Haim, M. & Hase, V. (in press). Computational Methods und Tools für die Erhebung und Auswertung von Social-Media-Daten. [Computational methods and tools for the collection and analysis of socia-media data.] In S. Stollfuß, L. Niebling, & F. Raczkowski (eds.), Handbuch Digitale Medien und Methoden. Wiesbaden: Springer VS. https://doi.org/10.1007/978-3-658-36629-2_41-1

Waldherr, A., Weber, M., Wu, S., Haim, M., Velden, M. A. v. d., & Chen, K. (2024). Between innovation and standardization: Best practices and inclusive guidelines in Computational Communication Science. Journalism & Mass Communication Quarterly, Advance Online Publication. https://doi.org/10.1177/10776990241301676

Hase, V., Ausloos, J., Boeschoten, L., Pfiffner, N., Janssen, H., Araujo, T., Carrière, T., Vreese, C. d., Haßler, J., Loecherbach, F., Kmetty, Z., Möller, J., Ohme, J., Schmidbauer, E., Struminskaya, B., Trilling, D., Welbers, K., & Haim, M. (2024). Fulfilling data access obligations: How could (and should) platforms facilitate data donation studies? Internet Policy Review, 13(3). https://doi.org/10.14763/2024.3.1793

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://doi.org/10.5117/CCR2024.2.2.hase

Knöpfle, P., Haim, M., & Breuer, J. (2024). Key topic or bare necessity? How research ethics are addressed and discussed in Computational Communication Science. Publizistik, 69, 333–356. https://doi.org/10.1007/s11616-024-00846-7

Breuer, J., Knöpfle, P., & Haim, M. (9/2024). Reproduzierbarkeit und Replizierbarkeit bei Forschung mit Social-Media-Daten. [Reproducibility and replicability for researching social media data.] Presented at the Combined Annual 53rd DGPs Congress/15th ÖGP Conference, Vienna.

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, 7, 1625–1644. https://doi.org/10.1007/s42001-024-00283-6

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://doi.org/10.5771/2192-4007-2023-4-277

M. Haim, V. Hase, J. Schindler, M. Bachl, & E. Domahidi (2023). Validity and the Four "R's": (Re-)Establishing Standards for Content Analysis. Studies in Communication and Media.

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://doi.org/10.5771/1615-634X-2023-1-2-130

Haim, M. & Puschmann, C. (2023). Opening up data, tools, and practices: Collaborating with the future. Digital Journalism, 11(2), 1-8. https://doi.org/10.1080/21670811.2023.2174894

Breuer, J., Kmetty, Z., Haim, M., & Stier, S. (2023). User-centric approaches for collecting Facebook data in the 'post-API age': Experiences from two studies and recommendations for future research. Information, Communication & Society, 26(14), 2649-2668. https://doi.org/10.1080/1369118X.2022.2097015

M. Haim & C. Puschmann (2023). Analytical Advances through Open Science: Employing a Reference Dataset to Foster Best-Practice Data Validation, Analysis, and Reporting. Digital Journalism.

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.

ScrapeBotR (2021). An R package to orchestrate ScrapeBot for agent-based testing. https://github.com/MarHai/ScrapeBotR.

Haim, M. (11/2021). Computational Methods für Journalismus und Journalismusforschung. [Computational methods for journalism and journalism studies.] Invited presentation at Zukunftswerkstatt, Ulrich Saxer-Stiftung, Zurich.

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. & Unkel, J. (4/2021). Algorithmic auditing through agent-based experiments. Presented at the 65th Annual Conference of the DGPuK, Zurich.

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://doi.org/10.5771/1615-634X-2021-1-65 *

Haim, M., Stier, S., & Breuer, J. (5/2020). Open science vs. privacy? A case study with linked web tracking, social media, and survey data. Presented at the 70th Annual Conference of the International Communication Association, Gold Coast.

Haim, M. (2020). Agent-based testing: An automated approach toward artificial reactions to human behavior . Journalism Studies, 21(7), 895-911. https://doi.org/10.1080/1461670x.2019.1702892

2019: OsloMet Digital Journalism Research Fellow to the Oslo Metropolitan University, Norway. https://film.oslomet.no/investigating-algorithmic-content

Haim, M. (2019). Capturing the dynamics of online news. In P. Müller, S. Geiß, C. Schemer, T. K. Naab, & C. Peter (eds.), Dynamische Prozesse der öffentlichen Kommunikation. Methodische Herausforderungen (S. 38-56). Köln: Halem.

Haim, M. & Nienierza, A. (2019). Computational observation: Challenges and opportunities of automated observation within algorithmically curated media environments using a browser plug-in. Computational Communication Research, 1(1), 79-102. https://doi.org/10.5117/ccr2019.1.004.haim

Brosius, H.-B., Haim, M., & Weimann, G. (2019). Diffusion as a future perspective of agenda setting. The Agenda Setting Journal, 3(2), 175-190. https://doi.org/10.1075/asj.18022.hai

Haim, M. (5/2019). Agent-based testing: An automated approach toward artificial reactions to human behavior. Presented at the 69th Annual Conference of the International Communication Association, Washington D.C.

ScrapeBot (2019). A Selenium-based tool for agent-based testing. https://github.com/MarHai/ScrapeBot.

Haim, M. (3/2019). Personalized and polarized? Reflections on researching algorithmic content curation. Invited presentation at the Amsterdam School of Communication Research (ASCoR), Amsterdam.

Haim, M. (2018). Mehr methodischer Mut, bitte! [More methodical courage, please!] Aviso, 66, 8. https://www.dgpuk.de/de/aviso.html.

Haim, M. (9/2018). Challenges and experiences from the automated observation of social media use through a browser plug-in. Computational Social Science in the Age of Networked Media, Stavanger.

Haim, M. & Nienierza, A. (9/2018). Computational observation: Möglichkeiten und Herausforderungen automatisierter Beobachtungen in algorithmischen Informationsumgebungen mithilfe eines eigens entwickelten Browser-Plugins. [Computational observation: Challenges and Opportunities of automated observations within algorithmic information environments using a dedicated browser plug-in.] Presented at the 20th Annual Conference of the Methods Division of the DGPuK, Ilmenau. *

2017: Ausgezeichnet für Exzellente Lehre am IfKW der LMU (Award for Excellence in Teaching), 2nd place, for the seminar Datenanalyse.

Haim, M. (9/2017). Up to date. Zu Aktualisierungsmustern und Änderungsintervallen im Online-Journalismus. [Up to date. Refresh cycles and update patterns in online journalism.] Presented at the 19th Annual Conference of the Methods Division of the DGPuK, Mainz.

ScrapeBot (2015). CasperJS-based tool for automatized website interaction and scraping. http://dx.doi.org/10.1080/10410236.2015.1113484, https://github.com/MarHai/ScrapeBot/tree/v1.1.

Keyling, T. & Haim, M. (10/2014). Zur Stichprobenqualität von Online-Nachrichtenmedien. [On the quality of sampling in online media.] Presented at the 16th Annual Conference of the Methods Division of the DGPuK, Munich.