Remixing war: An analysis of the reimagination of the Russian–Ukraine war on TikTok

Interpretative struggles of global crises are increasingly being reflected on social media networks. TikTok is a relatively new social media platform that has achieved substantial popularity among young people in many parts of the world and is now being used to disseminate and make sense of information about the Russian invasion of Ukraine. Through a user-centered sampling approach, we collected 62 TikTok videos and conducted an in-depth qualitative analysis of them and their uploading profiles to explore how the war was being represented on the platform. Our analysis revealed a strong prevalence of remixing practices among content creators; that is, they recontextualise images, sounds and embodied self-performance within the platform-specific affordances of trends. We found that distant suffering is mediated through the emotive online self-performance of content creators, cuing their audiences toward appropriate emotional responses. Trending sounds situate videos within a singular-motif and context-diverse environment, facilitating what we theorize as affective audio networks.


Introduction
On February 24, 2022, Russia's invasion of Ukraine marked the onset of another string of crises following the waning of the Covid-19 pandemic. While crisis is arguably the norm of Western democratic societies (Ercan and Gagnon, 2014;Przeworski, 2016Przeworski, , 2019Hall, 2018), negotiating the interpretation of a crisis or how to make sense of it on social media networks has become prevalent. This is not to say that traditional media actors or governments have no impact in this participatory paradigm (Dyczok and Chung, 2022), but crises are reimagined online through the lens of particular platforms and their users. Online, contexts collapse (Marwick and Boyd, 2011;Davis and Jurgenson, 2014) and spontaneous networked and affective publics emerge (Papacharissi and Fatima Oliveira, 2012;Bruns and Burgess, 2015;Papacharissi, 2015).
A relatively new social media platform that has become popular among young people for their everyday media repertoire is TikTok (Stassen, 2020;Newman et al., 2022;TikTok Statistics, 2022). In the present study, we explored the reimagination of the Russian-Ukraine War on this platform. We employed a user-centered approach by collecting videos with the help of student TikTok users in Germany, Hungary and Spain and analyzing them using a qualitative coding framework. In the following section, we provide a brief overview of the platform's particularities before we situate it in the broader literature on war and (social) media. We then explain the research methods that we used and present and discuss our findings.

Literature review
TikTok's particularities TikTok's For You Page (FYP), an algorithmically curated starter page with an endless stream of videos determined interesting for the user based on an opaque set of variables, is of extraordinary importance for its users (Bhandari and Bimo, 2022, p. 5). Bhandari and Bimo (2022) aptly note that the foregrounded position of the algorithm on the platform takes away some of the classical "social" aspects of social media platforms. As TikTok users do not have to follow each other to engage with content, the algorithm constitutes the platform itself. View counts and viewership are less dominated by the classic social media metrics of reach by followership but are driven by virality or the content's ability to be spreadable and to spark sustained interest (Jenkins et al., 2013;Guinaudeau et al., 2022). This focus on immersive and prolonged interaction can lead to problematic use (Montag and Hegelich, 2020;Montag et al., 2021). In research on uses and gratifications of TikTok use entertainment, affective needs, escapism and self-expression emerge as the most relevant drivers of TikTok usage (Bucknell Bossen and Kottasz, 2020;Omar and Dequan, 2020;Shao and Lee, 2020). However, research has shown that the platform is also used for political communication (Medina Serrano et al., 2020) and hate speech (Weimann and Masri, 2021).
While users seem to mostly enjoy the content offered to them by the algorithm (Bhandari and Bimo, 2022), it also makes the platform prone to censorship and other types of contentregulative intervention. The use of specific words in comments can trigger ambiguous keyword lists and may lead to blocking by TikTok. As a recent German investigative report (https://www. tagesschau.de/investigativ/ndr/tik-tok-begriffe-101.html) confirms, the aforementioned keywords include "pornography" or "crack" but also "gay", "LGBTQ", "sex work", even "gas" or "slavery", and some phrases related to the Russia-Ukraine War, such as "international law" or "special operation". Of course, the relatively rigorous censorship practice and uneven distribution of visibility for different issues and communities at the margins are not exclusive to TikTok. Other mainstream video-and image-sharing apps, such as Instagram, employ similar techniques (Fitzsimmons, 2021;Jaramillo-Dent et al., 2022).
Furthermore, social media platforms always foster different forms of digital self-performance but inhibit others (Szulc, 2018) and users form complex ideas of algorithmic interaction, i.e., in the form of "algorithmic gossip" (Bucher, 2017;Bishop, 2019). Thereby, any platform logic is, first and foremost, an economic one, built for the revenue interest of the concerned platform company and its stakeholders, constructed in a deeply capitalist logic (Gillespie, 2013(Gillespie, , 2014Hearn, 2017). User identities operate within the platform affordances, testing and pushing boundaries (van Dijck and Poell, 2013;Hearn, 2017). Over time, users" practices within a platform's affordances shape the platform reflexively. On TikTok's predecessor Musical.ly, for instance, users developed complex sets of performative gestures as their voices took a backseat to lip-syncing playback (Rettberg, 2017). Creative self-performance and economic motivations of reach monetarization and connectivity merge into a "like economy" (Gerlitz and Helmond, 2013), a "remix culture" (Lacasa, 2020) or "imitation publics" (Zulli and Zulli, 2022), in which publication does not mark the end of content but the beginning of an evernew reinterpretation of content fostered by a participatory paradigm with its very own resistances and demands (Neuberger et al., 2019).
Due to TikTok's FYP-centered content curation, the videos are largely detached from the contexts of their creator profiles. Bhandari and Bimo (2022) refer to this feature of the platform as "content without context" (p. 7). However, instead of the creatorcentered curation prominent on Instagram or YouTube, TikTok content is contextualized by topic and, most importantly, socially contextualized by the imitation practices and viral trends that are prominent characteristics of the platform. This re-enactment of video snippets and stories and the recontextualization and personalization of proven concepts, such as specific sounds and camera action combinations, speak more for what we might call recontextualized content.
This paper aims to contribute to the growing body of literature exploring the particularities of TikTok. In particular, we offer an in-depth qualitative analysis of the platform-specific representation of the current Russian-Ukraine War. In the following, we discuss the literature on war and conflict reporting and representation. We present TikTok as a timely consequence of the technological progress in war coverage and within the contemporary participatory paradigm of hybrid media systems. Then, we provide a detailed description of the sampling and analysis methods that we used in our research before presenting our analysis and discussion of our study results and findings.

War representations and social media
The Russia-Ukraine War is not the first to be extensively covered on social media. The Syrian uprising in 2011 was widely shared and commented on by citizens on the scene (Al-Ghazzi, 2014). The Iraq War of 2003 was considered the first war that was accompanied by an online struggle for sovereignty of interpretation. Traditional news media were considered biased, and war blogs attracted substantial interest (Cammaerts and Carpentier, 2009). This was a turning point because previously, such as in the Gulf Wars or the Vietnam War, journalists had to negotiate complex dependency relationships with the military leadership on the ground to be able to report on the war onsite. These dependencies were increasingly loosened by technological developments such as smaller cameras and storage media, but above all, by the spread of the internet, whose prominence in the midst of a conflict situation was seen for the first time during the Kosovo Conflict of 1999 (e.g., Matheson and Allan, 2009, p. 28).
The development of smartphones and social media platforms further lowered the hurdles of demanded specialist knowledge and skill for the documentation and reporting of conflicts, which soon became multimodal, connective efforts (Bruns and Hanusch, 2017). This technological advancement marks the "era of becoming a witness" (Givoni, 2011, p. 165). The smartphone camera allows citizens to record any event, often from a dangerous setting, and widely spread their recordings to make them available to a broad public and, at times, to make sense of the event and repurpose and adapt its context (Andén-Papadopoulos, 2014;Schankweiler et al., 2018). In today's digitally networked world, witnessing and providing testimony to events such as armed conflicts is no longer exclusively tied to editorial decisions and newsroom resources. While . /fpos. . the scholarly work on war and conflict on social media still largely focuses on news media and institutions and their use of platforms (Wall, 2010;Cowart et al., 2016;Parry, 2018;Crilley and Chatterje-Doody, 2020;Dhanesh and Rahman, 2021;McCrow-Young and Mortensen, 2021;Hedling et al., 2022), analyses of user-generated content have become increasingly prevalent (Andén-Papadopoulos, 2009Al-Ghazzi, 2014;Makhortykh and Sydorova, 2017). A shortcoming of digital communication research is that it primarily focuses on Twitter, a development that is often attributed to the data availability and access restriction issues shaping the computational turn of the discipline (Berry, 2011;Burgess and Bruns, 2015;Freelon, 2018;Lazer et al., 2020). However, public organizations engaged in conflict, such as the police, also primarily use Twitter and Facebook in their crisis communication (Jungblut et al., 2022). The general preference for Twitter is also prevalent in activism and war research (Seo, 2014;Bruns and Hanusch, 2017;Manor and Crilley, 2018;Özkula et al., 2022), but studies on, for instance, Instagram, YouTube and thematic forums also exist (Andén-Papadopoulos, 2014;Dinnen, 2016;Crilley and Chatterje-Doody, 2020;Al-Rawi, 2021). However, TikTok research is still scarce (Medina Serrano et al., 2020;Subramanian, 2021;Guinaudeau et al., 2022;Kaye et al., 2022).

Imaginaries of war
The research on the self-representation of US military personnel on Facebook shows the prevalence of "moto photos", posed, personal pictures in military gear (Silvestri, 2014). While these photos can also serve to boost one's morale, they are often targeted outward, to yet-undeployed comrades (p. 115; see also Andén-Papadopoulos, 2009). Aesthetic shots of artillery hardware alone exist but are less common than personnel informally posing with their guns or "casually engaging with them in some way" (p. 115). Notably, the personnel posing on such photos show emotionless faces and position their military gear centrally, suggesting that "the weapons, rather than the people, are the central foc[i]" (p. 115). This aestheticizing focus is also common in employer-branding campaigns of armed forces and is used in the best interests of the arms industry. In her paper on arms producers' YouTube content, Jackson (2019) notes that arms producers construct a discourse of militarized national security that promotes certain normative citizen ideals and aims at prohibiting citizens' questioning of militarized national security (p. 271).
Recent studies have shown an increased focus on humanitarian and personalized perspectives in news reporting on war (Hellmueller and Zhang, 2019). This points to the important role of affective intent in conflict-related audiovisual content (Papacharissi and Fatima Oliveira, 2012;Pantti, 2013;Bruns and Hanusch, 2017;Papailias, 2019). Displays of feelings and solidarity represent important audiovisual news values in crisis contexts. Chouliaraki (2008) notes that "through their systematic choices of word and image, the media not only expose audiences to the spectacles of distant suffering but also, in so doing, simultaneously expose them to specific dispositions to feel, think, and act toward each instance of suffering" (p. 372, italics in original). Chouliaraki (2008) outlines a hierarchy of misfortune coverage from adventure to ecstatic news and claims that the former offers "maximal distance from the sufferer and no options for action toward the misfortune [one] watches", whereas the latter allows for "reflexive identification" (p. 378) with the suffering subjects. It is important to note, however, that the particular local contexts of conflicts and the witnessing of these must be taken into consideration to fully grasp "the intentionality behind the use of digital media" (Al-Ghazzi, 2014, p. 449).
Bruns and Hanusch (2017) similarly argue that the aforementioned highly engaged form of coverage "extends the concept of connective witnessing beyond the circulation of purely factual footage" and can culminate "to a point where that affective response becomes newsworthy in its own right" (p. 25). On social media, memes are a popular affective response format. Silvestri (2018) argues that remixing is an essential tool in the rhetorical function of memes that can evoke memories and emotions (p. 4001). TikTok content gains a new dimension of spreadability through networked imitation and memetic reinterpretation of contexts in the form of trends that make particular forms of storytelling more salient than others at a given point in time. We thus view TikTok as a consequential progression in the digitalized user coverage of war and argue that in our analyses of TikTok-mediated conflict, we must place particular emphasis on a particular affordance of the platform: its fostering of creative self-performance.

Methods
Due to its relative novelty, TikTok is still an understudied platform. Its specific affordances also create specific challenges that we had to accommodate during the research process. A challenge that we encountered from the beginning of the research process was the platform's strongly foregrounded algorithmic curation regime. Before data collection commended, we downloaded the application to familiarize ourselves with the interface, and search for content related to the war using hashtags and looking at profiles to get acquainted with the object of study. Throughout this initial digital walkthrough on the platform, we noticed that the war had received considerable attention, but after this early hot phase, the topic vanished from our FYPs. While others reported similar observations (Nrk, 2022), the exact political workings behind them can only be speculated about. Regardless of the platform company's intention, this presented a problem in our endeavor to sample TikTok content. The research community's helplessness in the face of asymmetric data provision by platform companies is a long-known problem (Freelon, 2018;Tromble, 2021). Since TikTok has no official API at the moment, researchers have to rely on community provided unofficial packages such as Deen Freelon (2023) "Pytok" for large scale data collection. These, however, are vulnerable to changes on the platform (see e.g., https://github.com/dfreelon/pyktok/issues?q= is%3Aissue+is%3Aclosed).
We decided to employ a user centered approach as qualitative approaches are more resilient to change on the platform side (Schellewald, 2021). Our solution was to focus fully on an approach based on what users deemed relevant. This is a common practice when it is difficult to determine sample populations in social media content (e.g., Poell and Borra, 2011, p. 700). Our approach was informed by pragmatic decision-making, the influence of the platform's censorship regime, the little clarity regarding the platform's reach metrics and their meaning and our need for rich data suitable for in-depth analysis. The user-centered strategy that we chose allowed us to maintain as much of the ecologically valid relationship of the user with the platform as possible without relying on long lead Participants were selected through convenience sampling and were recruited in undergraduate communications and media courses. With an anonymized survey, we asked students who use TikTok to "open the application and select two videos that deal with the war in Ukraine in the broadest sense", and provide the links to these videos in an open response mask. Ethical approval was not required for the study involving human participants in accordance with the local legislation and institutional requirements. The participants provided written informed consent for participation in the study.
The survey was conducted online from May 23 to June 12, 2022 with the survey tool SoSci Survey (Leiner, 2019). Thirty-three students (26 female and four male, three non-response; mean age 21.5) from Germany, Hungary and Spain participated in the survey and provided us with a total of 72 videos. We were able to retrieve 68 of those videos, and after checking for duplicates, we were left with 62 unique videos (Appendix 2). The average length of the videos was 53 s. Access to the videos can be provided via a OSF repository upon request.

Collaborative process
Because we followed an inductive research approach that one might call "grounded theory lite" (Braun and Clarke, 2006, p. 81), it was important to us to have frequent discussions on the study, which is also the recommended procedure for inducing reflexivity in qualitative research (Mauthner and Doucet, 2003). After we decided to use the final research approach explained above, we drafted a first analytical framework and collected data from students. We then met again to go through all the responses and videos together and conducted a test coding of five videos each. With this test coding, we reworked our analytical framework together. The final version of the analytical framework resulting from our deliberations can be found in Appendix 1. Finally, we split the sample and met again after the coding phase to go through the notes and content together several times for the final analysis.

Analytical framework
Our analytical framework was oriented toward qualitative video analysis and emphasized the affordances of TikTok. An obvious focus of video analysis is the action on the screen. However, any comprehensive video analysis must also include an analysis of the camera action: the acts carried out by the camera, such as zooms, framing, what is seen and what is unseen, and the post-production acts, such as effect and filter application and music and sound editing. The importance of these dimensions is recognized by different approaches to video analysis (Moritz, 2014;Moritz and Corsten, 2018). Reichertz (2014) aptly points out the following: On TikTok, the aforementioned acts of engagement with the viewer, and hence also the intentionality of the content, become salient in the various forms of remixing contexts and the application of filters and sound.
Our analysis focused on two main dimensions: the creator and the content. Video analysis often applies a sort of partiture or sequence protocol, sometimes even on the level of individual frames. In the present study, we used the video as a unit of analysis because TikTok videos tend to be short already. We coded in three subdimensions within the content and user dimensions. We traced the contextuality of the videos, with a specific focus on the uploading user's profile: gender, user interactions in content, user and content metrics and change of profile over time. The narrative construction dimension focused on the action in front of the camera: where, what and who is depicted in the content. We also addressed the intentionality of the content, which we coded last. Finally, the production dimension focused on the camera action (angle, cuts, and sound) and the platform-specific practices of remixing sound and footage (trends).
It is important to note that the aforementioned coding framework, like any partiture of a piece of audiovisual content, carries out only an orientation function as it is inseparable from the videos and is already an interpretative step (Reichertz, 2014, p. 68). We therefore provide many examples in our analysis chapter and supply a list of all the video creator handles included in our sample (Appendix 2). We can provide the videos as MP4 files upon request.

Findings
This section of the article follows the structure of the analytical framework. Firstly, we discuss the roles of content creators, grouped into two broad categories: professionalized and amateurs. In both categories, we discuss the most salient findings in terms of engagement and self-performance. Secondly, we discuss the two ways in which the content is conveyed: through visual editing and sound editing. On this level of analysis, recontextualization and the particular use of media remixes are addressed.

Content creators Professionalized content creators
Professionalized content creators consist of official, verified accounts of news outlets or newscasters and of social media professionals, such as influencers or public relations staff. These experienced content creators have consistent visual practices and large video repertoires. Their production efforts appear to be high, with personal involvement in the creation and editing of footage. Interestingly, experienced social media content creators tend to emulate the political or news television style. Their positions in relation to and interactions with the camera mimic those of the traditional news host through the use of the golden ratio, often in front of a greenscreen, employing maps and superimposed content as visual aids. However, unlike the traditional news actors in our sample, such as a Bavarian public broadcaster or a Spanish news channel, .
/fpos. . content creators do not claim to adhere to any journalistic practice. Those among them focusing specifically on creating content for social media mimic the journalistic style but do not adhere to journalistic values. They show no degree of organization or embeddedness in any journalistic structure; rather, they produce content self-referentially and within the framework of their self-performance. Both professional journalists and social media influencers appear as hosts of their content, similar to a televised political program. However, they are different from traditional television hosts in that they are in informal attire and frequently use memetic content superimpositions and informal, easy-to-understand language. This duality is especially intriguing as influencers tend to emulate traditional news anchors, while news anchors emulate influencers (this seems to be a potential future mediatization research topic). An example for the latter is video 1002 from the Bavarian public broadcaster #Infofluencer. Its mix of providing information and eliciting emotional responses is the reason that Student 10 selected it, claiming that it is "about how the war could end" and adding, "On the one hand, this gives hope for an end, but [it] also shows the harsh reality of what has happened".
Interestingly, TikTok creators initiate very little to no engagement. They do not call for action or connect much with the users commenting on their videos. This may be explained by the specific affordances of the platform, as TikTok does not reward the building of a large followership or community as much as other platforms do. There is also no strong breach in the consistency of self-performance in relation to the Russia-Ukraine War. This does not mean that the content of the videos remains unchanged. For example, user @valerisssh, a young Ukrainian influencer with a large audience, now almost exclusively talks about her opinions about Russia, her refuge or home. However, the integration of war-related content into users' profiles does not change their self-performance; rather, the content assumes a consistent style that is familiar to the audience and centered around the influencer. For example, in video 1401, the creator shares that "Putin killed [her] 18-year-old brother" in a photo montage. The 13-s video begins with the influencer's mirror selfie (the first 7 s), with the aforementioned text, and then shows the viewer three images of herself and her brother as regular teenagers before the war (meticulously edited to fit the music). Although the video was produced to honor the influencer's lost brother, the frame remains focused on the influencer's persona.
In other words, PCCs stay true to the online identities they have established, following their distinctive visual appearance and content editing style, and frame themselves as the central vocal points in their content. They are still recognizable as the same influencers, no matter what the actual topic of their content is. Creators who focused on their own bodies before the war continue to do so, and those who primarily made informative content before the war still do. Those who shared information about their personal lives before the war continue to do so even if it means showing their desperation and sadness. These creators communicate a strong and compelling sense of agency as they seem to stay in control and showcase their resilience in the midst of adversity.

Amateurs
Contrary to PCCs, amateur creators are often not identifiable, and in our sample the persons behind such accounts are often not visible. Their videos are often TikTok edits of footage taken from television or other social media users and platforms and appear to have been quickly put together in "low-budget" and "low-effort" productions. Consequently, these creators do not have a particular online selfperformance and do not attempt to authentically portray a person. Instead, they create engagement using the TikTok specific editing style and niche topics. The most salient topics appearing in these videos are weapons and military footage, and the creators showcase a vague genre of military enthusiasm that aestheticizes military gear. They achieve this by using engaging music and fast cuts and angles that highlight physical features showing strength and superiority, such as filming a tank barrel from below or missile artillery rounds fired. These types of videos create a unifying sense of resistance and cohesion against a common enemy and engender emotional responses with little effort. Student 13 captioned their video showing snippets of the Georgian and Ukrainian military and protests with "both countries have the same enemy". A video montage of alleged fallen Ukrainian soldiers was captioned by Student 8 with a "very emotional, nice gesture to show heroes who fought for Ukraine . . . Very personal".
Unsurprisingly, amateur content creators do not attempt to engage directly with their audiences. Instead, they employ the particular TikTok vernaculars that are believed to be crucial for virality in an attempt to create platform engagement and appear on the audiences' FYPs.

Media recontextualization Visual editing
In their videos, creators consistently employ recontextualization and remixing practices. Overwhelmingly, both professionalized and amateur content creators take existing footage to create their TikTok content by editing together or reacting to television or other social media content. Using such footage, they mix contexts that unveil the intrusion of the Russia-Ukraine War into the civil areas of everyday life. This was also recognized by the students who sent us videos. For instance, students shared that they had "never seen "simple" people train in defence" (video 602) or communicated their sadness over witnessing "the conditions under which people and children who had nothing to do with the decision-making have to live" (video 2202). In this latter video, a young girl sings a song from the Disney production "Frozen" sung by Princess Elsa, an ordinary thing for a young girl to do and for their caretaker to film. However, the scene takes place in a bunker or shelter, which aptly portrays the displacement of ordinary citizens' lives.
Video 601 is another interesting case of an active and recurring professionalized profile in our sample: that of @valerisssh, which shows three different contexts. Firstly, the creator is a young influencer who is personally affected by the war and has left Ukraine; in the video, she invites the viewers to witness the war from her perspective. Secondly, the specific video is a reaction to a thirdperson footage of elderly Ukrainian women who remained within the local context of the war and were interviewed about what happened to their livelihoods during the attacks. Thirdly, the footage was filmed from the point of view of a soldier who is faceless in the video and invites the viewer to watch the video through his eyes. The distant sufferers are thereby brought closer to the viewer in a recontextualization sequence. The influencer creates the necessary . /fpos. . proximity for an ecstatic response from the viewer. The appropriate emotional response is mediated through the influencer, who is also in control of whom the ecstatic response is to be elicited from. This is perceived as "the voice of the people" and as "very impressive" by Student 6. In a similar video (1001), a German folk singer films her emotional response to a video that shows a soldier and his infant son emotionally saying farewell to each other before the former's deployment. The creator uses the emotionality conveyed by the video as an input to create her own embodied representation of it, with the intention of eliciting a similar response from the viewer to both her and the video. She even explains the action seen in the video in writing to justify this response and underscores it with the addition of a German pop-folk song with a fitting motif.

Sound editing
Background music and sound are crucial parts of the platformspecific remixing practices. In most cases, elaborate background music that at least fits the visual content mood-wise is used. However, many videos show a considerably high degree of audio editing. In such instances, music is not used only to underscore a mood, but its rhythm, speed, lyrics and motifs are carefully selected and timed perfectly to match the visual content. An example of this is video 1802 by a professional interior decor company in Ukraine, which shows its office space before and after its destruction during the Russia-Ukraine War. On TikTok, engagement with trending music is a crucial part of visibility. Users can find trending sounds and repurpose them without specific skills and hardware or software knowledge, using only their smartphones. This significantly lowers the hurdles for compelling narrative construction.
As previously mentioned, amateur creators also rely on sound editing and make an effort to select and edit visual content and sound together. In the case of video 3202, television footage of country leaders was not only seamlessly edited using consistent visual aids, such as color correction and transitions; it was also made emotive and powerful through the use of a specific piece of viral music to which the visual content was immaculately matched. In other words, TikTok users can jump on trending sounds quickly, thereby contributing to the formation of what we might call affective audio networks of sounds used in similar contexts.

Distant su ering and military enthusiasm
The theme of suffering is conveyed in the TikTok videos in the sample through the use of visuals of the war-torn country that are frequently employed in videos. The most prominent of these visuals are images of shelled buildings or cities and vehicles. The war and its consequences are made visible through images and footage of material objects, but the suffering of civilians or soldiers and human casualties are rarely depicted. Nonetheless, one student (Student 20) wrote that their video choice, which does not demonstrate human affectedness, "shows the consequences properly", and another student (Student 22) noted their empathetic response to the depiction of the war-torn country. TikTok videos such as 2201 or 2901 are photomontages that were edited to match emotive music, showing before-and-after photographs of cities and buildings in Ukraine. The consequences of the war are thus shown as purely material; in the cases in which people are also shown, they happen to be soldiers, usually presented in full tactical gear, hence remaining uniform and impersonal. Importantly, however, there are moments of humanization, when soldiers are depicted doing something unrelated to fighting, such as joking around while on the highway or dancing. These are the instances that allow for ecstatic responses from the viewers to military personnel. However, ripped clothes or bloody bodies are not shown, seemingly suggesting that what is war-torn is the country, not its people. This is interesting because shocking pictures are usually important for the depiction of conflict and catastrophe. A reason for this could be the creation of a unifying sense of the war-torn nation and its resilient people. It can also be both an intended and unintended consequence of algorithmic curation and censorship by the platform. The creators counter such censorship by using hashtags such as "fake body" or "airsoft". In this way, creators disguise real war action as fictional, hence circumventing the platform's censorship regime, which flags and removes potentially violent content.
The aforementioned depiction of the material consequences of the Russia-Ukraine War rather than its human casualties transforms the image of the war on TikTok, showing that the war is not really life-threatening but only affects people's livelihoods and material environment. Thus, the actual meaning of the war for the Ukrainian people remains opaque. A type of TikTok content that exemplifies this very well is the military anesthetization video. Here, we often see machinery and weapons in action: shooting missiles or artillery projectiles from somewhere at something, demonstrating a kind of unaffected excitement over "blowing something up", as in video 2401, which is described as "strange" by Student 24. In one video (2002), two soldiers in a trench are shown being shot at with artillery or mortars and shooting back at their opponents. Yet, together with the engaging music, no urgent sense of danger is made salient, just the excitement of the action conveyed. This is further emphasized by the fact that the soldiers even adjust the camera after a particular close hit. No one seems to be in any immediate danger of dying.

Emotional cues and distance bridging
While the viewer is mostly distanced from the deadly realities of the war, content creators often practice a sort of emotional response cuing to elicit an appropriate emotional response from their audience. They achieve this by placing themselves in front of the content they adopted, either in the sequence or the frame, and showing the audience their emotional state, perhaps with the intention to create emotionally contagious effects (e.g., Coplan, 2006). These types of videos can be said to belong to the popular genre of reaction videos (e.g., McDaniel, 2021). TikTok fosters the reaction video style by means of the "stich" function and the overall lowered hurdles to content editing. In this sense, smartphones, more specifically social media apps such as TikTok, allow users not only to cover armed conflict and share their related experiences (or allow other users to witness this firsthand testimony) but also to share their embodied response to the suffering. We find that the consistent advancing of collapsing contexts eventually amounts to a recontextualization of embodied experiences on TikTok, where the "embodied performance of eyewitnessing" (Andén-Papadopoulos, . /fpos. . 2014, p. 760) mediated through the smartphone camera action is furthered by the simplicity and affordance of remixing images, sound and movement. At this instance, creators function as mediators, bridging the emotional distance between their audience and the war and allowing ecstatic coverage (Chouliaraki, 2008) within the platform affordances and censorship regime. In other words, the lack of graphic or drastic images and explicit stories is compensated by emotional response cuing.

Remixing and a ective audio networks
The practice of remixing (Lacasa, 2020) shapes the reimagination of the Russia-Ukraine War on two levels. Firstly, creators employ visual editing practices to adopt television and other social media footage related to the war, which they recontextualize to their profiles. It is this practice that follows and facilitates the collapse of contexts (Marwick and Boyd, 2011) on the platform. Users imagine their audiences and adopt and adapt content of other creators to fit their personal branding. On the one hand this recontextualization is facilitated and constrained by the platform affordances. It seems trivial yet is important to realize that stitching or remixing as a platform feature has become industry standard (see YouTube shorts or Instagram remix). It is a defining feature for short-video content production and users perform their remixing practices within this affordance. In other words: Remixing has been written into the social media logic (van Dijck and Poell, 2013).
On the other hand, users perform these reimagination practices within the boundaries of their profiles' commodified self-performance. As Szulc (2018) notes, users' profiles are to a large extent defined by the abundance created through constant updating. The core self of a user, that is the profile created upon signing up (name, gender etc.), retreats behind the datafication logic of platforms (van Dijck and Poell, 2013); on TikTok with its strong focus on the algorithmically curated For You Page in particular. The profile core self on TikTok is so minimized that the self is performed almost exclusively in content. The remixing of content thus embeds it not within a static context of a profile but within the continued performance of the self.
Secondly, sound remixing facilitated by the platform-defining feature of trending sounds is widely used. Zulli and Zulli (2022) write that "[TikTok] networks form through processes of imitation and replication, not interpersonal connections, expressions of sentiment, or lived experiences" (1873). While we agree with the idea that interpersonal connection, such as through followership or community-building practices, is not as relevant on the platform as on others, we found that it is precisely the embodiment of expressions of sentiment that, facilitated by the use of sounds and sound editing practices, creates what we call affective audio networks. As such, the sounds used match not only a single creator's visual content through rhythm and motif but also that of others. This has two functions: to elicit appropriate emotional responses from the viewers and to connect the content to other trending creations with the same motif and similar contexts. While the first function thus serves as an orientation for the audience within the creator's self-performance, the second function orients the creator's self within the platform. Papacharissi (2011) aptly wrote that in the "networked and remixed sociabilities" of SNSs "a sense of place is formed in response to the particular sense of self, or in response to the identity performance constructed upon that place" (p. 317). In that sense, trending sounds can be seen as a signpost to aid that sense of place. As Ramati and Abeliovich (2022) point out, voices can thus, as an original sound, become and remain an integral part of a network even when the bearers of the voices themselves have long since gone.

Limitations
Our study, like any other study, has limitations. Our sample selection was limited in two crucial ways. Firstly, a small number of users forwarded the content that we analyzed. We therefore cannot make any claims to generalizability and finding the same videos on the app in a replication study seems unfeasible. However, as our study was an explorative inductive one, this was not necessarily an issue. Nonetheless, larger surveys offer the potential for providing more insight into not only more content but perhaps also detailed measures of user experience. Secondly, we approached the topic of the Russia-Ukraine War from the lens of students, most of whom are not directly affected by the war. It would be enriching to directly sample videos from Ukrainian youths and make crosscountry comparisons. Additionally, our sample was generally in favor of Ukraine. Introducing a dynamic component, such as drawing subsamples of content from different periods of the war, could also enhance the time-sensitive validity of a study on an ongoing conflict. A longitudinal perspective could offer both a broader data basis and a solution to the very practical problem of data availability. We frequently experienced content availability issues during our research, which is also why we offer readers access to a video repository of saved TikTok content and suggest that future researchers strategically save content on an ongoing basis. In addition, we did not address disinformation issues. We did not attempt to analyze the veracity of our content sample, but future research could address the potential for political propaganda and misinformation/disinformation on TikTok regarding the Russia-Ukraine War.

Conclusion
In this paper, we present our findings from our in-depth qualitative analysis of TikTok videos concerning the Russia-Ukraine War. We collected TikTok videos from young users in Germany, Hungary and Spain and gained insight from these into how the image of the war is being constructed on the platform. The videos were analyzed on two levels: the content creator and content production levels. Thus, our analytical framework allowed us to go beyond the particular case focused on here and to extend our analysis and findings to broader platform-specific recontextualization affordances.
Content creators can be grouped into two distinctive categories: professionalized creators and amateur creators. Professionalized creators, who can be professional journalists or social media influencers, employ a consistent self-performance-centered content style to drive engagement with their audiences. For amateur creators, the primary emphasis shifts from online self-performance to the potential virality of the content. Content created by amateur creators does not depict the person behind the video and often focuses on a very specific aspect of the Russia-Ukraine conflict, such as the political actors or the military. Instead of focusing on building authentic audience relationships, the content is designed to game . /fpos. . the algorithm. This may be achieved through online person-centered narratives, but the creators perhaps rely more on the skillful use of media remixes, taking into consideration trending memetic expressions, challenges, framings and viral sounds. The Russia-Ukraine War's image on TikTok is first and foremost emotional, especially in instances where the appeal of the content leans toward informative, quasi-journalistic styles. However, the footage directly showcases the shelled buildings and cities; in other words, things, not people. There is a lack of footage showing human suffering or lifeless bodies. Thus, in many instances, the war-caused human suffering is distant from the audience. In instances where people are shown, the people happen to be resilient civilians and skilled military personnel facing adversity, united, not dispersed, and angry or hopeful and recovering, not desperate. Such depiction of the war is likely also a result of TikTok's censorship regime. In this way, the war in Ukraine is constructed as a militarized action that largely has consequences only for material realities.
However, content creators can function as intermediaries for ecstatic war coverage by recontextualizing the images that they adopted within the framework of their personal profiles and through emotional response cuing. By showcasing appropriate emotional responses in a TikTok-style reaction video, they facilitate emotionally contagious effects. By situating their content within a broader network of trending sounds, they mediate distant suffering through emotive online self-performance in a singular-motif and contextdiverse environment, facilitating what we theorize as affective audio networks.
Based on our analysis, we identified further potential directions for communication and media research. As noted, when we discussed the two content creator categories (professionalized and amateurs), we found it intriguing that professional journalists and social media influencers employ a similar person-centered approach to convey their content, borrowing from both journalistic practice and influencer industry standards. A potential matter to explore is how the presentation style of actual professional journalistic actors is adjusted to the platform-specific emotive style. Affective audio networks demand more research to contribute to the growing body of theory on (affective) networked publics and the specific workings of remixing and recontextualization within them. Finally, political communication on TikTok is understudied. Future research should investigate topic distributions and modes of political speech on the platform. Given this analysis, it is clear that TikTok will continue to shape how young people experience social media and spark sustained interest by media and communication scholars.

Data availability statement
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary material.

Ethics statement
Ethical approval was not required for the study involving human participants in accordance with the local legislation and institutional requirements. The participants provided written informed consent for participation in the study.

Author contributions
All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.

Funding
We acknowledge support by the Open Access Publication Initiative of Freie Universität Berlin.