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

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.

Breuer, J., Kmetty, Z., Haim, M., & Stier, S. (2022). User-centric approaches for collecting Facebook data in the 'post-API age': Experiences from two studies and recommendations for future research. Information, Communication & Society, Advance Online Publication. https://dx.doi.org/10.1080/1369118X.2022.2097015

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. (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 *

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., 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://dx.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://dx.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://dx.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.