Prof. Dr. Markus Strohmaier
Chair of Data Science in the Economic and Social Sciences
Credit: Katrin Glückler
Main fields of research
- Computational Social Science
- Social and Economic Data Science
- Network Science
- Text Mining
Curriculum vitae
| 2017- | present Scientific Coordinator for Digital Behavioral Data at GESIS – Leibniz Institute for the Social Sciences |
| 2017–2021 | Chair for Computational Social Sciences and Humanities, RWTH Aachen University |
| 2013–2017 | Professor for Web-Science, University of Koblenz-Landau |
| 2013–2017 | Founder and Scientific Director of the Computational Social Science Department at GESIS – Leibniz Institute for the Social Sciences |
| 2011–2012 | Visiting Assistant Professor at Stanford University, Palo Alto, CA, USA |
| 2010–2011 | Visiting Scientist at (XEROX) Parc, Palo Alto, CA, USA |
| 2007–2013 | Assistant Professor (Univ.Ass.) at Graz University of Technology |
Selected memberships
- External Faculty Member at the Complexity Science Hub Vienna
Prizes, awards, honors
- 2015 Best Paper Award at WWW'15, the 24th International World Wide Web Conference (WWW2015), Best Paper ''Hyptrails: A bayesian approach for comparing hypotheses about human trails'', Firenze, Italy, Co-Author
- 2015 Best Paper Award at WebSci'15, the ACM Web Science Conference (WebSci2015), Best Paper ''Mining cross-cultural relations from Wikipedia – A study of 31 European food cultures'', Oxford, UK, Co-Author
- 2015 Honorable Mention Award at ICWSM'15, the 9th International AAAI Conference on Weblogs and Social Media, Honorable Mention Award ''Voting behaviour and power in online democracy: A study of LiquidFeedback in Germany’s pirate party'', Oxford, UK, Co-Author
- 2014 Best Paper Award at ICWSM'14, the 8th International AAAI Conference on Weblogs and Social Media, Best Paper ''When politicians talk: Assessing online conversational practices of political parties on twitter'', Ann Arbor, MI, USA, Co-Author
Selected publications
- Pellert, M., Lechner, C. M., Wagner, C., Rammstedt, B. and Strohmaier, M. (2024). AI psychometrics: Assessing the psychological profiles of large language models through psychometric inventories. Perspectives on Psychological Science, 19, 808–826.
- Génois, M., Zens, M., Oliveira, M., Lechner, C. M., Schaible, J. and Strohmaier, M. (2023). Combining sensors and surveys to study social interactions: A case of four science conferences. Personality Science : PS, 4, 1–24.
- Neuhäuser, L., Karimi, F., Bachmann, J., Strohmaier, M. and Schaub, M. T. (2023). Improving the visibility of minorities through network growth interventions. Communications Physics, 6, 108–13.
- Smirnov, I., Oprea, C. and Strohmaier, M. (2023). Toxic comments are associated with reduced activity of volunteer editors on Wikipedia. PNAS Nexus, 2, 1–10.
- Espín-Noboa, L., Wagner, C., Strohmaier, M. and Karimi, F. (2022). Inequality and inequity in network-based ranking and recommendation algorithms. Scientific Reports, 12, 1–14.
- Koncar, P., Santos, T., Strohmaier, M. and Helic, D. (2022). Correction to: On the application of the Two-Factor Theory to online employer reviews. Journal of Data, Information and Management, 4, 87.
- Koncar, P., Santos, T., Strohmaier, M. and Helic, D. (2022). On the application of the Two-Factor Theory to online employer reviews. Journal of Data, Information and Management, 4, 1–23.
- Oliveira, M., Karimi, F., Zens, M., Schaible, J., Génois, M. and Strohmaier, M. (2022). Group mixing drives inequality in face-to-face gatherings. Communications Physics, 5, 1–9.
- Reelfs, J. H., Hohlfeld, O., Strohmaier, M. and Henckell, N. (2022). Characterizing the country-wide adoption and evolution of the Jodel messaging app in Saudi Arabia. The Journal of Web Science, 8, 1–14.
- Sikdar, S., Sachdeva, R., Wachs, J., Lemmerich, F. and Strohmaier, M. (2022). The effects of gender signals and performance in online product reviews. Frontiers in Big Data, 4, 1–1.
- Neuhäuser, L., Stamm, F. I., Lemmerich, F., Schaub, M. T. and Strohmaier, M. (2021). Simulating systematic bias in attributed social networks and its effect on rankings of minority nodes. Applied Network Science, 6, 1–22.
- Smirnov, I., Lemmerich, F. and Strohmaier, M. (2021). Quota-based debiasing can decrease representation of the most under-represented groups. Royal Society Open Science, 8, 1–5.
- Wagner, C., Strohmaier, M., Olteanu, A., Kiciman, E., Contractor, N. and Eliassi-Rad, T. (2021). Measuring algorithmically infused societies. Nature, 595, 197–204.