Hase, V. & Haim, M. (2024). Can we get rid of bias? Mitigating systematic error in data donation studies through survey design strategies. Computational Communication Research, 6(2). https://dx.doi.org/10.5117/CCR2024.2.2.hase

Schwabl, P., Haim, M., & Unkel, J. (2024). Aligning Agent-Based Testing (ABT) with the experimental research paradigm: A literature review and best practices. Journal of Computational Social Science, Advance Online Publication. https://dx.doi.org/10.1007/s42001-024-00283-6

Knöpfle, P., Haim, M., & Breuer, J. (2024). Key topic or bare necessity? How research ethics are addressed and discussed in Computational Communication Science. Publizistik, Advance Online Publication. https://dx.doi.org/10.1007/s11616-024-00846-7

Haim, M., Hase, V., Schindler, J., Bachl, M., & Domahidi, E. (2023). Editorial to the Special Issue: (Re)Establishing quality criteria for content analysis: A critical perspective on the field's core method. Studies in Communication and Media, 12(4), 277-288. https://dx.doi.org/10.5771/2192-4007-2023-4-277

Haim, M. (2023). Computational Communication Science: Eine Einführung. [Computational Communication Science: Introduction.] Wiesbaden: Springer VS. https://link.springer.com/book/10.1007/978-3-658-40171-9.

Haim, M., Leiner, D., & Hase, V. (2023). Integrating data donations into online surveys. Medien & Kommunikationswissenschaft, 71(12), 130-137. https://dx.doi.org/10.5771/1615-634X-2023-1-2-130

Schwabl, P., Unkel, J., & Haim, M. (2023). Vielfalt bei Google? Vielzahl, Ausgewogenheit und Verschiedenheit wahlbezogener Suchergebnisse. In C. Holtz-Bacha (eds.), Die (Massen-) Medien im Wahlkampf. Die Bundestagswahl 2021 (S. 293-316). Wiesbaden: Springer VS. https://dx.doi.org/10.1007/978-3-658-38967-3_11

Haim, M. & Jungblut, M. (2023). How open is communication science? Analyzing open-science principles in the field. Annals of the International Communication Association, 47(3), 338-357. https://dx.doi.org/10.1080/23808985.2023.2201601

Jungblut, M. & Haim, M. (2023). Visual gender stereotyping in campaign communication: Evidence on female and male candidate imagery in 28 countries. Communication Research, 50(5), 535-664. https://dx.doi.org/10.1177/00936502211023333

Hepp, A., Hohmann, F., Belli, A., Boczek, K., Haim, M., Heft, A., Jünger, J., Jürgens, P., Koenen, E., Nordheim, G. v., Rinsdorf, L., Rothenberger, L., Schatto-Eckrodt, T., & Unkel, J. (2021). Forschungssoftware in der Kommunikations- und Medienwissenschaft: Stand, Herausforderungen und Perspektiven. [Research software in communication and media science: Status quo, challenges, and perspectives.] DGPuK-Positionspapiere. https://www.dgpuk.de/sites/default/files/DGPuK%20Positionspapier%20-%20Forschungssoftware%20in%20der%20Kommunikations-%20und%20Medienwissenschaft_0.pdf.

Haim, M. & Jungblut, M. (5/2021). How open is communication science? Analyzing open-science principles in communication science and psychology. Presented at the 71st Annual Conference of the International Communication Association, Denver.

Breuer, J. & Haim, M. (4/2021). Reproducibility and replicability in computational social science: Challenges and potential solutions. Presented at the Open Science and Replicability in the Behavioural Social Sciences, Chemnitz.

Haim, M. (2021). Gütekriterien und Handlungsempfehlungen für die Entwicklung von Forschungssoftware in der Kommunikations- und Medienwissenschaft. [Quality Criteria and Recommendations for Developing Research Software in Communication Science.] Medien & Kommunikationswissenschaft, 69(1), 65-79. https://dx.doi.org/10.5771/1615-634X-2021-1-65 *