While survey research has been at the heart of social science for decades and social scientific research with digital trace data has been growing rapidly in the last few years, until now, there are relatively few studies that combine these two data types. This may be surprising given the potential of linking surveys and digital trace data, but at the same time, it is important to note that the collection and analysis of such linked data are challenging in several regards. The three key issues are: (1) data linking including informed consent for individual-level studies, (2) methodological and ethical issues impeding the scientific (re)analysis of linked survey and digital trace data sets, and (3) developing conceptual and theoretical frameworks tailored toward the multidimensionality of such data. This special issue addresses these challenges by presenting cutting-edge methodological work on how to best collect and analyze linked data as well as studies that have successfully combined survey data and digital trace data to find innovative answers to relevant social scientific questions.

Political astroturfing, a centrally coordinated disinformation campaign in which participants pretend to be ordinary citizens acting independently, has the potential to influence electoral outcomes and other forms of political behavior. Yet, it is hard to evaluate the scope and effectiveness of political astroturfing without "ground truth" information, such as the verified identity of its agents and instigators. In this paper, we study the South Korean National Information Service's (NIS) disinformation campaign during the presidential election in 2012, taking advantage of a list of campaign accounts published in court proceedings. Features that best distinguish these accounts from regular users in contemporaneously collected Twitter data are traces left by coordination among astroturfing agents, instead of the individual account characteristics typically used in related approaches such as social bot detection. We develop a methodology that exploits these distinct empirical patterns to identify additional likely astroturfing accounts and validate this detection strategy by analyzing their messages and current account status. However, an analysis relying on Twitter influence metrics shows that the known and suspect NIS accounts only had a limited impact on political social media discussions. By using the principal-agent framework to analyze one of the earliest revealed instances of political astroturfing, we improve on extant methodological approaches to detect disinformation campaigns and ground them more firmly in social science theory.

Although considerable research has concentrated on online campaigning, it is still unclear how politicians use different social media platforms in political communication. Focusing on the German federal election campaign 2013, this article investigates whether election candidates address the topics most important to the mass audience and to which extent their communication is shaped by the characteristics of Facebook and Twitter. Based on open-ended responses from a representative survey conducted during the election campaign, we train a human-interpretable Bayesian language model to identify political topics. Applying the model to social media messages of candidates and their direct audiences, we find that both prioritize different topics than the mass audience. The analysis also shows that politicians use Facebook and Twitter for different purposes. We relate the various findings to the mediation of political communication on social media induced by the particular characteristics of audiences and sociotechnical environments.Keywords cross-media analysis, language models, online campaigning, social media, text analysis Social media have become ubiquitous communication channels for candidates during election campaigns. Platforms like Facebook and Twitter enable candidates to directly reach out to voters, mobilize supporters, and influence the public agenda. These fundamental changes in political communication therefore present election candidates with a widened range of strategic choices. Should candidates address the topics most important to a mass audience? Should they tailor their messages to the specific habits and audiences on social media platforms? Although academic research on social media campaigning has flourished in the past several years (Boulianne, 2016;Jungherr, 2016b), it is still unclear which topics politicians address on these platforms, since previous research mostly concentrated on meta data generated by the use of communication conventions such as retweets, @-mentions, likes, or hashtags. Understanding the ways in which politicians Sebastian Stier, Arnim Bleier, and Haiko Lietz are Postdoctoral Researchers, and Markus Strohmaier is a Scientific Director at GESIS -Leibniz Institute for the Social Sciences.Address correspondence to Dr. Sebastian Stier, Department Computational Social Science, GESIS -Leibniz Institute for the Social Sciences, Unter Sachsenhausen 6-8, Köln, D-50667. E-mail: sebastian.stier@gesis.org Color versions of one or more of the figures in the article can be found online at www. tandfonline.com/UPCP. Political Communication, 35:50-74, 2018© 2017 Taylor & Francis Group, LLC ISSN: 1058 print / 1091-7675 online DOI: https://doi.org/10. 1080/10584609.2017.1334728 adapt the contents of their messages to the peculiarities of different platforms generates deeper insights into how political communication is shaped by social media.Much research revealed a continuation of the status quo in online campaigning, as politicians mostly replicated traditional messages and campaign mo...

Research has prominently assumed that social media and web portals that aggregate news restrict the diversity of content that users are exposed to by tailoring news diets toward the users’ preferences. In our empirical test of this argument, we apply a random-effects within–between model to two large representative datasets of individual web browsing histories. This approach allows us to better encapsulate the effects of social media and other intermediaries on news exposure. We find strong evidence that intermediaries foster more varied online news diets. The results call into question fears about the vanishing potential for incidental news exposure in digital media environments.

Although considerable research has concentrated on online campaigning, it is still unclear how politicians use different social media platforms in political communication. Focusing on the German federal election campaign 2013, this article investigates whether election candidates address the topics most important to the mass audience and to which extent their communication is shaped by the characteristics of Facebook and Twitter. Based on open-ended responses from a representative survey conducted during the election campaign, we train a human-interpretable Bayesian language model to identify political topics. Applying the model to social media messages of candidates and their direct audiences, we find that both prioritize different topics than the mass audience. The analysis also shows that politicians use Facebook and Twitter for different purposes. We relate the various findings to the mediation of political communication on social media induced by the particular characteristics of audiences and sociotechnical environments.

Research has shown that citizens with populist attitudes evaluate the news media more negatively, and there is also suggestive evidence that they rely less on established news sources like the legacy press. However, due to data limitations, there is still no solid evidence whether populist citizens have skewed news diets in the contemporary high-choice digital media environment. In this paper, we rely on the selective exposure framework and investigate the relationship between populist attitudes and the consumption of various types of online news. To test our theoretical assumptions, we link 150 million Web site visits by 7,729 Internet users in France, Germany, Italy, Spain, the United Kingdom, and the United States to their responses in an online survey. This design allows us to measure media exposure more precisely than previous studies while linking these data to demographic attributes and political attitudes of participants. The results show that populist attitudes leave pronounced marks in people's news diets, but the evidence is heterogeneous and highly contingent on the supply side of a country's media system. Most importantly, citizens with populist attitudes visit less Web sites from the legacy press, while consuming more hyperpartisan news. Despite these tendencies, the Web tracking data show that populist citizens still primarily get their news from established sources. We

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