Lukas Erhard is a research assistant at the Interchange Forum for Reflecting on Intelligent Systems (SRF IRIS). In this context, as well as part of the Computational Social Science (CSS) chair, he sits at the intersection of social and computer sciences and works on the integration of machine learning techniques into the social science research process.
Since his master's program, his methodological focus has been on large-scale data processing, statistics, machine learning, natural language processing, and social network analysis.
His dissertation project analyzes influences of (social) media on the opinion formation process as well as the attitudes of individuals.
- Erhard, L., & Heiberger, R. (2023). Regression and Machine Learning. In J. Skopek (Ed.), Research Handbook on Digital Sociology (pp. 129--144). Edward Elgar Publishing. https://www.e-elgar.com/shop/gbp/research-handbook-on-digital-sociology-9781789906752.html
- Unger, S., Erhard, L., Wieczorek, O., Koß, C., Riebling, J., & Heiberger, R. H. (2022). Benefits and detriments of interdisciplinarity on early career scientists’ performance. An author-level approach for U.S. physicists and psychologists. PLOS ONE, 17(6), Article 6. https://doi.org/10.1371/journal.pone.0269991
- Erhard, L., Heiberger, R. H., & Windzio, M. (2021). Diverse Effects of Mass Media on Concerns about Immigration: New Evidence from Germany, 2001–2016. European Sociological Review. https://doi.org/10.1093/esr/jcab063
- Wieczorek, O., Unger, S., Riebling, J., Erhard, L., Koß, C., & Heiberger, R. (2021). Mapping the field of psychology: Trends in research topics 1995–2015. Scientometrics. https://doi.org/10/gk7x93