Theory development and empirical research in the field of journalism and communication science are influenced by the digitalization of media in many ways, not least because of the availability of large amounts of individual traces of behavior over long periods of time. The novel area of computational communication science complements traditional empirical communication research with new methods as well as methodological perspectives. Our research group focuses on the automatic collection and computational modeling of individual user behavior and emerging communication processes and structures. This concerns theory development, e.g. via statistical and agent-based simulation methods, as well as data collection and analysis, e.g. in the area of automatic content analysis and statistical modeling of complex data structures.
In addition to research on methodological issues of empirical communication research and the development and application of novel methods, we study the contents, use and impact of digital media, individual news and media repertoires and audience networks as well as problematic media use.
Fähnrich, B., Vogelgesang, J., & Scharkow, M. (2020). Evaluating universities’ strategic online communication: How do Shanghai Ranking’s top 50 universities grow stakeholder engagement with Facebook posts? Journal of Communication Management, online first. https://doi.org/10.1108/JCOM-06-2019-0090
Scharkow, M., Mangold, F., Stier, S., & Breuer, J. (2020). How social network sites and other online intermediaries increase exposure to news. Proceedings of the National Academy of Sciences, 201918279. doi:10.1073/pnas.1918279117
Trepte, S., Scharkow, M., & Dienlin, T. (2020). The privacy calculus contextualized: The influence of affordances. Computers in Human Behavior, 104, 106115.
Scharkow, M. (2019). The reliability and temporal stability of self-reported media exposure: A meta-analysis.Communication Methods and Measures, 13(3), 198–211.
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