Digitalization is changing the media landscape at a rapid pace. Our research group investigates how these changes affect our communication. We are at the interface of Communication and Computer Science, where established social science research meets innovative computational methods.
Our focus is on the development of new theories and the application of modern methods such as automatic content analysis, simulation and the analysis of digital trace data. We use these methods to research how people use digital media, what content they share and what effect this has for individuals and society.
Substantively, we investigate the use of digital media, its contents, and impact, exploring a diverse range of topics such as digital media use, individual’s and organisation’s social media behavior, science communication, and gender diversity in the media and in communication science.
Antonia Glaser, Dennis Maus, Pia Singer, Charlotte Tryba
Ernst, A., Dietrich, F., Rohr, B., Reinecke, L., & Scharkow, M. (2026). Revisiting the digital jukebox in daily life: Applying Mood Management Theory to algorithmically curated music streaming environments. Human Communication Research, 0(0), 1–12. https://doi.org/10.1093/hcr/hqaf030
Ernst, A., & Schnauber-Stockmann, A. (2025). Won’t stop ’til you get enough? Determinants of disengaging from mobile media apps in daily life. Communication Research, 0(0), 1–28. https://doi.org/10.1177/00936502251378582
Meltzer, C. E., Scharkow, M., & Jürgens, P. (2025). Beyond the Beat: The Representation of Women in Music Videos Across Genres Over Four Decades. Computational Communication Research, 7(1), 1. https://doi.org/10.5117/CCR2025.1.11.MELT
Dietrich, F., Ernst, A., Kreling, R., Gilbert, A., Rohr, B., Scharkow, M., & Reinecke, L. (2025). The differential effects of algorithmic recommendations on user experience: Enjoyment and serendipity in everyday music streaming. In Proceedings of the 3rd International Conference of the ACM Greek SIGCHI Chapter (pp. 8-16). https://doi.org/10.1145/3749012.3749040
Schnauber-Stockmann, A., Scharkow, M., Karnowski, V., Naab, T. K., Schlütz, D., & Pressmann, P. (2025). Distinguishing person-specific from situation-specific variation in media use: A meta-analysis. Communication Research, 52(2), 143-172. https://doi.org/10.1177/00936502241262664
Denner, N., Koch, T., Viererbl, B., & Ernst, A. (2024). Feeling Connected and Informed Through Informal Communication: A Quantitative Survey on the Perceived Functions of Informal Communication in Organizations. Journal of Communication Management. https://doi.org/10.1108/JCOM-06-2024-0085
Scharkow, M., & Trepte, S. (2024). National Diversity at Conferences of The International Communication Association. Annals of the International Communication Association, 48(1), 17–36. https://doi.org/10.1080/23808985.2023.2261018
Diversity-X. A pilot project to identify the gender citation gap in the scientific research process
Collaborative project with the field of Media Psychology, Prof. Dr. Sabine Trepte, University of Hohenheim
Duration: 4/2022 – 3/2025, grant from the BMBF, funding line Innovative Women in Focus.
Multilevel Flows of Political Communication on Facebook – A Computational Approach Using Individual Digital Traces
Gemeinschaftsprojekt mit Dr. Marko Bachl, Universität Hohenheim
Laufzeit: 12/2020 – 11/2023, Förderung durch die Fritz Thyssen Stiftung
The Computational Communication Science research group offers at least one course with a focus on computational methods for each of the three bachelor’s-level advanced seminars on methodological applications (content analysis, survey research, and experiment). These courses enable interested students to systematically acquire expertise in this field and immediately apply it in their own research projects. In addition to traditional aspects such as hypothesis generation, research design, sampling, and quality assurance, the courses emphasize the automated collection, statistical analysis, and visualization of large-scale datasets.
The courses are open to all bachelor’s students, but include a substantial component of statistical data analysis and coding exercises using R. Beyond these computational components, student groups remain free to plan and carry out traditional content analyses, surveys, or experiments. To support students particularly interested in computational methods, we aim to enable them to attend all three courses consecutively. Therefore, please contact us by email in addition to registering via Jogustine.
We supervise both bachelor’s and master’s theses in the Master’s program in Digital Communication Science. We are open to a wide range of topics related to media content, media use, and media effects. However, we only supervise empirical (quantitative) theses, which may also include systematic literature reviews. Theses with a methodological focus—particularly on computational methods—are especially welcome.
Students interested in writing their thesis under our supervision should send us an email approximately 4–6 weeks before formal registration, including a preliminary topic proposal (approx. 0.5–1 page, including research question, theoretical foundation, and method). If we have the capacity to supervise your thesis, we will then discuss the specific design of the study and the next steps.