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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.

Search engines play a gatekeeper role in current high-choice information environments. Considered a form of new media, users are still more likely to find and trust news found through search than social media sites. Indeed, search engines are one of the most utilised technologies to find political information, despite audits uncovering biases in their results, for example, towards national outlets over local ones. It is therefore important to keep in mind the potential of search results to affect public opinion. With this study, we investigate how Google search news headlines and snippets differ when varying migrant search terms (e.g., immigrant, refugee, expat). We employ computational text analysis methods as well as qualitative content analysis. Specifically, we employ an automated framework for detecting media frames, originally trained on Twitter data, and attempt to transfer it to news data; this framework allows for a categorization of data to frames of a generic-issue (economy, safety, health) and specific (hero:diversity, threat:jobs) nature. We evaluate its applicability for this novel data source and find that it performs well for frames related economy and security. Our next steps include analysing the results of other computational measures, namely, sentiment, agency and political outlet of the news item. We expect that sentiment and agency will complement the initial results we see based on media frames.

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 paper, we conduct a systematic algorithm audit to examine how one specific form of misrepresentation bias, namely, sexualization, is manifested in Google's text search results about different national and gender groups. We find evidence of sexualization of women, particularly those from the Global South and East in search outputs. This is amplified by contextual advertisements pushed by Google in response to different search queries.

On 24 February 2022, Russia launched a large-scale invasion of Ukraine which since then has been consistently referred to by the Russian authorities as a special operation and not war. The purpose of this specific framing of the Russian aggression can be attributed to multiple reasons, but among the main advantages it provides to the Kremlin is the emphasis of power inequality between Russia and Ukraine as well as minimizing the concerns of the Russian population about the impact of the war on their lives. However, despite all the Kremlin’s propaganda and censorship efforts, it is still unclear what the dominant framing of the war is among regular Russian internet users and how they engage with different frames used in relation to it. To address this gap, we conducted an automated analysis of over 6 million public posts from VK, the biggest Russian social media platform, published between 14 February 2022 and 24 June 2022 and related to different ways of framing the war as well as the ways users engage with these frames. Our analysis reveals that the invasion was predominantly discussed in connection with the losses in the Russian army, and allusions to WW2 were also common. The users who posted about the war were older than average VK users and tuned in to pro-regime and pro-war content more frequently.

The present paper contributes to the research on the activities of far-right actors on social media by examining the interconnections between far-right actors and groups on Telegram platform using ...

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.

With the increasing importance of online information environments, researchers have started investigating direct measures of online media use, such as online tracking. Most existing studies using tracking data have so far relied on commercial solutions, but these have limitations in terms of their costliness, replicability, and applicability to certain research questions. Hence, different research groups are developing their own tracking solutions for academic purposes. In this paper, we provide a critical review and classification of the existing approaches, apt to guide research decisions on the appropriate tracking approach and tool. First, we develop criteria to distinguish different user-centric desktop and mobile tracking approaches and tools (types of information, technical complexity, privacy implementation, user experience, and availability). Second, we describe different tools and approaches – separately for desktop and mobile tracking – with concrete examples and evaluate them using the aforementioned criteria. Finally, we discuss how different mobile and desktop tracking solutions can complement each other and provide recommendations for future research.

We examine the patterns of medical preprint sharing on Twitter during the early stages of the COVID-19 pandemic. Our analysis demonstrates a stark increase in attention to medical preprints among the general public since the beginning of the pandemic. We also observe a political divide in medical preprint sharing patterns - a finding in line with previous observations regarding the politicisation of COVID-19-related discussions. In addition, we find that the increase in attention to preprints from the members of the general public coincided with the change in the social media-based discourse around preprints.

On 3 September 2021, the Russian court forbade Google and Yandex to display search results for “Smart Voting,” the query referring to a tactical voting project by the jailed Russian opposition leader Alexei Navalny. To examine whether the two search engines complied with the court order, we collected top search outputs for the query from Google and Yandex. Our analysis demonstrates the lack of compliance from both engines; however, while Google continued prioritizing outputs related to the opposition’s web resources, Yandex removed links to them and, in some cases, promoted conspiratorial claims aligning with the Russian authorities’ anti-Western narrative.

Web search engines influence perception of social reality by filtering and ranking information. However, their outputs are often subjected to bias that can lead to skewed representation of subjects such as professional occupations or gender. In our paper, we use a mixed-method approach to investigate presence of race and gender bias in representation of artificial intelligence (AI) in image search results coming from six different search engines. Our findings show that search engines prioritize anthropomorphic images of AI that portray it as white, whereas non-white images of AI are present only in non-Western search engines. By contrast, gender representation of AI is more diverse and less skewed towards a specific gender that can be attributed to higher awareness about gender bias in search outputs. Our observations indicate both the the need and the possibility for addressing bias in representation of societally relevant subjects, such as technological innovation, and emphasize the importance of designing new approaches for detecting bias in information retrieval systems., Comment: 16 pages, 3 figures

BACKGROUND Since the beginning of the COVID-19 pandemic, scientists have been willing to share their results quickly to speed up the development of potential treatments and/or a vaccine. At the same time, traditional peer-review-based publication systems are not always able to process new research promptly. This has contributed to a surge in the number of medical preprints published since January 2020. In the absence of a vaccine, preventative measures such as social distancing are most helpful in slowing the spread of COVID-19. Their effectiveness can be undermined if the public does not comply with them. Hence, public discourse can have a direct effect on the progression of the pandemic. Research shows that social media discussions on COVID-19 are driven mainly by the findings from preprints, not peer-reviewed papers, highlighting the need to examine the ways medical preprints are shared and discussed online. OBJECTIVE We examine the patterns of medRxiv preprint sharing on Twitter to establish (1) whether the number of tweets linking to medRxiv increased with the advent of the COVID-19 pandemic; (2) which medical preprints were mentioned on Twitter most often; (3) whether medRxiv sharing patterns on Twitter exhibit political partisanship; (4) whether the discourse surrounding medical preprints among Twitter users has changed throughout the pandemic. METHODS The analysis is based on tweets (n=557,405) containing links to medRxriv preprint repository that were posted between the creation of the repository in June 2019 and June 2020. The study relies on a combination of statistical techniques and text analysis methods. RESULTS Since January 2020, the number of tweets linking to medRxiv has increased drastically, peaking in April 2020 with a subsequent cool-down. Before the pandemic, preprints were shared predominantly by users we identify as medical professionals and scientists. After January 2020, other users, including politically-engaged ones, have started increasingly tweeting about medRxiv. Our findings indicate a political divide in sharing patterns of the top-10 most-tweeted preprints. All of them were shared more frequently by users who describe themselves as Republicans than by users who describe themselves as Democrats. Finally, we observe a change in the discourse around medRxiv preprints. Pre-pandemic tweets linking to them were predominantly using the word “preprint”. In February 2020 “preprint” was taken over by the word “study”. Our analysis suggests this change is at least partially driven by politically-engaged users. Widely shared medical preprints can have a direct effect on the public discourse around COVID-19, which in turn can affect the societies’ willingness to comply with preventative measures. This calls for an increased responsibility when dealing with medical preprints from all parties involved: scientists, preprint repositories, media, politicians, and social media companies. CONCLUSIONS Widely shared medical preprints can have a direct effect on the public discourse around COVID-19, which in turn can affect the societies’ willingness to comply with preventative measures. This calls for an increased responsibility when dealing with medical preprints from all parties involved: scientists, preprint repositories, media, politicians, and social media companies.