (N=10,000) ofusers who published posts mentioning the “war” or “special operation” words. Additionally, itshows the characteristics of a random sample of VK users (N=10,000) which serves as abaseline for the comparison. The comparison shows that women are slightly over-representedin the “war” sample and under-represented in the “special operation” sample. Additionally, itappears that the users in the random sample are more privacy conscious, because birth yearinformation there is available only for 33.5% of users (compared to 51.88% and 50.13% for the“special operation” and “war” samples). Despite the lesser availability of birth year data, it stillallows drawing a comparison between the samples which suggests that older users areover-represented in the “special operation” and “war” samples. To a lesser extent, the same istrue for the youngest demographic users (i.e. those born after 2000), whereas those bornbetween 1980 and 1999 are under-represented in the two samples of interest compared to therandom sample.

Table 3. Statistics on the demographic characteristics of users in each sample (wheninformation was publicly available)

Demographiccharacteristic

“Special operation”sample

“War” sample Random sample of VKusers

Women, %4 48.50% (N=9,981) 54.41% (N=9,940) 50.66% (N=9,179)

Born before 1940, %5 2.47% (N=5,188) 2.33% (N=5,013) 1.13% (N=3,550)

Born 1940-1949, % 2.45% 1.90% 0.20%

Born 1950-1959, % 10.60% 6.8% 1.27%

Born 1960-1969, % 18.54% 13.98% 4.08%

Born 1970-1979, % 23.30% 18.93% 11.3%

Born 1980-1989, % 23.38% 26.09% 62.99%

Born 1990-1999, % 11.35% 16.94% 18.08%

Born 2000 or later, % 7.90% 13.03% 0.96%

Tables 4 and 5 present the data on the content consumption preferences for the three usersamples: Table 4 shows the public pages most popular with users in each sample in absolutepercentages, whereas Table 5 highlights the public pages that are more popular in each samplecompared with the two others. The data shows that the “special operation” sample is the most

5 N=number of users for who birth year information was publicly available

4 N=number of users for whom this information was publicly available)

consistent in terms of content preferences with the highest number of subscriptions sharedbetween the users. These subscriptions are mostly related to politics-related and/orpro-Kremlin news pages, with the top three pages being Tsargrad (i.e., a pro-war far-rightRussian news media), RT (i.e., the Russian edition of Russia Today, a state-sponsored newsoutlet), and the page of Nikita Mikhalkov, a Russian film director currently known for hisconspiratorial and pro-war YouTube vlog. The top subscriptions for the random sample do notcontain any politics- or news-related pages, whereas for the “war” there is only one such page(i.e., Tsargrad).

The preference towards pro-war and pro-Kremlin content among the users from the “specialoperation” sample is corroborated by Table 5 which shows that pro-war pages are particularlyvisible in this sample compared with the other two. Two pages emerge as particularly relevantin this context - the one of Tsargrad and of Nikita Mikhalkov - by having a higher share ofsubscribers in the “war” sample compared to the random one, and an even higher percentageof subscribers in the “special operation” sample. Furthemore, “special operation” sampleshows a higher share of subscriptions to pages of Vladimir Soloviev and Sergei Miheev, twopro-Kremlin public personalities known for their hawkish (and, at times, extremist) stances onthe war in Ukraine. These findings indicate a clear difference in the content preferencesbetween the users who posted about “special operation” and the random sample with theformer giving preference to more radical pro-Kremlin stances on the war.

Table 4. The most popular public pages per three user samples6.

Pages mostpopular in“war” sample

% ofsubscribers in“war” sample

Pages mostpopular in“specialoperation”sample

% ofsubscribers in“specialoperation”sample

Pages mostpopular inrandom sample

% ofsubscribers inrandom sample

1poetry 5.83% tsargradtv 8.89% i_des 4.59%

vk 5.16% rt_russian 6.93% foodrumedia 4.56%

kino_kaif 5.02% nm 6.68% lepragram 4.10%

exclusive_muzic 4.80% vk 5.91% bestad 3.97%

i_des 4.58% ria 5.62% sci 3.96%

kinomania 4.33% 1poetry 5.42% beginenglish_ru 3.95%

dayvinchik 3.97% solovievlive 5.30% kino_mania 3.92%

6 We list the screennames of the pages, the VK urls for public pages follow the pattern:vk.com/screenname

kino_mania 3.94% dmitry_abzalov 5.25% interestplanet_ru 3.82%

veruj 3.84% miheevpolitolog 5.12% ru.esquire 3.53%

tsargradtv 3.82% russ_great 4.98% cook_good 3.31%

Table 5. Public pages that are relatively more popular in each sample compared to the others.

Pages morepopular in “war”sample

Difference in %of subscribersbetween the"war" sampleand anothersample

Pages morepopular in“specialoperation”sample

Difference in %of subscribersbetween the"specialoperation"sample andanother sample

Pages morepopular inrandom sample

Difference in % ofsubscribersbetween therandom sample andanother sample

Compared to “special operation”sample

Compared to “war” sample Compared to “war” sample

dayvinchik 1.53% tsargradtv 5.07% bestad 1.71%

sokolov.russia 1.07% nm 3.80% foodrumedia 1.63%

i_d_t 0.91% rt_russian 3.35% ru.esquire 1.46%

vkclassifieds 0.88% solovievlive 5.09% vandroukiru 1.10%

bot_maxim 0.78% miheevpolitolog 4.99% comedyclubru 1.07%

Compared to random sample Compared to random sample Compared to “special operation” sample

tsargradtv 3.55% tsargradtv 8.62% foodrumedia 2.36%

vk 3.51% nm 6.40% bestad 1.81%

nm 3.05% rt_russian 6.35% ru.esquire 1.39%

1poetry 2.85% solovievlive 5.09% beginenglish_ru 1.18%

contact_fun 2.81% dmitry_abzalov 4.50% just__cook 1.11%

DiscussionOur analysis has revealed that the framing of the Russian war against Ukraine on Russiansocial media does not fully align with the framing actively pushed by the Kremlin. Despite theintroduction of the repressive laws that make referring to the Russian invasion as warpunishable by up to 15 years in prison, many social media users still use the term “war”. Inaddition, in the corpus of posts that refer to the invasion as a special operation - in line with theKremlin’s framing - the most prevalent topic is that related to the deceased Russian soldiers.Further, posts associated with this topic are not only the most prevalent but also the most

actively engaged with ones. Notably, the most engagement with such posts came not fromstate- or media-related pages but rather from more general ones (e.g.,public pages related toRussian Orthodoxy).

These two observations demonstrate that the Kremlin’s efforts to downplay the scale of theinvasion and its death toll among Russian soldiers were countered by an alternative framing ofthe war on social media, thus highlighting the importance of online platforms even under strictcensorship (Tang & Huhe, 2014). That being said, the most popular pages that posted contentabout the deceased soldiers still overall endorsed the war. Hence, though the proliferation ofthe information about the human toll might go against the Kremlin’s framing strategy, thedominance of the war frame seems to have emerged not out of the opposition to the invasionbut rather out of sympathy with the soldiers who participated in it. We also observe that the“war” term is still largely associated with WWII rather than with the Russian war againstUkraine. Even the frames associated with current conflict in the “war” sample are still oftenrelated to WWII, thus reinforcing the known tendency of the Kremlin to selectivelyinstrumentalize WWII memory to advance its political aims (e.g. Gaufman 2015; Makhortykh etal. 2021). It can also suggest that in the long-term, the Kremlin might find it more effective toshift from the current framing of “special operation” which does not necessarily find support (atleast based on our observations) to the more WWII-like framing that will be more in line withthis tradition of memory instrumentalisation.

We have also found several differences in the demographics and content consumptionpreferences of the random sample of VK users and the users who published posts with theterms “war” or “special operation”. One major difference is related to the age distributionswithin the samples. The random sample contained more users born between 1980 and 1999than the two other samples, whereas the latter samples contained more older users, inparticular the “special operation” one. Such a difference can be explained by severalcomplementary factors: first, older people in Russia tend to be more supportive of the regimegenerally and of the war against Ukraine in particular, and pay more attention to the waraccording to surveys (e.g., Levada-Center, 2022). While these survey results should be takenwith a grain of salt considering the tendency for preference falsification out of fear of repression(Chapkovski & Schaub, 2022), it is possible that younger Russian VK users posted less aboutthe invasion because of being less interested in it than the older users. Additionally, youngerusers even in liberal democracies are more likely to be concerned about their privacy on socialmedia and potential repercussions of their online activities (e.g., in the context of job search;Blank et al., 2014). In contemporary Russia this general tendency is aggravated by the fear ofrepression for anti-war opinions and can explain why users born between 1980-1999 (i.e. theones most active on the job market) are less likely to post about the war or, alternatively, keeptheir posts about the war hidden from the public (and thus not part of our data collection).

We also found the prevalence of interest in political content in the “war” and “specialoperation” samples as compared to the random sample. In the random sample there were nopolitics-related pages neither in the top 10 nor in top 20 public pages by the share ofsubscribers (Table 4). This is generally in line with the previous observations that only a minorityof Russian VK users follow political news pages (Urman, 2019). At the same time, there wereseveral politics-relevant pro-regime pages in the top subscriptions of the “war” sample,whereas the “special operation” sample’s top subscriptions were dominated by such pages.Our findings highlight that the users who produced content about the war were more politicizedin the pro-regime direction than average VK users are. Tsargrad TV - a nationalistic and pro-warmedia founded by Russian billionaire Konstantin Malofeev following the Russian annexation ofCrimea and the beginning of the Russian hybrid war against Ukraine - emerges as the mostinfluential (in terms of the shares of subscribers as compared to the random sample) politicalpage. The second most influential page is that of Nikita Mikhalkov, Russian film director knownfor his pro-regime and pro-war views as well as promotion of conspiracy theories (e.g., thoserelated to the COVID-19 vaccines). This highlights the importance of non-state actors for thespread of pro-war narratives on Russian social media: both, Tsargrad and Mikhalkov’s channel,are not directly backed by the Kremlin (unlike RT or state-owned TV channels). We suggest thisobservation warrants further research into such actors and their potential influence as well ason the differences and similarities in the narratives pushed by such actors and those directlyaffiliated with the Russian state.

Finally, it is important to note some limitations of the conducted study. First, our results shouldnot be interpreted as an objective representation of the perception of war framing among theRussian population. While social media-based discussions are not representative of the generalsocietal opinions in most contexts, their representativeness becomes even low in the case withcontemporary Russia since users might be hesitant to post anti-war content due to the fear ofpersecution and such content can be removed by the Russian social media platforms. This isconnected to the fact that while before the Russian invasion VK maintained at least someanti-regime public groups and pages on the platform (Urman, 2019) with Russian oppositionleader Alexei Navalny even able to strategically utilize VK to spread his messages (Dollbaum,2021), in recent years VK has blocked almost all anti-regime communities, with the blockingefforts accelerating since the beginning of the Russian invasion of Ukraine (Meaker, 2022).Second, for our data collection we used only two terms - “war” and “special operation” -whereas other terms (e.g., “invasion” or “conflict”) might also be related to the respectiveframes.

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