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This article evaluates the quality of data collection in individual-level desktop information tracking used in the social sciences and shows that the existing approaches face sampling issues, validity issues due to the lack of content-level data and their disregard of the variety of devices and long-tail consumption patterns as well as transparency and privacy issues. To overcome some of these problems, the article introduces a new academic tracking solution, WebTrack, an open source tracking tool maintained by a major European research institution. The design logic, the interfaces and the backend requirements for WebTrack, followed by a detailed examination of strengths and weaknesses of the tool, are discussed. Finally, using data from 1185 participants, the article empirically illustrates how an improvement in the data collection through WebTrack leads to new innovative shifts in the processing of tracking data. As WebTrack allows collecting the content people are exposed to on more than classical news platforms, we can strongly improve the detection of politics-related information consumption in tracking data with the application of automated content analysis compared to traditional approaches that rely on the list-based identification of news., Comment: 73 pages

The growing availability of data about online information behaviour enables new possibilities for political communication research. However, the volume and variety of these data makes them difficult to analyse and prompts the need for developing automated content approaches relying on a broad range of natural language processing techniques (e.g. machine learning- or neural network-based ones). In this paper, we discuss how these techniques can be used to detect political content across different platforms. Using three validation datasets, which include a variety of political and non-political textual documents from online platforms, we systematically compare the performance of three groups of detection techniques relying on dictionaries, supervised machine learning, or neural networks. We also examine the impact of different modes of data preprocessing (e.g. stemming and stopword removal) on the low-cost implementations of these techniques using a large set (n = 66) of detection models. Our results show the limited impact of preprocessing on model performance, with the best results for less noisy data being achieved by neural network- and machine-learning-based models, in contrast to the more robust performance of dictionary-based models on noisy data.

News factors can be conceptualized as general relevance indicators guiding the attention of all humans. However, that doesn't mean that they are the only factors influencing selection processes or that all news factors have the same importance across different actor types. Within the concept of news factors it is still unclear to what degree those news factors also apply to the communication outside of traditional mass media. We therefore ask whether and how actors with varying degrees of professionalization employ news factors in their communication differently. To answer our research question, we conducted a quantitative content analysis and compared the coverage in traditional newspapers with the communication of civil society actors with varying degrees of professionalization. We analyzed the relevance of news factors within the presentation of a specific issue, namely climate change in Germany. Our results show that news factors are - at least partly - also applied by non-journalist actors. The mass media and the more professionalized civil society actors do not apply news factors more strongly to their communication than do non-professionalized civil society actors. Instead, we find that different actors focus on different news factors.

Economic considerations, identity related considerations and cueing theory are used for explaining citizens' attitudes towards the European Union. Yet, all of this research has failed to show how elite cues on interests and identities actually reach the citizens. As a consequence, the author argues that domestic mass media as the most widely used source for citizens' information about the European Union has the potential to fill this missing link. Mass media actively construct reality by promoting ideas (agenda-setting and framing) and thereby shaping processes of socialization and persuasion. In this article the author discusses theoretical concepts of how mass media might affect citizens' attitudes, summarizes what we know about the role of domestic mass media in the course of EU integration, derives research desiderates and finally shows why knowledge on the link between mass media and citizens is paramount to understand the future of EU integration.

In this article, we analyze political parties' campaign communication during the 2009 European Parliamentary election in 11 countries (Austria, Bulgaria, Czech Republic, Germany, Hungary, The Netherlands, Poland, Portugal, Spain, Sweden, and the UK). We study which types of issues Euroskeptic fringe and Euroskeptic mainstream parties put on their campaign agendas and the kind and extent of EU opposition they voice. Further, we seek to understand whether Euroskeptic and non-Euroskeptic parties co-orient themselves toward each other within their national party systems with regard to their campaigns. To understand the role of Euroskeptic parties in the 2009 European Parliamentary elections, we draw on a systematic content analysis of parties' posters and televised campaign spots. Our results show that it is Euroskeptic parties at the edges of the political spectrum who discuss polity questions of EU integration and who most openly criticize the union. Principled opposition against the project of EU integration, however, can only be observed in the UK. Finally, we find indicators for co-orientation effects regarding the tone of EU mobilization: In national political environments where Euroskeptic parties strongly criticize the EU, pro-European parties at the same time publicly advance pro-EU positions., Vallkampanjer

In this chapter we develop an agenda for future research on the personalization of politics. To do so, we clarify the propositions of the personalization hypothesis, critically discuss the normative standard on which most studies base their evaluation of personalization, and systematically summarize empirical research findings. We show that the condemnation of personalization is based on a trivial logic and on a maximalist definition of democracy. The review of empirical studies leads us to question the assumption that personalization has steadily increased in all areas of politics. Finally, our normative considerations help us develop new research questions on how personalized politics affects democracy. Moreover, this review also makes clear that another weakness of today's empirical research on the personalization of politics lies in methodological problems and a lack of analysis of the impacts of systemic and contextual variables. Consequently, we suggest methodological pathways and possible explanatory factors for the study of personalization.

News factors can be conceptualized as general relevance indicators guiding the attention of all humans. However, that doesn't mean that they are the only factors influencing selection processes or that all news factors have the same importance across different actor types. Within the concept of news factors it is still unclear to what degree those news factors also apply to the communication outside of traditional mass media. We therefore ask whether and how actors with varying degrees of professionalization employ news factors in their communication differently. To answer our research question, we conducted a quantitative content analysis and compared the coverage in traditional newspapers with the communication of civil society actors with varying degrees of professionalization. We analyzed the relevance of news factors within the presentation of a specific issue, namely climate change in Germany. Our results show that news factors are - at least partly - also applied by non-journalist actors. The mass media and the more professionalized civil society actors do not apply news factors more strongly to their communication than do non-professionalized civil society actors. Instead, we find that different actors focus on different news factors.