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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. [ABSTRACT FROM AUTHOR]

The 2020 US elections news coverage was extensive, with new pieces of information generated rapidly. This evolving scenario presented an opportunity to study the performance of search engines in a context in which they had to quickly process information as it was published. We analyze novelty, a measurement of new items that emerge in the top news search results, to compare the coverage and visibility of different topics. Using virtual agents that simulate human web browsing behavior to collect search engine result pages, we conduct a longitudinal study of news results of five search engines collected in short bursts (every 21 minutes) from two regions (Oregon, US and Frankfurt, Germany), starting on election day and lasting until one day after the announcement of Biden as the winner. We find more new items emerging for election related queries ("joe biden," "donald trump," and "us elections") compared to topical (e.g., "coronavirus") or stable (e.g., "holocaust") queries. We demonstrate that our method captures sudden changes in highly covered news topics as well as multiple differences across search engines and regions over time. We highlight novelty imbalances between candidate queries which affect their visibility during electoral periods, and conclude that, when it comes to news, search engines are responsible for such imbalances, either due to their algorithms or the set of news sources that they rely on. [ABSTRACT FROM AUTHOR]

Social media platforms play a major role in shaping how the public around the world perceives contemporary wars, including the ongoing Russian invasion of Ukraine. However, there are multiple challenges in studying how exactly these platforms represent violence and what aspects of it are made more salient by their users. One of these challenges concerns the broad range of qualitative and quantitative approaches used to study platform-based war framing and their different capabilities in tackling the large volume of available data. To address this challenge, the authors compare the performance of qualitative and quantitative approaches – i.e. qualitative content analysis and topic modelling – for studying how one of the key episodes of the Russian–Ukrainian war, the siege of Mariupol in 2022 was framed on Twitter over time. Their findings demonstrate that both approaches show the prevalence of human interest and conflict frames that aligns with earlier research on war framing in journalistic media. At the same time, they observe differences in the estimated visibility of less common frames, such as morality and responsibility frames, depending on what method is used. [ABSTRACT FROM AUTHOR]

Implicit and explicit gender biases in media representations of individuals have long existed. Women are less likely to be represented in gender-neutral media content (representation bias), and their face-to-body ratio in images is often lower (face-ism bias). In this article, we look at representativeness and face-ism in search engine image results. We systematically queried four search engines (Google, Bing, Baidu, Yandex) from three locations, using two browsers and in two waves, with gender-neutral (person, intelligent person) and gendered (woman, intelligent woman, man, intelligent man) terminology, accessing the top 100 image results. We employed automatic identification for the individual's gender expression (female/male) and the calculation of the face-to-body ratio of individuals depicted. We find that, as in other forms of media, search engine images perpetuate biases to the detriment of women, confirming the existence of the representation and face-ism biases. In-depth algorithmic debiasing with a specific focus on gender bias is overdue. [ABSTRACT FROM AUTHOR]

Search engines serve as information gatekeepers on a multitude of topics dealing with different aspects of society. However, the ways search engines filter and rank information are prone to biases related to gender, ethnicity, and race. In this article, we conduct a systematic algorithm audit to examine how one specific form of bias, namely, sexualization, is manifested in Google's text search results about different national and gender groups. We find evidence of the sexualization of women, particularly those from the Global South and East, in search outputs in both organic and sponsored search results. Our findings contribute to research on the sexualization of people in different forms of media, bias in web search, and algorithm auditing as well as have important implications for the ongoing debates about the responsibility of transnational tech companies for preventing systems they design from amplifying discrimination. [ABSTRACT FROM AUTHOR]

Algorithm audits have increased in recent years due to a growing need to independently assess the performance of automatically curated services that process, filter and rank the large and dynamic amount of information available on the Internet. Among several methodologies to perform such audits, virtual agents stand out because they offer the ability to perform systematic experiments, simulating human behaviour without the associated costs of recruiting participants. Motivated by the importance of research transparency and replicability of results, this article focuses on the challenges of such an approach. It provides methodological details, recommendations, lessons learned and limitations based on our experience of setting up experiments for eight search engines (including main, news, image and video sections) with hundreds of virtual agents placed in different regions. We demonstrate the successful performance of our research infrastructure across multiple data collections, with diverse experimental designs, and point to different changes and strategies that improve the quality of the method. We conclude that virtual agents are a promising venue for monitoring the performance of algorithms across long periods of time, and we hope that this article can serve as a basis for further research in this area. [ABSTRACT FROM AUTHOR]

While there is growing academic attention to readers of hyperpartisan, alternative, and conspiracy (HAC) media, our understanding of these sites has developed in separate bodies of work. We make a case for studying HAC media in unison, recognizing them as different information sources that share the same underlying anti-establishment sentiment. We do so by painting a detailed portrait of HAC media users, detailing 1) who consumes HAC media; 2) how they access it; and 3) how its consumption relates to public opinion. This is made possible by the unique combination of panel surveys taken before and after the first COVID-19 lockdowns in Germany and Switzerland, and webtracking data capturing participants’ actual online behavior. Our results show that those exposed to HAC media have a strong distrust of government and place themselves at the ideological extremes. While social media was a quintessential entry point for such media, most visits were registered by a small percentage of repeat visitors. Lastly, we show that those who consumed HAC media developed distinct opinions about the threat posed by COVID-19, mirroring the sentiments expressed in HAC media that the danger of the virus was exaggerated and that the real threat was to individual freedoms. With this case study, we showcase the theoretical utility of taking an integrated approach to HAC media, while providing nuanced insights into their audience. [ABSTRACT FROM AUTHOR]

This article examines how digital media interact with collective memories and teaching practices by exploring a selection of Wikipedia articles that describe the capture of Lviv by the Germans on 30 June 1941. This event constitutes an important episode in the history of Ukraine and a complex case of violence that produced several controversies concerning the national historiographies of the Second World War in the post-Soviet region. Using a combination of qualitative and quantitative metrics, this article investigates how the event is represented in different language versions of Wikipedia and assesses what kind of memory is produced by each of them.

This paper offers a critical look at the promises and drawbacks of a popular, novel data collection technique—online tracking—from the point of view of sample composition. Using data from two large-scale studies about political attitudes and information consumption behavior carried out in Germany and Switzerland, we find that the likelihood of participation in a tracking study at several critical dropout points is systematically related to the gender, age, and education of participants, with men, young, and more educated participants being less likely to dropout of the studies. Our findings also show that these patterns are incremental, as changes in sample composition accumulate over successive study stages. Political interest and ideology were also significantly related to the likelihood of participation in tracking research. The study explores some of the most common concerns associated with tracking research leading to non-participation, finding that they also differ across demographic groups. The implications of these findings are discussed. [ABSTRACT FROM AUTHOR]

The rise of digital technologies has caused a major shift in memory studies. The unprecedented possibilities for storing and retrieving information enabled by platforms not only expand capacities for preserving memory-related content for individuals and collectives but also challenge existing memory power structures. An integral constituent of the scholarly assessment of these transformations is the increased focus on the memory actors' agency and connectivity. Despite the importance of such a user-centric focus, the article argues that it can be limiting for the field of (digital) memory studies conceptually and methodologically. Under the condition when platforms and their algorithms turn into (hegemonic) memory actors themselves and determine what data memory scholars and the general public can (not) access, there is a pressing need for critically revisiting the key assumptions about memory in the digital age. To address this need, the article discusses the fundamental premises of a more infrastructure-centric approach to memory studies together with the conceptual and methodological implications of its adoption for studying individual and collective remembrance. [ABSTRACT FROM AUTHOR]

This study explores shifts in political trust during the outbreak of the COVID-19 pandemic in Switzerland, examining the role that media consumption and threat perceptions played in individuals' trust in politics. We combine panel surveys taken before and during the first nation-wide lockdown with webtracking data of participants' online behaviour to paint a nuanced picture of media effects during the crisis. Our work has several findings. First, political trust, an attitude known for its stability, increased following lockdown. Second, consumption of mainstream news on COVID-19 directly hindered this increase, with those reading more news having lower over-time trust, while the relatively minor alternative news consumption had no direct effect on political trust. Third, threat perceptions a) to health and b) from the policy response to the pandemic, have strong and opposite effects on political trust, with threats to health increasing trust, and threats from the government policy response decreasing it. Lastly, these threat perceptions condition the effect of COVID-19 news consumption on political trust: perceptions of threat had the power to both exacerbate and mute the effect of media consumption on government trust during the pandemic. Notably, we show that the expected negative effect of alternative news on political trust only exists for those who did not think COVID-19 posed a threat to their health, while public service news consumption reduced the negative effect produced by government threat perceptions. The paper therefore advances our understanding of the nuanced nature of media effects, particularly as relates to alternative media, especially during moments of crisis. [ABSTRACT FROM AUTHOR]

The memorialization of mass atrocities such as war crimes and genocides facilitates the remembrance of past suffering, honors those who resisted the perpetrators, and helps prevent the distortion of historical facts. Digital technologies have transformed memorialization practices by enabling less top-down and more creative approaches to remember mass atrocities. At the same time, they may also facilitate the spread of denialism and distortion, attempt to justify past crimes and attack the dignity of victims. The emergence of generative forms of artificial intelligence (AI), which produce textual and visual content, has the potential to revolutionize the field of memorialization even further. AI can identify patterns in training data to create new narratives for representing and interpreting mass atrocities—and do so in a fraction of the time it takes for humans. The use of generative AI in this context raises numerous questions: For example, can the paucity of training data on mass atrocities distort how AI interprets some atrocity-related inquiries? How important is the ability to differentiate between human- and AI-made content concerning mass atrocities? Can AI-made content be used to promote false information concerning atrocities? This article addresses these and other questions by examining the opportunities and risks associated with using generative AIs for memorializing mass atrocities. It also discusses recommendations for AIs integration in memorialization practices to steer the use of these technologies toward a more ethical and sustainable direction. [ABSTRACT FROM AUTHOR]

We analyze short-term media trust changes during the COVID-19 pandemic, their ideological drivers and consequences based on panel data in German-speaking Switzerland. We thereby differentiate trust in political information from different types of traditional and non-traditional media. COVID-19 serves as a natural experiment, in which citizens' media trust at the outbreak of the crisis is compared with the same variables after the severe lockdown measures were lifted. Our data reveal that (1) media trust is consequential as it is associated with people's willingness to follow Covid-19 regulations; (2) media trust changes during the pandemic, with trust levels for most media decreasing, with the exception of public service broadcasting; (3) trust losses are hardly connected to ideological divides in Switzerland. Our findings highlight that public service broadcasting plays an exceptional role in the fight against a pandemic and that contrary to the US, no partisan trust divide occurs. [ABSTRACT FROM AUTHOR]

Previous research highlighted how algorithms on social media platforms can be abused to disseminate disinformation. However, less work has been devoted to understanding the interplay between Facebook news curation mechanisms and propaganda content. To address this gap, we analyze the activities of RT (formerly, Russia Today) on Facebook during the 2020 U.S. presidential election. We use agent-based algorithmic auditing and frame analysis to examine what content RT published on Facebook and how it was algorithmically curated in Facebook News Feeds and Search Results. We find that RT's strategic framing included the promotion of anti-Biden leaning content, with an emphasis on antiestablishment narratives. However, due to algorithmic factors on Facebook, individual agents were exposed to eclectic RT content without an overarching narrative. Our findings contribute to the debate on computational propaganda by highlighting the ambiguous relationship between government-sponsored media and Facebook algorithmic curation, which may decrease the exposure of users to propaganda and at the same time increase confusion. [ABSTRACT FROM AUTHOR]

Search engines, such as Google or Yandex, shape social reality by informing their users about current and historical phenomena. However, there is little research on how search engines deal with contested memories, which are subjected to ontological conflicts known as memory wars. In this article, we investigate how search engines circulate information about memory wars related to the Holodomor, a mass famine caused by Soviet repressive politics in Ukraine in 1932–1933. For this aim, we conduct an agent-based audit of four search engines—Bing, DuckDuckGo, Google, and Yandex—and examine how their top search results represent the Holodomor and related memory wars. Our findings demonstrate that search engines prioritize interpretations of the Holodomor aligning with specific sides in the memory wars, thus becoming memory warriors themselves. [ABSTRACT FROM AUTHOR]

We examine how six search engines filter and rank information in relation to the queries on the U.S. 2020 presidential primary elections under the default—that is nonpersonalized—conditions. For that, we utilize an algorithmic auditing methodology that uses virtual agents to conduct large-scale analysis of algorithmic information curation in a controlled environment. Specifically, we look at the text search results for "us elections," "donald trump," "joe biden," "bernie sanders" queries on Google, Baidu, Bing, DuckDuckGo, Yahoo, and Yandex, during the 2020 primaries. Our findings indicate substantial differences in the search results between search engines and multiple discrepancies within the results generated for different agents using the same search engine. It highlights that whether users see certain information is decided by chance due to the inherent randomization of search results. We also find that some search engines prioritize different categories of information sources with respect to specific candidates. These observations demonstrate that algorithmic curation of political information can create information inequalities between the search engine users even under nonpersonalized conditions. Such inequalities are particularly troubling considering that search results are highly trusted by the public and can shift the opinions of undecided voters as demonstrated by previous research. [ABSTRACT FROM AUTHOR]

The rise of user-generated content (UGC), such as internet memes and amateur videos, enables new possibilities for mediatization of the past. However, these possibilities can facilitate not only more diverse and less top-down engagements with memory, but also lead to its trivialization and distortion of historical facts. The latter concerns are particularly pronounced in the case of memories about mass atrocities (e.g. the Holocaust), where online media are often used to promote denialism and attack the victims’ dignity. To better understand the relationship between UGC and memory mediatization, we examine a selection of internet memes dealing with Anne Frank, an iconic Holocaust victim. Using a combination of inductive content analysis and close reading, we identify four classes of Anne Frank memes: (1) ad hominems; (2) deniers; (3) trivializers; and (4) thought provokers. Our findings demonstrate the multi-faceted functionality of memes, which are used not only to trivialize Holocaust memory, but also to reinforce canonical narratives about Anne Frank, and highlight the dependency of memes on other forms of memory mediatization, thus raising questions about the interrelations between UGC and institutionalized forms of remembrance. [ABSTRACT FROM AUTHOR]

The growth of online platforms is accompanied by the increasing use of automated agents. Despite being discussed primarily in the context of opinion manipulation, agents play diverse roles within platform ecosystems that raises the need for governance approaches that go beyond policing agents' unwanted behaviour. To provide a more nuanced assessment of agent governance, we introduce an analytical framework that distinguishes between different aspects and forms of governance. We then apply it to explore how agents are governed across nine platforms. Our observations show that despite acknowledging diverse roles of agents, platforms tend to focus on governing selected forms of their misuse. We also observe differences in governance approaches used by platforms, in particular when it comes to the agent rights/obligations and transparency of policing mechanisms. These observations highlight the necessity of advancing the algorithmic governance research agenda and developing a generalizable normative framework for agent governance. [ABSTRACT FROM AUTHOR]

Datafication and the use of algorithmic systems increasingly blur distinctions between policy fields. In the financial sector, for example, algorithms are used in credit scoring, money has become transactional data sought after by large data-driven companies, while financial technologies (FinTech) are emerging as a locus of information warfare. To grasp the context specificity of algorithmic governance and the assumptions on which its evaluation within different domains is based, we comparatively study the sociotechnical imaginaries of algorithmic governance in European Union (EU) policy on online disinformation and FinTech. We find that sociotechnical imaginaries prevalent in EU policy documents on disinformation and FinTech are highly divergent. While the first can be characterized as an algorithm-facilitated attempt to return to the presupposed status quo (absence of manipulation) without a defined future imaginary, the latter places technological innovation at the centre of realizing a globally competitive Digital Single Market. [ABSTRACT FROM AUTHOR]

The use of algorithmically tailored individual news feeds is increasingly viewed as an important strategy for accommodating consumers' information needs by legacy media. However, growing personalization of news distribution also raises normative concerns about the societal function of legacy media, in particular when dealing with personalization of traumatic and polarizing content. To extend the discussion of these concerns beyond the current focus on the role of news personalization in Western democracies, this article offers a conceptual assessment of perspectives for adopting personalization for conflict coverage in Ukraine and Russia, where media systems enjoy a lesser degree of press freedom. Using the coverage of the conflict in Eastern Ukraine as a case study, the article offers a conceptual framework for assessing the impact of personalization on the distribution of conflict-related news in a non-Western context. [ABSTRACT FROM AUTHOR]

This article discusses how popular culture products – digital greeting cards – interact with hegemonic historical narratives in the context of war remembrance. It employs the Foucauldian concept of counter-memory to analyse how user-generated mnemonic content interacts with historical power relations. Using content analysis to examine a sample of amateur greeting cards, the authors investigate how these cultural products engage with official and counter-official memory practices in Russia related to the Soviet victory in the Second World War. Specifically, the article explores how different visual elements are employed to (de)construct specific narratives about the Soviet victory and it discusses how the use of computer graphics, in particular animation, influences the potential role of greeting cards as a means of resurrecting the subjugated past. [ABSTRACT FROM AUTHOR]

The article contributes both conceptually and methodologically to the study of online news consumption by introducing new approaches to measuring user information behaviour and proposing a typology of users based on their click behaviour. Using as a case study two online outlets of large national newspapers, it employs computational approaches to detect patterns in time- and content-based user interactions with news content based on clickstream data. The analysis of interactions detects several distinct timelines of news consumption and scrutinises how users switch between news topics during reading sessions. Using clustering analysis, the article then identifies several types of news readers (e.g. samplers, gourmets) and examines their news diets. The results point out the limited variation in topical composition of the news diets between different types of readers and the tendency of these diets to align with the news supply patterns (i.e. the average distribution of topics covered by the outlet). [ABSTRACT FROM AUTHOR]

The paper examines ideological segregation among Ukrainian users in online environments, using as a case study partisan news communities on Vkontakte, the largest online platform in post-communist states. Its findings suggest that despite their insignificant numbers, partisan news communities attract substantial attention from Ukrainian users and can encourage the formation of isolated ideological cliques – or 'echo chambers' – that increase societal polarisation. The paper also investigates factors that predict users' interest in partisan content and establishes that the region of residence is the key predictor of selective consumption of pro-Ukrainian or pro-Russian partisan news content. [ABSTRACT FROM AUTHOR]

In our article we examine changes experienced by media and memory systems in Russia since the beginning of the Ukraine crisis. Using as an example a popular Russian blogging platform, LiveJournal, we scrutinize how the digital practices related to commemoration of the 70th anniversary of the Soviet victory over Nazi Germany are influenced by the growing instrumentalization of Second World War memory for media propaganda and manipulation. Using topic modeling to analyze a large set of data on Russian users' interactions with the platform, we examine how hegemonic and alternative interpretations of the Second World War interact on LiveJournal and how their interactions are influenced by the growing antagonism between Russia and the West. Our findings suggest that LiveJournal constitutes a fractured memory system, which is characterized by uneven representation of Second World War experiences and the growing influence of pro-government actors promoting hegemonic war narratives. However, our observations also show that instrumentalization of the past in the context of the Ukraine crisis does not necessarily interfere with digital practices of Second World War commemoration with the latter remaining unaffected by the events in Ukraine. [ABSTRACT FROM AUTHOR]

Chatbots are a burgeoning opportunity for news media outlets to disseminate their content in a conversational way, and create an engaging experience around it. Since chatbots are social and interactive technologies, they might be effective tools to lower the threshold of engaging with news content containing opposing views. In an experiment, we test this idea by investigating whether people are more likely to accept a news article containing conflicting views when it is delivered by a chatbot, as compared with the same article on a news website. The results indicated that people agreed more to a counter-attitudinal news article when it was delivered by a news chatbot (compared with the website article). In addition, users also perceived this chatbot article as more credible. The underlying process for this effect was that people attributed human-like characteristics to the chatbot on an implicit level (i.e., perceived mindless anthropomorphism). These results are discussed in the light of their potential contribution to an informed public discourse and a decrease in polarization in our society. [ABSTRACT FROM AUTHOR]

The article discusses interactions between emotions, memory and user-generated digital content in the context of online protest campaigns. Using as a case study anti-government protest in Ukraine (2013–2014) and Venezuela (2019), it compares how pro- and anti-government communities use visuality and memoricity of internet memes to stir affect and promote their political agendas. It shows that despite differences in the use of visual content elements, Ukrainian and Venezuelan memes have similar political functionality. In both countries, pro-government memes usually rely on simple emotional messages for propaganda/polarization purposes, whereas anti-government memes produce more nuanced statements used as a form of creative criticism/coping mechanism. These political functions are often amplified by memoricity, which is used to stigmatize regime's opponents by pro-government communities and to legitimize protesters' demands by anti-government communities. [ABSTRACT FROM AUTHOR]

This article examines how Second World War memory is circulated, reproduced, and challenged in the transnational space of digital media by Ukrainian and Russian Internet users. Using as a case study one episode of the war on the Eastern Front—the capture of the Ukrainian capital, Kyiv, by the Red Army in 1943—it investigates how this event is commemorated through YouTube, which is a popular online platform for uploading, viewing, and commenting on audiovisual materials. This article employs content analysis to assess audiovisual tributes to the Battle of Kyiv from two perspectives: that of representation (how the event is presented on YouTube) and that of interaction (how YouTube users interact with memory of the event). This article concludes that although YouTube is frequently used for the propagation of nationalistic interpretations of the past in Ukraine and Russia, it still has the potential to democratize collective remembrance of the Second World War. [ABSTRACT FROM AUTHOR]

This article examines how digital technology interacts with Holocaust remembrance in post-socialist countries. Using the Lviv pogrom of 1941 as a case study, it explores how Russophone and Ukrainophone web users engage with audiovisual tributes to this event on YouTube. The article scrutinizes user engagement with Holocaust memory on two levels: the level of representation (how the pogrom is represented on YouTube) and the level of interaction (how users interact with tributes to the pogrom). The article suggest that digital media can democratize existing memory practices, but it does not necessarily lead to more pluralist views on the past. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to develop a conceptual framework for assessing what are the possibilities and pitfalls of using algorithmic systems of news personalization – i.e. the tailoring of individualized news feeds based on users' information preferences – for constructive conflict coverage in the context of peace journalism, a journalistic paradigm calling for more diversified and creative war reporting. Design/methodology/approach: The paper provides a critical review of existing research on peace journalism and algorithmic news personalization, and analyzes the intersections between the two concepts. Specifically, it identifies recurring pitfalls of peace journalism based on empirical research on constructive conflict coverage and then introduces a conceptual framework for analyzing to what degree these pitfalls can be mediated – or worsened – through algorithmic system design. Findings: The findings suggest that AI-driven distribution technologies can facilitate constructive war reporting, in particular by countering the effects of journalists' self-censorship and by diversifying conflict coverage. The implementation of these goals, however, depends on multiple system design solutions, thus resonating with current calls for more responsible and value-sensitive algorithmic design in the domain of news media. Additionally, our observations emphasize the importance of developing new algorithmic literacies among journalists both to realize the positive potential of AI for promoting peace and to increase the awareness of possible negative impacts of new systems of content distribution. Originality/value: The article particle is the first to provide a comprehensive conceptualization of the impact of new content distribution techniques on constructive conflict coverage in the context of peace journalism. It also offers a novel conceptual framing for assessing the impact of algorithmic news personalization on reporting traumatic and polarizing events, such as wars and violence. [ABSTRACT FROM AUTHOR]

In this article we explore the use of the #SaveDonbassPeople hashtag in the context of an online protest campaign against the military operation in Eastern Ukraine. The campaign was initiated by anti-government activists, but soon became contested by supporters of the Ukrainian government, turning Twitter into an online battleground. Our findings suggest that in the course of the campaign, Twitter was predominantly used as a propaganda outlet to broadcast opposing views on the ongoing conflict. [ABSTRACT FROM AUTHOR]

This study seeks to understand how populist radical-right (PRR) attitudes and political involvement relate to individuals’ political information consumption and selective exposure to ideological content. The study approaches political information selection as a two-step phenomenon: first, individuals use different amounts of political information, and second, they rely on attitude-consonant information to different degrees. Results from a combination of survey measures, implicit association tests and automated text analysis of large-scale online tracking data collected in Germany and Switzerland in 2020 showed that first, political information consumption was related to political involvement but also to PRR attitudes—in different ways—in both countries. Second, our analyses revealed country variations regarding attitude-consonant online PRR exposure. Third, implicit PRR attitudes were not relevant in explaining the use of PRR content online. We discuss the relevance of moving beyond analyses of traditional news toward the breadth of political information consumption, country contexts, and naturalistic research designs. [ABSTRACT FROM AUTHOR]