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.

Springer, N. & Haim, M. (9/2020). Maschinelles Lernen in der Journalismusforschung: Rechtliche, ethische und praktische Herausforderungen eines interdisziplinären Lehr-/Forschungsprojekts. [Machine learning in journalism studies: Legal, ethical, and practical challenges in interdisciplinary teaching and research.] Presented at the Presented at the Annual Conference of the Journalism Division of the DGPuK, Hamburg.

Haim, M. (2019). Die Orientierung von Online-Journalismus an seinen Publika. Anforderung, Antizipation, Anspruch. [The orientation of online journalism toward its audiences. Demand, anticipation, claim.] Wiesbaden: Springer VS. https://doi.org/10.1007/978-3-658-25546-6.

Haim, M., Heinzel, I., Lankheit, S., Niagu, A.-M., & Springer, N. (5/2019). Identifying the good and the bad: Using machine learning to moderate user commentary on news. Presented at the 69th Annual Conference of the International Communication Association, Washington D.C.

Springer, N. & Haim, M. (11/2018). Machines in moderation: A theoretical framework for the application of machine learning in the management of user commentary. Presented at the 7th Annual ECREA Conference, Lugano.