Papers by Mykola Makhortykh
Elgar Encyclopedia of Political Communication, 2025
Propaganda is one of those communication science concepts that often overlaps with other communic... more Propaganda is one of those communication science concepts that often overlaps with other communication phenomena (e.g., public relations, political campaigning, or psychological warfare; Laskin, 2019) and has many definitions depending on the area in which it is used. These definitions range from it being a form of ‘manipulation of the rational will to close off the debate’ (Stanley, 2015, p. 48) to the ‘false or misleading information or ideas addressed to a mass audience by parties who thereby gain advantage’ (Huckin, 2016, p. 126). However, most of these definitions agree that the core aspect of propaganda relates to ‘the deliberate attempts to persuade individuals to behave and think in a particular way’ (Taylor, 2003, p. 6), which often involve surrendering individual agency and interests for the sake of the larger entity (Laskin, 2019). The rest of the entry first discusses the evolution of propaganda from analog to digital formats, then reviews key areas of propaganda research dealing with the detection of propaganda content, agents, and impact, and concludes with a discussion of the challenges of tackling propaganda.
Elgar Encyclopedia of Political Communication, 2025
Digital memory is constituted by the set of online practices that deal with preservation, transmi... more Digital memory is constituted by the set of online practices that deal with preservation, transmission, and engagement with information about the past. Varying from everyday individual experiences to historical (counter) discourses, such information is mediated by a broad range of online platforms, including social media (Smit et al., 2018), messengers (Schwarzenegger & Wagner, 2023), online encyclopedias (Pentzold, 2009), and search engines (Zavadski & Toepfl, 2019). The diverse platform affordances shape various formats of digital memory practices – from audiovisual tributes (Knudsen & Stage, 2013) and internet memes (Makhortykh & González Aguilar, 2020) to rogue archives (Harel, 2022) and hashtag campaigns (Bosch, 2017) – which influence the development of cultural norms and articulation of identities (Menke & Hagedoorn, 2023). The entry briefly reviews distinctions between analog and digital memory, followed by a discussion of the role of digital memory in political communication, the methods used for studying digital memory, and possible implications of the rise of artificial intelligence (AI) for digital memory.
Elgar Encyclopedia of Political Communication, 2025
This entry provides a definition and examples of algorithmic biases, outlines common sources of s... more This entry provides a definition and examples of algorithmic biases, outlines common sources of such biases, and examines methodological approaches to their detection and mitigation.
Telematics and Informatics, 2024
This article presents a comparative analysis of political bias in the outputs of three Large Lang... more This article presents a comparative analysis of political bias in the outputs of three Large Language Model (LLM)-based chatbots-ChatGPT (GPT3.5, GPT4, GPT4o), Bing Chat, and Bard/Gemini-in response to political queries concerning the authoritarian regime in Russia. We investigate whether safeguards implemented in these chatbots contribute to the censorship of information that is viewed as harmful by the regime, in particular information about Vladimir Putin and the Russian war against Ukraine, and whether these safeguards enable the generation of false claims, in particular in relation to the regime's internal and external opponents. To detect whether LLM safeguards reiterate political bias, the article compares the outputs of prompts focusing on Putin's regime and the ones dealing with the Russian opposition and the US and Ukrainian politicians. It also examines whether the degree of bias varies depending on the language of the prompt and compares outputs concerning political personalities and issues across three languages: Russian, Ukrainian, and English. The results reveal significant disparities in how individual chatbots withhold politics-related information or produce false claims in relation to it. Notably, Bard consistently refused to respond to queries about Vladimir Putin in Russian, even when the relevant information was accessible via Google Search, and generally followed the censorship guidelines that, according to Yandex-related data leaks, were issued by the Russian authorities. A subsequent evaluation of Gemini showed that the chatbot restricts political information beyond what was officially confirmed by Google. In terms of false claims, we find substantial variation across languages with Ukrainian and Russian prompts generating false information more often and Bard being more prone to produce false claims in relation to Russian regime opponents (e.g., Navalny or Zelenskyy) than other chatbots. We also found that while GPT4 and GPT4o generate less factually incorrect information, both models still make mistakes, with their prevalence being higher in Russian and Ukrainian than in English. This research aims to stimulate further dialogue and research on developing safeguards against the misuse of LLMs outside of democratic environments.
UNESCO, 2024
This paper explores the risks, challenges and opportunities of AI advancements for Holocaust know... more This paper explores the risks, challenges and opportunities of AI advancements for Holocaust knowledge and understanding, and asks: how should policymakers, online platforms (including social media and AI tool builders) and educators respond to this new reality? How can the facts of the Holocaust be safeguarded?
EKAW 2024: EKAW 2024 Workshops, Tutorials, Posters and Demos, 24th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2024), 2024
Generative AI, in particular large language models (LLMs), can significantly impact the journalis... more Generative AI, in particular large language models (LLMs), can significantly impact the journalistic practices. One possible application of LLMs in newsrooms is to assist journalists in fact-checking false and contested claims. However, the research on LLMs' ability to reliably verify (political) information remains limited. This study examines how five LLMs fact-check claims related to migration in Switzerland. We test whether the prompting strategy (e.g., mentioning an opinion on the issue or assuming the role of a journalist or a voter) and the political leaning expressed in the prompt affect the accuracy of LLM-generated fact-checks. Analysis of 1,493 outputs shows that LLMs achieve 60.4% accuracy in fact-checking overall. However, we find a drastic difference across the claims varying from 100% accuracy for one false claim to only 10.2% accuracy for a true claim. Contrary to our expectations, acting as a journalist led to a lower quality of the outputs if compared to other strategies. Finally, with the minimal temperature values, LLMs show a relatively high, yet not absolute, degree of consistency in their responses. These findings highlight that while LLMs can aid fact-checking, their output is still prone to systematic errors. Factors leading to these inaccuracies should be studied further to identify best practices for using LLMs in newsrooms.
TRIALOG, 2024
The rise of digital technologies and geographic information systems (GIS) has transformed the pro... more The rise of digital technologies and geographic information systems (GIS) has transformed the process of mapping spatial phenomena ranging from pandemics to elections to the effects of climate change. Armed conflicts are no exception, with several studies discussing how digital maps can influence the representation of war destruction and the planning of postwar reconstruction and recovery. However, a number of questions still remain: For instance, how do digital mapping projects use different platform affordances to track the impact of contemporary wars on urban spaces? What possibilities for interacting with the mapping projects are provided to their users? And how can different types of digital maps facilitate the process of postwar recovery in Ukraine? To address these questions, this article examines a selection of projects that map the destruction of Ukrainian cities caused by the ongoing Russian invasion. Using a combination of interface analysis and visual discourse analysis, this article examines how four types of mapping projects-i.e., private, state-affiliated, NGO-affiliated and investigative journalism mapping initiatives-track damage inflicted on Ukrainian cities and asks whether these projects can be used for planning urban recovery in the future. This article concludes that, independently of their type, most of the mapping projects use their affordances in a similar way by focusing on spatial and temporal visualisations of damage to Ukrainian cityscapes, which provide limited possibilities for user interaction. The possibilities and limitations of existing mapping projects for planning the postwar recovery in Ukraine are then briefly discussed.
FAccT '25: Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 2025
The increasing reliance on complex algorithmic systems by online platforms has sparked a growing ... more The increasing reliance on complex algorithmic systems by online platforms has sparked a growing need for algorithm auditing, a methodology evaluating these systems' functionality and impact. In this paper, we systematically review 176 peer-reviewed online platform-focused algorithm auditing studies and identify trends in their methodological approaches, the geographic distribution of authors, and the selection of platforms, languages, geographies, and group-based attributes in the focus of the reviewed research. We find a significant skew of research focus towards few online platforms, Western contexts, particularly the US, and English language data. Additionally, our analysis indicates a tendency to focus on a narrow set of group-based attributes, often operationalized in simplified ways, which might obscure more nuanced aspects of algorithmic bias and discrimination. We provide a clearer understanding of the current state of the online platform-focused algorithm auditing and identify gaps to be addressed for a more inclusive and representative research landscape.
Memory, Mind & Media, 2025
Advances in generative artificial intelligence (AI) have driven a growing effort to create digita... more Advances in generative artificial intelligence (AI) have driven a growing effort to create digital duplicates. These semi-autonomous recreations of living and dead people can be used for many purposes. Some of these purposes include tutoring, coping with grief, and attending business meetings. However, the normative implications of digital duplicates remain obscure, particularly considering the possibility of them being applied to genocide memory and education. To address this gap, we examine normative possibilities and risks associated with the use of more advanced forms of generative AI-enhanced duplicates for transmitting Holocaust survivor testimonies. We first review the historical and contemporary uses of survivor testimonies. Then, we scrutinize the possible benefits of using digital duplicates in this context and apply the Minimally Viable Permissibility Principle (MVPP). The MVPP is an analytical framework for evaluating the risks of digital duplicates. It includes five core components: the need for authentic presence, consent, positive value, transparency, and harm-risk mitigation. Using MVPP, we identify potential harms digital duplicates might pose to different actors, including survivors, users, and developers. We also propose technical and sociotechnical mitigation strategies to address these harms.
Memory, Mind & Media, 2024
The rise of digital technology has led to fundamental changes in how individual and collective pe... more The rise of digital technology has led to fundamental changes in how individual and collective perspectives on the past are transmitted and engaged. An immediate implication of these changes relates to the shift away from human communication as a single form of communication about memory towards multiple models which involve non-human (or robotic) agents. These nonhuman agents are primarily constituted by artificial intelligence (AI)-driven systems, such as search engines and conversational agents, which retrieve information about the past for human users and are increasingly used to generate memory-related content. To account for the growing complexity of memory-related digital communication, the article introduces three agency-based models of such communication: (1) human-to-human; (2) human-to-robot; and (3) robot-to-robot. It discusses examples of communication practices enabled by these models and scrutinises their implications for individual and collective memory transmission. The article concludes by outlining several directions for memory communication research increasingly shaped by non-human agents.
Arxiv, 2025
Search engines like Google have become major sources of information for voters during election ca... more Search engines like Google have become major sources of information for voters during election campaigns. To assess potential biases across candidates' gender and partisan identities in the algorithmic curation of candidate information, we conducted a large-scale algorithm audit analyzing Google's selection and ranking of information about candidates for the 2023 Swiss Federal Elections, three and one week before the election day. Results indicate that text searches prioritize media sources in search output but less so for women politicians. Image searches revealed a tendency to reinforce stereotypes about women candidates, marked by a disproportionate focus on stereotypically pleasant emotions for women, particularly among right-leaning candidates. Crucially, we find that patterns of candidates' representation in Google text and image searches are predictive of their electoral performance.
Memory Studies Review, 2024
In this article, we critically examine the history of artificial intelligence (ai) to explore how... more In this article, we critically examine the history of artificial intelligence (ai) to explore how it can shape the future of collective memory. By situating our work within critical debates that challenge the dominant anthropomorphising discourse of ai, we scrutinise how ai specificities shape its interactions with information about the past. We highlight how the development of ai has been often misremembered in public discourse, and by extension in the humanities, and explore the consequences for ai's emerging status as a form of media memory. Based on our exploration, we outline three scenarios for the future of ai-shaped collective memory: 1) the reiteration of the simulative paradigm of ai media memory; 2) the enfolding of ai as an alien actant in human (memory) collectives; and 3) the recognition of the radical alterity of ai for human-ai memory symbiosis.
Personality and Individual Differences, 2024
Research has explored the links between personality and political news consumption, resulting in ... more Research has explored the links between personality and political news consumption, resulting in mixed results that vary across platforms. One potential reason for these inconclusive patterns might be that previous work has exclusively relied on self-reported measures of political news consumption. Considering that personality has been linked to biased response behavior in the past, we investigate to what extent the relationship is affected by potential measurement errors associated with different capturing methods. To do so, we introduce an innovative measurement technique: logs capturing actual internet use through webtracking. While we do not find strong evidence that personality is systematically related to over- or underestimating one's political news consumption, the comparison between the behavioral webtracking measure and self-reported news consumption nevertheless reveals significant differences: notably, openness is positively associated with self-reported online news consumption, but this relationship does not hold in the webtracking data. Instead, when using behavioral measures, neuroticism is a better predictor of political news consumption – an association not observed in the self-reported data. Our insights refine our understanding of the interplay between personality and online political news consumption and enhance the broader discourse on survey response behaviors linked to personality.
Georgetown Journal of International Affairs, 2024
The rise of digital platforms transforms contemporary warfare by enabling new possibilities for m... more The rise of digital platforms transforms contemporary warfare by enabling new possibilities for monitoring war destruction, identifying human rights violations, and commemorating individual and collective suffering. However, to achieve these aims, it is important to ensure that war-related platform content is archived and preserved. Using Russia’s war in Ukraine as a case study, the article discusses challenges associated with the use of digital archiving for documenting and remembering modern wars and proposes a set of recommendations for preventing the disappearance of digital evidence of mass violence.
arXiV, 2024
Search engines like Google have become major information gatekeepers that use artificial intellig... more Search engines like Google have become major information gatekeepers that use artificial intelligence (AI) to determine who and what voters find when searching for political information. This article proposes and tests a framework of algorithmic representation of minoritized groups in a series of four studies. First, two algorithm audits of political image searches delineate how search engines reflect and uphold structural inequalities by under-and misrepresenting women and non-white politicians. Second, two online experiments show that these biases in algorithmic representation in turn distort perceptions of the political reality and actively reinforce a white and masculinized view of politics. Together, the results have substantive implications for the scientific understanding of how AI technology amplifies biases in political perceptions and decision-making. The article contributes to ongoing public debates and cross-disciplinary research on algorithmic fairness and injustice.
Proceedings of the ACM on Human-Computer Interaction, 2024
Internet users highly rely on and trust web search engines, such as Google, to find relevant info... more Internet users highly rely on and trust web search engines, such as Google, to find relevant information online. However, scholars have documented numerous biases and inaccuracies in search outputs. To improve the quality of search results, search engines employ various content moderation practices such as interface elements informing users about potentially dangerous websites and algorithmic mechanisms for downgrading or removing low-quality search results. While the reliance of the public on web search engines and their use of moderation practices is well-established, user attitudes towards these practices have not yet been explored in detail. To address this gap, we first conducted an overview of content moderation practices used by search engines, and then surveyed a representative sample of the US adult population (N=398) to examine the levels of support for different moderation practices applied to potentially misleading and/or potentially offensive content in web search. We also analyzed the relationship between user characteristics and their support for specific moderation practices. We find that the most supported practice is informing users about potentially misleading or offensive content, and the least supported one is the complete removal of search results. More conservative users and users with lower levels of trust in web search results are more likely to be against content moderation in web search.
Media, Culture & Society, 2024
After Russia's war against Ukraine destroyed people's ability to move and communicate freely in U... more After Russia's war against Ukraine destroyed people's ability to move and communicate freely in Ukraine, many Ukrainians turned to social media and messenger apps, especially Telegram, to produce and share information. The vast amount of this digital data is privatized, ephemeral, and difficult to utilize for research, raising urgent questions about its sustainable accessibility and usability. In this article, we explore a specific aspect of digital archive sustainability-the use of digital archives to preserve platform data related to Russia's war against Ukraine-by focusing on data integrity, usability, and ethics. Our research is based on a case study of an interdisciplinary Data Sprint, "Russia's War in Ukraine," organized in collaboration with a Telegram Archive, in which academics and practitioners investigated qualitative approaches to studying a war on Telegram. In the article, we explore the possibilities and drawbacks of sustainable use of the Telegram Archive for qualitative approaches-semantic, visual, spatial, and link analysis-to working with large amounts of data. We argue that the sustainability of digital archives depends not only on their use, based on consistently stored and accessible data, but also the ethical aspects of their use for diverse research needs.
Remembering Transitions: Local Revisions and Global Crossings in Culture and Media, 2023
The first post-Soviet decade occupies an important place in the Russian collective memory. Associ... more The first post-Soviet decade occupies an important place in the Russian collective memory. Associated with the transition to democracy, but also economic hardships and violence, it constitutes a complex amalgamation of traumatic and nostalgic recollections. The ambiguous role of the 1990s memories is further complicated by their intense instrumentalization by the Kremlin for consolidating the public support as well as their counter-instrumentalization by the civil society for criticizing the revival of authoritarian tendencies in Russia. Under these circumstances, it is important to understand how the remediation of narratives about the first post-Soviet decade is influenced by social media platforms capable of both countering and reinforcing hegemonic discourses about the past. With this aim, the chapter examines how trauma and nostalgia associated with the 1990s are remediated via Instagram. Using a sample of Instagram data, it examines whether memory remediation on the platform reflects the above-mentioned intense politicization of nostalgia and trauma associated with this period and how this remediation is affected by the consumption-oriented nature of Instagram. The chapter's findings demonstrate that Instagram is primarily used for showcasing cultural products associated with the 1990s and expressing a yearning towards childhood and teenage years that coincided with the post-Soviet transition. Despite the absence of explicit political statements, however, nostalgic content on Instagram can still be seen as a form of challenging the hegemonic narrative of the 1990s as a time of misery and hardships.
Ethics in artificial intelligence: Bias, fairness and beyond, 2023
The growing application of artificial intelligence (AI) in the field of information retrieval (IR... more The growing application of artificial intelligence (AI) in the field of information retrieval (IR) affects different domains, including cultural heritage. By facilitating organisation and retrieval of large volumes of heritage-related content, AI-driven IR systems inform users about a broad range of historical phenomena, including genocides (e.g. the Holocaust). However, it is currently unclear to what degree IR systems are capable of dealing with multiple ethical challenges associated with the curation of genocide-related information. To address this question, this chapter provides an overview of ethical challenges associated with the human curation of genocide-related information using a three-part framework inspired by Belmont criteria (i.e. curation challenges associated with respect for individuals, beneficence and justice/fairness). Then, the chapter discusses to what degree the above-mentioned challenges are applicable to the ways in which AI-driven IR systems deal with genocide-related information and what can be the potential ways of bridging AI and memory ethics in this context.
De-Commemoration: Removing Statues and Renaming Places, 2023
The push to bring down monuments tied to colonialism and slavery in the summer of 2020 highlights... more The push to bring down monuments tied to colonialism and slavery in the summer of 2020 highlights the complex interplay between memory and power relations in the public space. While far from being the first instance of radical reassessment of the role of troubled memories in the public space, the massive scale of this process and its extensive media coverage resulted in an unprecedented transnational debate about the interpretations of the past and the monuments that reinforce these interpretations. However, this debate has mostly remained within the conceptual binary of removing versus maintaining certain monuments. Neither the question of what (if anything) should replace the empty pedestals nor alternative solutions have as yet been discussed extensively.
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Papers by Mykola Makhortykh