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The pervasive use of mobile information technologies brings new patterns of media usage, but also challenges to the measurement of media exposure. Researchers wishing to, for example, understand the nature of selective exposure on algorithmically driven platforms need to precisely attribute individuals' exposure to specific content. Prior research has used tracking data to show that survey-based self-reports of media exposure are critically unreliable. So far, however, little effort has been invested into assessing the specific biases of tracking methods themselves. Using data from a multi-method study, we show that tracking data from mobile devices is linked to systematic distortions in self-report biases. Further inherent but unobservable sources of bias, along with potential solutions, are discussed.The paper is structured as follows: We first review the existing state of research on the relation between self-reports and tracking data. Building on that literature, we discuss the theoretical and pragmatic limitations in the data collection process of various tracking methods, with a special focus on mobile devices.As that section will reveal, there are numerous potential sources of errors at various stages in the data collection process, which warrant an investigation into biases in tracking data. We go on to show empirically that such biases exist, drawing on original data from a multi-method study comprising survey and tracking data. In order to establish the validity of data and method, we first replicate existing findings of biased selfassessments (RQ 1). Using the differences between participants who provided mobile and/or desktop tracking data, we then show a genuinely new type of bias, namely a differential bias in self-reports of people willing to share mobile tracking data (RQ 2). Finally, we assess the impact of this bias through a simulation exercise (RQ 3), which builds on a realistic statistical model of perceived polarization to show how strong tracking bias will impact results. Literature Review: Self-report Bias, Direction and SourcesA growing list of study designs aims to bypass the insufficient reliability of self-reports by directly capturing trace data of digital media usage through various means (Revilla et al. 2017, Araujo et al. 2017, Vraga et al. 2016, Scharkow 2016. The results show rather consistently that there are strong systematic biases present in self-reports across different devices, settings and operationalizations. An early study that served to draw attention to the issues is Prior's (2009b) investigation of time spent on TV. By comparing survey-based self-assessments to Nielsen people meter data (which are generated from custom tracking devices on TVs, see Napoli 2003), he shows that individuals on average overestimate their TV usage by a factor of three, with younger respondents doing worse. Tapping into an earlier debate in political communication (Price & Zaller 1993), the paper suggests either using alternative methods for measuring exposure or instead focusing on deeper l...

Seek and you shall find? A content analysis on the diversity of five search engines' results on political queriesSearch engines are important political news sources and should thus provide users with diverse political information -an important precondition of a well-informed citizenry. The search engines' algorithmic content selection strongly influences the diversity of the content received by the users -particularly since most users highly trust search engines and often click on only the first result. A widespread concern is that users are not informed diversely by search engines, but how far this concern applies has hardly been investigated. Our study is the first to investigate content diversity provided by five search engines on ten current political issues in Germany. The findings show that sometimes even the first result is highly diverse, but in most cases, more results must be considered to be informed diversely. This unreliability presents a serious challenge when using search engines as political news sources. Our findings call for media policy measures, for example in terms of algorithmic transparency.possible, but by no means guaranteed -particularly if a user simply clicks on the first result, as most users do (Pan et al., 2007).Below, we first describe how the filtering and sorting of search engines can affect content diversity, give an overview of the few existing empirical studies thereon, and derive our innovative measurement of content diversity. Afterwards, we present our findings and discuss their implications as well as our study's limitations. Conceptual framework How search engines influence content diversityDiversity is considered a precondition of healthy democracies (Napoli, 1999) since it is assumed to guarantee a public debate with opposing viewpoints and a well-informed citizenry, as illustrated by the "marketplace of ideas" -an idealized metaphor of public discourse (Karppinen, 2006): citizens shall freely exchange diverse ideas and viewpoints to ensure well-informed decision-making, tolerance toward other viewpoints (Jandura & Friedrich, 2014), and the stimulation of "popular wisdom" (Donohue & Glasser, 1978, p. 592). The media should contribute to it by providing diverse content (Jandura & Friedrich, 2014), stressing the importance of diversity in media policy (Just, 2009) and in communication research.Originally, the debate focused on human, journalistic gatekeepers, often revitalized by developments considered as potential threats to content diversity (e.g., concentration processes in the newspaper market (Donohue & Glasser, 1978), the introduction of commercial broadcasting in European countrues (Aslama, Hellman, & Sauri, 2004)). The rise of the Internet brought along the hope of unlimited content diversity online (European Commission, 2010, p. 30), but it quickly turned out that the processing capacities of the users limit diversity: in the information flood, they rely on gatekeepers to identify relevant information more than ever. Search engines were invented exactly for ...

The term tabloidization describes the spillover of tabloid journalism’s characteristics – which aim to attract recipients’ attention – to other media types, particularly elite media. The validity of the common assumption that tabloidization has increased over the last decades is unknown since long-term studies are widely lacking. Applying a most similar systems design, the current study pursues several goals: On the macro-level, it aims to clarify whether campaign coverage of seven German and Austrian elite newspapers has become more tabloidized over six decades (1949–2009) and whether the long-term developments are related to three structural drivers of tabloidization – tabloid newspapers, commercial television, and the Internet. On the meso-level, the study investigates among outlet differences in tabloidization. Tabloidization is conceptualized as multidimensional, considering the topic, focus, and style dimension. The results show that tabloidization in general and in the single newspapers has increased, but only slightly and only in a few respects. While some of the hypothesized structural influences on tabloidization are confirmed, other, more situative drivers of tabloidization seem to account for short-term ups and downs in levels of tabloidization.

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