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
Cause/antecedents/history (News Performance)