Ruben Bach
Photo credit: Farina Stock
| Course name | Credits | Details | Term |
|---|---|---|---|
| Empirisches Forschungspraktikum I | 5 ECTS | Course details | spring term |
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Research Interests
- Social impacts of AI
- AI and discrimination (Fair ML)
- Using new data sources for social research
- Causal inference with observational data
- Privacy
- Survey methodology (response propensities, measurement error, conditioning effects)
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Career
Academic Career
Ruben is a postdoctoral researcher in social science quantitative methods. He joined the Professorship for Statistics and Methodology in 2018 after spending three years in the Institute for Employment Research’s (IAB) Graduate Program where he wrote his dissertation on respondent conditioning. He completed his PhD (Dr. rer. soc.) at the University of Mannheim in 2018 and holds an M.Sc. in Socio-Economics from the University of Erlangen-Nuremberg and a B.A. in Social Sciences from the University of Dusseldorf.
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Publications
- Gerdon, F., Nissenbaum, H., Bach, R. L., Kreuter, F. & Zins, S. (2021). Individual acceptance of using health data for private and public benefit: Changes during the COVID-19 pandemic. Harvard Data Science Review : HDSR, 3(Spec. Iss. 1), 1–27. https://doi.org/10.1162/99608f92.edf2fc97
- Kuppler, M., Kern, C., Bach, R. L. & Kreuter, F. (2021). Distributive justice and fairness metrics in automated decision-making: How much overlap is there? Ithaca, NY: Cornell University.
- Altmann, S., Milsom, L., Zillessen, H., Blasone, R., Gerdon, F., Bach, R. L., Kreuter, F., Nosenzo, D., Toussaert, S. & Abeler, J. (2020). Acceptability of app-based contact tracing for COVID-19: Cross-country survey study. JMIR mHealth and uHealth : JMU, 8(8), e19857. https://doi.org/10.2196/19857
- Amaya, A., Bach, R. L., Kreuter, F. & Keusch, F. (2020). Measuring the strength of attitudes in social media data. In C. A. Hill (eds.), Big data meets survey science : a collection of innovative methods (S. 163–192). Hoboken, NJ: John Wiley & Sons. https://doi.org/10.1002/9781118976357.ch5
- Bach, R. L., Eckman, S. & Daikeler, J. (2020). Misreporting among reluctant respondents. Journal of Survey Statistics and Methodology : JSSAM, 8(3), 566–588. https://doi.org/10.1093/jssam/smz013
- Bach, R. L. & Wenz, A. (2020). Studying health-related internet and mobile device use using web logs and smartphone records. PLOS ONE, 15(6), e0234663. https://doi.org/10.1371/journal.pone.0234663
- Daikeler, J., Bach, R. L., Silber, H. & Eckman, S. (2020). Motivated misreporting in smartphone surveys. Social Science Computer Review : SSCORE. https://doi.org/10.1177/0894439319900936
- Gerdon, F., Theil, C. K., Kern, C., Bach, R. L., Kreuter, F., Stuckenschmidt, H. & Eckert, K. (2020). Exploring impacts of artificial intelligence on urban societies with social simulations. 40. Kongress der Deutschen Gesellschaft für Soziologie, Online.
- Amaya, A., Bach, R. L., Keusch, F. & Kreuter, F. (2019). New data sources in social science research: Things to know before working with Reddit data. Social Science Computer Review : SSCORE, 1–10. https://doi.org/10.1177/0894439319893305
- Bach, R. L. & Eckman, S. (2019). Participating in a panel survey changes respondents' labour market behaviour. Journal of the Royal Statistical Society. Series A, Statistics in Society, 182(1), 263–281. https://doi.org/10.1111/rssa.12367
- Bach, R. L. & Eckman, S. (2019). Rotation group bias in reporting of household purchases in the U.S. Consumer Expenditure Survey. Economics Letters, 187, Article 108889. https://doi.org/10.1016/j.econlet.2019.108889
- Bach, R. L., Kern, C., Amaya, A., Keusch, F., Kreuter, F., Hecht, J. & Heinemann, J. (2019). Predicting voting behavior using digital trace data. Social Science Computer Review : SSCORE. https://doi.org/10.1177/0894439319882896
- Bach, R. L. (2018). Unintended behavioral consequences due to repeated measurement. [Doctoral dissertation, Universität Mannheim].
- Bach, R. L. & Eckman, S. (2018). Motivated misreporting in web panels. Journal of Survey Statistics and Methodology : JSSAM, 6(3), 418–430. https://doi.org/10.1093/jssam/smx030
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Projects