News Consumption of Russian Vkontakte Users: Polarization and News Avoidance

This study explores the patterns of news consumption of Russian users of Vkontakte, the most popular social media platform in Russia, based on a sample of 55,344 users. The analysis is conducted via a combination of network analysis techniques. It demonstrates that the majority of Vkontakte users do not subscribe to news sources, demonstrating that there is a politically apathetic majority and news-interested minority. And news subscribers are polarized along political lines. There is a distinct group of users who subscribe to pro-opposition-leaning politicized sources more than other users do. This study builds on research on polarization, selective exposure, and the role of social media in authoritarian regimes. It provides new empirical evidence on the way that selective exposure and polarization manifest themselves on a non-Western platform in an authoritarian state

Political polarisation on social media in different national contexts

The present dissertation examines the phenomenon of political polarisation on social media. Specifically, the dissertation addresses the question of how the intensity of polarisation and the ideological lines along which it occurs might vary between different national contexts. First, it explores the differences in the intensity of political polarisation on Twitter in 16 democratic countries (Article 1). Second, it examines the ideological lines along which polarisation occurs in two non-Western contexts, specifically among Russian (Article 2) and Ukrainian (Article 3) users of Vkontakte – a social media platform popular among users from post-Soviet states. The dissertation demonstrates that the levels of political polarisation differ dramatically between countries. In democracies, polarisation tends to be lowest in multi-party systems with proportional electoral rules (e.g., Sweden), and the highest in pluralist two-party systems (e.g., United States). It also shows that, in non-democratic non- Western contexts, polarisation does not necessarily run along the left–right spectrum or party system lines. In authoritarian regimes or those with less stable party systems, polarisation runs along the lines of other issues that are more politically relevant in a given context. In Russia, polarisation manifests itself along pro-regime vs anti-regimes lines, whereas in Ukraine, polarisation happens around geopolitical issues. Polarisation on social media thus tends to reflect existing political cleavages and their intensity, in line with the theory of political parallelism. The major implication of this dissertation in the context of research into polarisation on social media is that findings on the topic from single-country studies that come from Western democratic contexts should be interpreted with caution, as they are not necessarily generalisable. To make generalisable inferences about the relationship between social media and political polarisation, more comparative studies are needed, as well as studies that take into account platform affordances and the causal mechanisms that might drive polarisation

How transparent are transparency reports? Comparative analysis of transparency reporting across online platforms

Over the last decade, transparency reports have been adopted by most large information technology companies. These reports provide important information on the requests tech companies receive from state actors around the world and the ways they respond to these requests, including what content the companies remove from platforms they own. In theory, such reports shall make inner workings of companies more transparent, in particular with respect to their collaboration with state actors. They shall also allow users and external entities (e.g., researchers or watchdogs) to assess to what extent companies adhere to their own policies on user privacy and content moderation as well as to the principles formulated by global entities that advocate for the freedom of expression and privacy online such as the Global Network Initiative or Santa Clara Principles. However, whether the current state of transparency reports actually is conducive to meaningful transparency remains an open question. In this paper, we aim to address this through a critical comparative analysis of transparency reports using Santa Clara Principles 2.0 (SCP 2.0) as the main analytical framework. Specifically, we aim to make three contributions: first, we conduct a comparative analysis of the types of data disclosed by major tech companies and social media platforms in their transparency reports. The companies and platforms analyzed include Google (incl. YouTube), Microsoft (incl. its subsidiaries Github and LinkedIn), Apple, Meta (prev. Facebook), TikTok, Twitter, Snapchat, Pinterest, Reddit and Amazon (incl. subsidiary Twitch). Second, we evaluate to what degree the released information complies with SCP 2.0 and how it aligns with different purposes of transparency. Finally, we outline recommendations that could improve the level of transparency within the reports and beyond, and contextualize our recommendations with regard to the Digital Services Act (DSA) that received the final approval of the European Council in October 2022

There can be only one truth: Ideological segregation and online news communities in Ukraine

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

"Foreign beauties want to meet you": The sexualization of women in Google's organic and sponsored text search results

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

You are how (and where) you search? Comparative analysis of web search behavior using web tracking data.

In this article, we conduct a comparative analysis of web search behaviors in Switzerland and Germany. For this aim, we rely on a combination of web tracking data and survey data collected over a period of 2 months from users in Germany (n = 558) and Switzerland (n = 563). We find that web search accounts for 13% of all desktop browsing, with the share being higher in Switzerland than in Germany. In over 50% of cases users clicked on the first search result, with over 97% of all clicks being made on the first page of search outputs. Most users rely on Google when conducting searches, with some differences observed in users' preferences for other engines across demographic groups. Further, we observe differences in the temporal patterns of web search use between women and men, marking the necessity of disaggregating data by gender in observational studies regarding online information seeking behaviors. Our findings highlight the contextual differences in web search behavior across countries and demographic groups that should be taken into account when examining search behavior and the potential effects of web search result quality on societies and individuals

This is what a pandemic looks like: Visual framing of COVID-19 on search engines

In today's high-choice media environment, search engines play an integral role in informing individuals and societies about the latest events. The importance of search algorithms is even higher at the time of crisis, when users search for information to understand the causes and the consequences of the current situation and decide on their course of action. In our paper, we conduct a comparative audit of how different search engines prioritize visual information related to COVID-19 and what consequences it has for the representation of the pandemic. Using a virtual agent-based audit approach, we examine image search results for the term "coronavirus" in English, Russian and Chinese on five major search engines: Google, Yandex, Bing, Yahoo, and DuckDuckGo. Specifically, we focus on how image search results relate to generic news frames (e.g., the attribution of responsibility, human interest, and economics) used in relation to COVID-19 and how their visual composition varies between the search engines.Comment: 18 pages, 1 figure, 3 table

Memory, counter-memory and denialism: How search engines circulate information about the Holodomor-related memory wars

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

Auditing the representation of migrants in image web search results

Search engines serve as information gatekeepers on a multitude of topics that are prone to gender, ethnicity, and race misrepresentations. In this paper, we specifically look at the image search representation of migrant population groups that are often subjected to discrimination and biased representation in mainstream media, increasingly so with the rise of right-wing populist actors in the Western countries. Using multiple (n = 200) virtual agents to simulate human browsing behavior in a controlled environment, we collect image search results related to various terms referring to migrants (e.g., expats, immigrants, and refugees, seven queries in English and German used in total) from the six most popular search engines. Then, with the aid of manual coding, we investigate which features are used to represent these groups and whether the representations are subjected to bias. Our findings indicate that search engines reproduce ethnic and gender biases common for mainstream media representations of different subgroups of migrant population. For instance, migrant representations tend to be highly racialized, and female migrants as well as migrants at work tend to be underrepresented in the results. Our findings highlight the need for further algorithmic impact auditing studies in the context of representation of potentially vulnerable groups in web search results

Scaling up search engine audits: Practical insights for algorithm auditing

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