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Science communication has been defined as encompassing “all forms of communication by and about the sciences, within science (professional audience) as well as in the [broader] public sphere (general audience)”. This broad understanding of science communication includes all kinds of communication focusing on scientific work or scientific results, within science or to non-scientists, in one-directional or dialogical form. It also includes communication about the natural sciences, the arts or the humanities, and it has considerable overlaps with research fields such as health communication and risk communication. Content analysis, especially of media content, is a common method in the research field and this article provides an overview of this research.

The transition from low- to high-choice media environments has had far-reaching implications for citizens’ media use and its relationship with political knowledge. However, there is still a lack of comparative research on how citizens combine the usage of different media and how that is related to political knowledge. To fill this void, we use a unique cross-national survey about the online and offline media use habits of more than 28,000 individuals in 17 European countries. Our aim is to (i) profile different types of news consumers and (ii) understand how each user profile is linked to political knowledge acquisition. Our results show that five user profiles – news minimalists, social media news users, traditionalists, online news seekers, and hyper news consumers – can be identified, although the prevalence of these profiles varies across countries. Findings further show that both traditional and online-based news diets are correlated with higher political knowledge. However, online-based news use is more widespread in Southern Europe, where it is associated with lower levels of political knowledge than in Northern Europe. By focusing on news audiences, this study provides a comprehensive and fine-grained analysis of how contemporary European political information environments perform and contribute to an informed citizenry.

Since Eveland and Shah (2003) published their seminal study on the impact of social networks on media bias perceptions in the US, little has been researched about the interpersonal antecedents of hostile media perceptions. In this study we address this gap by investigating the role of safe, or like-minded, political discussions on individuals’ likelihood to perceive media as hostile. We use survey data from more than 5,000 individuals in Germany. Our findings reveal that like-minded discussions increase one’s likelihood to perceive media as hostile; yet, only among those more politically engaged and ideologically on the left. The significance and theoretical implications of the results are discussed in the concluding section.

Field of application/theoretical foundation: Analyses of actor diversity are theoretically linked to news performance and the democratic media function of integration (Imhof, 2010). This construct is related to the normative assumption that news content should represent society as a whole and thus cover a large variety of societal groups (Boydstun et al., 2014). More recent studies also focus on the influence of algorithms on news diversity (Möller et al., 2018). Analyses are often carried out in three steps. First, all actors are (inductively or deductively) identified. Second, actors are coded according to predefined lists. Third, the level of diversity is determined using diversity indices (van Cuilenburg, 2007). Diversity indices are calculated at article level (internal diversity) or at the organizational level (external diversity) to compare diversity between news articles of a single outlet or between different news outlets. References/combination with other methods of data collection: Studies on actor diversity use both manual and automated content analysis to investigate the occurrence of actors and in texts. They use inductive or deductive approaches and/or a combination of both to identify actor categories and extend predefined lists of actors (van Hoof et al., 2014). Example studies: Masini et al. (2018); Humprecht & Esser (2018) Table 1. Summary of studies on actor diversity Author(s) Sample Unit of Analysis Values Reliability Masini et al. (2018) Content type: news about immigration Outlet/ country: 2 news outlets in four countries (BE, DE, IT, UK) Sampling period: January 2013 to April 2014 Sample size: N=2490) Unit of analysis: news article No. of actors coded: max. 10 quoted or paraphrased actors per article Level of analysis: article and news outlet level Diversity measure: Simpson’s diversity index National politics, international politics, public opinion and ordinary people, immigrants, civil society, public agencies/ organizations, judiciary/police/military, religion, business/corporate/finance, journalists/ media celebrities, traffickers/smugglers Krippendorff’s alpha average ?0.78 Humprecht & Esser (2018) Content type: Political routine-period news Outlet/ country: 48 online news outlets from six countries (CH, DE, FR, IT, UK, US) Sampling period: June – July 2012 Sample size: N= 1660 Unit of analysis: Political news items (make reference to a political actor, e.g. politician, party, institution in headline, sub?headline, in first paragraph or in an accompanying visual) News items are all journalistic articles mentioned on the front page (‘first layer’ of the website) that are linked to the actual story (on second layer of website) No. of actors coded: Max. 5 main actors (mentioned twice) per news item measured Level of analysis: news outlet level Diversity measure: relative entropy Executive (head of state and national government), legislative (national parliament and national parties), judicial (national courts and judges), national administration (prosecution, regional government authority, and police or army), foreign politicians (foreign heads of state and other foreign politicians), and international organizations (supranational and international organizations) Cohen’s kappa average ?0.76 References Boydstun, A. E., Bevan, S., & Thomas, H. F. (2014). The importance of attention diversity and how to measure it. Policy Studies Journal, 42(2), 173–196. https://doi.org/10.1111/psj.12055 Humprecht, E., & Esser, F. (2018). Diversity in Online News: On the importance of ownership types and media system types. Journalism Studies, 19(12), 1825–1847. https://doi.org/10.1080/1461670X.2017.1308229 Imhof, K. (2010). Die Qualität der Medien in der Demokratie. In fög – Forschungsbereich Öffentlichkeit und Gesellschaft (Ed.), Jahrbuch 2010: Qualität der Medien Qualität der Medien (pp. 11–20). Schwabe. https://doi.org/10.1007/978-3-322-97101-2_1 Masini, A., Van Aelst, P., Zerback, T., Reinemann, C., Mancini, P., Mazzoni, M., Damiani, M., & Coen, S. (2018). Measuring and Explaining the Diversity of Voices and Viewpoints in the News: A comparative study on the determinants of content diversity of immigration news. Journalism Studies, 19(15), 2324–2343. https://doi.org/10.1080/1461670X.2017.1343650 Möller, J., Trilling, D., Helberger, N., & van Es, B. (2018). Do not blame it on the algorithm: an empirical assessment of multiple recommender systems and their impact on content diversity. Information Communication and Society, 21(7), 959–977. https://doi.org/10.1080/1369118X.2018.1444076 van Cuilenburg, J. (2007). Media Diversity, Competition and Concentration: Concepts and Theories. In E. de Bens (Ed.), Media Between Culture and Commerce (pp. 25–54). Intellect. van Hoof, A., Jacobi, C., Ruigrok, N., & van Atteveldt, W. (2014). Diverse politics, diverse news coverage? A longitudinal study of diversity in Dutch political news during two decades of election campaigns. European Journal of Communication, 29(6), 668–686. https://doi.org/10.1177/0267323114545712