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Citation: Twomey J, Ching D, Aylett MP, Quayle M, Linehan C, Murphy G (2023) Do deepfake videos undermine our epistemic trust? A thematic analysis of tweets that discuss deepfakes in the Russian invasion of Ukraine. PLoS ONE 18(10): e0291668.
Copyright: 2023 Twomey et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data will not be fully available for legal/ethical concerns. Namely that the dataset contains un-anonymised user data and the ethical permission to carry out this research was predicated on this data staying confidential. The original dataset will be handed over to UCC psychology departments technical officer (currently Aaron Bolger aaron....@ucc.ie) for storage and access for anyone who meets criteria for access to the confidential data.
Funding: This work was supported with the financial support of the Science Foundation Ireland grant 13/RC/2094_2 and co-funded under the European Regional Development Fund through the Southern & Eastern Regional Operational Programme to Lero - the Science Foundation Ireland Research Centre for Software (www.lero.ie, Award PP5004). These groups had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Synthetic media are a type of audio-visual media which has been partly or fully generated/modified by technology [1]. Deepfakes are a new form of synthetic media which interpolates artificially generated media into an existing video, often with intent to imitate or mimic an individual. Researchers and commentators have argued that deepfakes have the potential to undermine truth, to spread misinformation and to undermine our trust in information, media and democracy [2]. The increasing prevalence of fake videos could undermine what we know to be true [3]. Specifically, academic researchers believe that deepfakes could create a situation where fake videos are believed to be real and conversely, where real videos are denounced as fake. Fears of deepfakes being used to spread disinformation have been realised during the Russo-Ukrainian war. We have seen fake videos of both Russian President Vladimir Putin and Ukrainian President Volodymyr Zelensky, as well as many satirical and entertainment uses of deepfakes around the crisis. Our paper seeks to provide empirical evidence for the hypothesised and forecasted harms of deepfakes to truth and knowledge. The aim of this paper is to understand the nature of deepfake discourse on social media in the context of the Russo-Ukrainian war.
In this paper, we analyse Twitter discourses around deepfakes in relation to the Russo-Ukrainian war by carrying out a thematic analysis on relevant tweets during the first months of the 2022 invasion. Our study is the first empirical analysis carried out on the use of deepfakes in wartime misinformation and propaganda. As deepfake technology becomes increasingly accessible, it is important to understand how such threats emerge over social media. Understanding the current threats of deepfakes will have implications in how social media companies and academic researchers deal with harmful deepfakes online. Understanding how the threats of deepfakes emerge online is a significant step in learning how to mitigate their harms. The current paper also has numerous implications for academic research on deepfakes. Our research explores the epistemic harms of deepfakes in practice, as opposed to the theoretical discussions of the concept in academia [4]. We also provide a non-exhaustive timeline of the use of deepfakes and other synthetic media in the Russo-Ukrainian war. The provided timeline is important as both a record of the uses and the impact of deepfakes during the Russian invasion of Ukraine and as a means to gauge the type and quality of synthetic media content created during the conflict.
Public outrage and interactions with the Russo-Ukrainian war have been mediated by social media platforms and technology. Cell-phone journalistic practices mean that first-hand accounts of the atrocities of the conflict are readily available online [33]. Internet activism has meant that individual users of the internet have been able to co-ordinate DDOS attacks on Russian websites [34]. While modern technologies have facilitated the spreading of first-hand accounts of the brutality of the war, they have also been used to spread misinformation and propaganda [35]. The Russo-Ukrainian war has seen for the first time, the use of deepfake technology in wartime propaganda and misinformation. Fig 1 provides an overview of deepfakes (as well as similar synthetic media that have been misidentified as deepfakes) used in the Russo-Ukrainian war during the first four months of the invasion. In this section we will discuss the key events relating to deepfakes, contested deepfakes and other synthetic media in the war in more detail.
In early March a deepfake of Russian president Vladimir Putin emerged, showing the Russian president announcing peace with Ukraine. The deepfake was first published online in the first week of March on the reddit r/sfwdeepfakes and r/ukraine communities [37]. It was posted with an acknowledgment that it was fake and the user who submitted this video claimed to have found it on the social media site Telegram and added their own subtitles. The deepfake was then published on Twitter on the 18th of March. This is the version that was reported on by news agencies. The version posted on Twitter did not contain subtitles, suggesting it may have come from Telegram. This deepfake was unique out of the major examples of the technology in the conflict as it has been suggested that the audio was also generated using AI [38].
As with all qualitative research, is also important to consider the biases and positionality of the research team. It is impossible to make claims to the demographics of the dataset, except that both it and the research team broadly consisted of privileged voices from western Europe and north America. Our research questions do not focus on the specific experiences of people involved in the war with deepfakes, as the specific demographics and anonymity of Twitter reduce any claims to the national identities of any of the participants. While we have justified our decisions to work on this demographic, it does highlight possible alternative avenues for the analysis of deepfake content on social media. Any qualitative research on the experiences of the Ukrainian people with deepfake disinformation (such as the Zelensky deepfakes) would require a different mode of analysis, and a different method of data collection which would avoid the risk of studying false identities online.
We used and inductive, reflexive thematic analysis [54] to understand and illustrate patterns in our data. We judged thematic analysis as the most appropriate way to address the data set, since the approach is flexible, allowing for many different levels of interpretation. Moreover, there is no existing well-defined theory of how people understand and respond to deepfakes that could guide a more deductive or theory-driven approach. The thematic analysis broadly followed the six steps outlined by Braun and Clarke [55]. Initially, while applying the inclusion and exclusion criteria, we familiarised ourselves with the data, drafting up a series of rough codes in a text document. We then used NVIVO software to descriptively open code the data. Once open coding was complete, we carried out a number of iterative rounds where we sought to meaningfully define observed patterns in the codes. Specifically, we first arranged the codes into small groupings and sub-themes within NVIVO, and then worked on developing larger overarching themes. The majority of this work was done by the primary researcher (White-Irish, Male), with regular consultation with the broader research team throughout the process to iterate on codes and themes. We chose to have one primary researcher do this work as the research often required making judgements to the truth or falsity of deepfake claims and the primary researcher was most aware of both the news media within the dataset (for exclusion of news headlines) and the specific cases of deepfakes used in the war. This was an inductive and iterative process. For example, while initially we approached formulating the codes as a typology of responses to deepfake misinformation, but we found that the range of novel themes and usages of deepfake content outside of misinformation necessitated a broader and more comprehensive set of themes.
Our analysis produced three main themes of online content related to deepfakes and the Ukraine crisis; 1) deepfakes and misinformation, 2) deepfake fuelled scepticism, and 3) non-misinformation related deepfake discourses. The first and third of these are relevant to our first research question: understanding how people reacted to deepfakes online. The second of these, addresses our second question showing epistemic distrust as a result of deepfakes. Each of these will be discussed in the following section using fictionalised versions of the quotations from the dataset.
A significant element of deepfake discourse highlighted in our analysis was the humorous and educational discourses around deepfakes. While these have generally been viewed as positive potentials of deepfakes [62], our dataset showed more complex views on the non-misinformation deepfakes. Because they used images of politicians and often related to current events, the humorous deepfakes in the war still served as a way for users to make political commentary through satire and parody. Humorous deepfakes were generally celebrated by users, but many found the videos uncomfortable, especially in instances where the deepfakes were graphic or violent. This highlights the need for more nuanced research into creative uses of deepfakes.
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