Selected Publications

Articles
Research Papers
Conference Publications
Books
Book Chapters
Dissertation
Encyclopedia Articles
Reports
Reviews
Conference Presentations

Achterhold, E., Mühlböck, M., Steiber, N. and Kern, C. (2025). Fairness in algorithmic profiling: The AMAS case. Minds and Machines, 35, 1–30.
Classe, F., Debelak, R. and Kern, C. (2025). Score-based tests for parameter instability in ordinal factor models. British Journal of Mathematical and Statistical Psychology, 1–29.
Hölzl, J., Keusch, F. and Sajons, C. (2025). The (mis)use of Google Trends data in the social sciences – A systematic review, critique, and recommendations. Social Science Research, 126, 1–22.
Kern, C., Fischer-Abaigar, U., Schweisthal, J., Frauen, D., Ghani, R., Feuerriegel, S., van der Schaar, M. and Kreuter, F. (2025). Algorithms for reliable decision-making need causal reasoning. Nature Computational Science, 5, 356–360.
Leipold, F. M., Kieslich, P. J., Henninger, F., Fernández-Fontelo, A., Greven, S. and Kreuter, F. (2025). Detecting respondent burden in online surveys: How different sources of question difficulty influence cursor movements. Social Science Computer Review : SSCORE, 43, 191–213.
Bach, R. L., Cornesse, C. and Daikeler, J. (2024). Equipping the offline population with internet access in an online panel: Does it make a difference? Journal of Survey Statistics and Methodology : JSSAM, 12, 80–93.
Bach, R. L., Silber, H., Gerdon, F., Keusch, F., Schonlau, M. and Schröder, J. (2024). To share or not to share – understanding individuals’ willingness to share biomarkers, sensor data, and medical records. Information, Communication & Society : ICS, 1–19.
Classe, F. and Kern, C. (2024). Detecting differential item functioning in multidimensional graded response models with recursive partitioning. Applied Psychological Measurement, 48, 83–103.
Classe, F. and Kern, C. (2024). Latent variable forests for latent variable score estimation. Educational and Psychological Measurement : EPM, 84, 1138-1172.
Collins, J. and Kern, C. (2024). Longitudinal nonresponse prediction with time series machine learning. Journal of Survey Statistics and Methodology : JSSAM, 1–32.
Fischer-Abaigar, U., Kern, C., Barda, N. and Kreuter, F. (2024). Bridging the gap: Towards an expanded toolkit for AI-driven decision-making in the public sector. Government Information Quarterly, 41, 1–22.
Gerdon, F. (2024). Attitudes on data use for public benefit: investigating context-specific differences across Germany, Spain, and the United Kingdom with a longitudinal survey experiment. Social Media + Society : SM + S, 10, 1–18.
Kern, C., Bach, R. L., Mautner, H. and Kreuter, F. (2024). When small decisions have big impact: fairness implications of algorithmic profiling schemes. ACM Journal on Responsible Computing, 1, 1–30.
Kern, C., Kim, M. P. and Zhou, A. (2024). Multi-accurate CATE is robust to unknown covariate shifts. Transactions on Machine Learning Research : TMLR, 1–59.
Schenk, P. O. and Kern, C. (2024). Connecting algorithmic fairness to quality dimensions in machine learning in official statistics and survey production. Wirtschafts- und Sozialstatistisches Archiv : AStA, 18, 131–184.
Schwerdtfeger, M. and Bach, R. L. (2024). How does broadband supply affect participation in panel surveys? : Using geospatial broadband data at the district level to analyze mode choice and panel attrition. Quality & Quantity, 58, 5805-5828.
Wenz, A., Keusch, F. and Bach, R. L. (2024). Measuring smartphone use: survey versus digital behavioral data. Social Science Computer Review : SSCORE, 1–20.
Bach, R. L., Kern, C., Mautner, H. and Kreuter, F. (2023). The impact of modeling decisions in statistical profiling. Data & Policy, 5, 1–19.
Fernández-Fontelo, A., Kieslich, P. J., Henninger, F., Kreuter, F. and Greven, S. (2023). Predicting question difficulty in web surveys: A machine learning approach based on mouse movement features. Social Science Computer Review : SSCORE, 41, 141–162.
Kern, C., Weiß, B. and Kolb, J.-P. (2023). Predicting nonresponse in future waves of a probability-based mixed-mode panel with machine learning. Journal of Survey Statistics and Methodology : JSSAM, 11, 100–123.
Keusch, F., Bähr, S., Haas, G.-C., Kreuter, F. and Trappmann, M. (2023). Coverage error in data collection combining mobile surveys with passive measurement using apps: data from a German national survey. Sociological Methods & Research : SMR, 52, 841–878.
Müller, P. and Bach, R. L. (2023). Populist alternative news use and its role for elections: Web-tracking and survey evidence from two campaign periods. New Media & Society, 25, 2664-2683.
Page, E. T., Antoun, C., Gonzalez, J., Kantor, L., Keusch, F., Miller, L. and Wenz, A. (2023). Editorial: Recent advances in survey methods for collecting food data. Survey Methods : Insights from the Field, 2023, 1–8.
Saw, H.-W., Owens, V., Morales, S. A., Rodriguez, N., Kern, C. and Bach, R. L. (2023). Population mental health in Burma after 2021 military coup: online non-probability survey. BJPsych Open, 9, 1–7.
Wenz, A. and Keusch, F. (2023). Increasing the acceptance of smartphone-based data collection. Public Opinion Quarterly : POQ, 87, 357–388.
Wenz, A. and Keusch, F. (2023). The second-level smartphone divide: A typology of smartphone use based on frequency of use, skills, and types of activities. Mobile Media & Communication, 11, 459–483.
Bähr, S., Haas, G.-C., Keusch, F., Kreuter, F. and Trappmann, M. (2022). Missing data and other measurement quality issues in mobile geolocation sensor data. Social Science Computer Review : SSCORE, 40, 212–235.
Cernat, A. and Keusch, F. (2022). Do surveys change behaviour? Insights from digital trace data. International Journal of Social Research Methodology : IJSRM, 25, 79–90.
Daikeler, J., Bach, R. L., Silber, H. and Eckman, S. (2022). Motivated misreporting in smartphone surveys. Social Science Computer Review : SSCORE, 40, 95–107.
Gerdon, F., Bach, R. L., Kern, C. and Kreuter, F. (2022). Social impacts of algorithmic decision-making: A research agenda for the social sciences. Big Data & Society, 9, 1–13.
Haas, G.-C., Keusch, F. and Frölich, M. (2022). Comparing single-sitting versus modular text message surveys in Egypt. International Journal of Public Opinion Research, 34, 1–11.
Kern, C., Gerdon, F., Bach, R. L., Keusch, F. and Kreuter, F. (2022). Humans versus machines: Who is perceived to decide fairer? Experimental evidence on attitudes toward automated decision-making. Patterns, 3, 1–13.
Keusch, F., Bähr, S., Haas, G.-C., Kreuter, F., Trappmann, M. and Eckman, S. (2022). Non-participation in smartphone data collection using research apps. Journal of the Royal Statistical Society. Series A, Statistics in Society, 185, S225-S245.
Keusch, F. and Conrad, F. G. (2022). Using smartphones to capture and combine self-reports and passively measured behavior in social research. Journal of Survey Statistics and Methodology : JSSAM, 10, 863–885.
Keusch, F., Wenz, A. and Conrad, F. G. (2022). Do you have your smartphone with you? Behavioral barriers for measuring everyday activities with smartphone sensors. Computers in Human Behavior, 127.
Kim, M. P., Kern, C., Goldwasser, S., Kreuter, F. and Reingold, O. (2022). Universal adaptability: Target-independent inference that competes with propensity scoring. Proceedings of the National Academy of Sciences of the United States of America : PNAS, 119, 1–6.
Kuppler, M., Kern, C., Bach, R. L. and Kreuter, F. (2022). From fair predictions to just decisions? Conceptualizing algorithmic fairness and distributive justice in the context of data-driven decision-making. Frontiers in Sociology, 7, 1–18.
Nordeck, C. D., Riehm, K. E., Smail, E. J., Holingue, C., Kane, J. C., Johnson, R. M., Veldhuis, C. B., Kalb, L. G., Stuart, E. A., Kreuter, F. and Thrul, J. (2022). Changes in drinking days among United States adults during the COVID-19 pandemic. Addiction, 117, 331–340.
Silber, H., Gerdon, F., Bach, R. L., Kern, C., Keusch, F. and Kreuter, F. (2022). A preregistered vignette experiment on determinants of health data sharing behavior: Willingness to donate sensor data, medical records, and biomarkers. Politics and the Life Sciences : PLS, 41, 161–181.
Sun, H., Conrad, F. G. and Kreuter, F. (2022). The carryover effects of preceding interviewer–respondent interaction on responses in audio computer-assisted self-interviewing (ACASI). Journal of Survey Statistics and Methodology : JSSAM, 10, 299–316.
Achimescu, V. and Chachev, P. D. (2021). Raising the flag: Monitoring user perceived disinformation on reddit. Information, 12, 4.
Achimescu, V., Sultănescu, D. and Sultănescu, D. C. (2021). The path from distrusting Western actors to conspiracy beliefs and noncompliance with public health guidance during the COVID-19 crisis. Journal of Elections, Public Opinion and Parties, 31, 299–310.
Amaya, A., Bach, R. L., Keusch, F. and Kreuter, F. (2021). New data sources in social science research: Things to know before working with Reddit data. Social Science Computer Review : SSCORE, 39, 943–960.
Astley, C. M., Tuli, G., Mc Cord, K. A., Cohn, E. L., Rader, B., Varrelman, T. J., Chiu, S. L., Deng, X., Stewart, K., Farag, T. H., Barkume, K. M., LaRocca, S., Morris, K. A., Kreuter, F. and Brownstein, J. S. (2021). Global monitoring of the impact of the COVID-19 pandemic through online surveys sampled from the Facebook user base. Proceedings of the National Academy of Sciences of the United States of America : PNAS, 118, 1–10.
Bach, R. L., Kern, C., Amaya, A., Keusch, F., Kreuter, F., Hecht, J. and Heinemann, J. (2021). Predicting voting behavior using digital trace data. Social Science Computer Review : SSCOR, 39, 862–883.
Badillo-Goicoechea, E., Chang, T.-H., Kim, E., LaRocca, S., Morris, K., Deng, X., Chiu, S., Bradford, A., Garcia, A., Kern, C., Cobb, C., Kreuter, F. and Stuart, E. A. (2021). Global trends and predictors of face mask usage during the COVID-19 pandemic. BMC Public Health, 21, 1–12.
Bauer, P. C., Gerdon, F., Keusch, F., Kreuter, F. and Vannette, D. L. (2021). Did the GDPR increase trust in data collectors? Evidence from observational and experimental data. Information, Communication & Society : ICS, 25, 2101-2121.
Conrad, F. G., Keusch, F. and Schober, M. (2021). New data in social and behavioral research. Public Opinion Quarterly : POQ, 85, 253–263.
Erlinghagen, M., Kern, C. and Stein, P. (2021). Migration, social stratification and dynamic effects on subjective well being. Advances in Life Course Research, 48, 1–17.
Galesic, M., Bruine de Bruin, W., Dalege, J., Feld, S. L., Kreuter, F., Olsson, H., Prelec, D., Stein, D. L. and Van der Does, T. (2021). Human social sensing is an untapped resource for computational social science. Nature, 2021, 214–222.
Gerdon, F., Nissenbaum, H., Bach, R. L., Kreuter, F. and 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, 1–27.
Gilan, D., Müssig, M., Hahad, O., Kunzler, A., Samstag, S., Röthke, N., Thrul, J., Kreuter, F., Bosnjak, M., Sprengholz, P., Betsch, C., Wollschläger, D., Tüscher, O. and Lieb, K. (2021). Protective and risk factors for mental distress and its impact on health-protective behaviors during the SARS-CoV-2 pandemic between march 2020 and march 2021 in Germany. International Journal of Environmental Research and Public Health : IJERPH, 18, 1–12.
Haensch, A.-C., Herklotz, M., Keusch, F. and Kreuter, F. (2021). The international program in survey and data science (IPSDS): a modern study program for working professionals. Statistical Journal of the IAOS, 37, 921–933.
Kern, C., Höhne, J. K., Schlosser, S. and Revilla, M. (2021). Completion conditions and response behavior in smartphone surveys: A prediction approach using acceleration data. Social Science Computer Review : SSCORE, 39, 1253-1271.
Kern, C., Li, Y. and Wang, L. (2021). Boosted kernel weighting – using statistical learning to improve inference from nonprobability samples. Journal of Survey Statistics and Methodology : JSSAM, 9, 1088-1113.
Keusch, F., Leonard, M. M., Sajons, C. and Steiner, S. (2021). Using smartphone technology for research on refugees: Evidence from Germany. Sociological Methods & Research : SMR, 50, 1863-1894.
Kreuter, F. (2021). What surveys really say. Nature, 600, 614–615.
Pfisterer, F., Kern, C., Dandl, S., Sun, M., Kim, M. P. and Bischl, B. (2021). mcboost: Multi-Calibration Boosting for R. The Journal of Open Source Software : JOSS, 6, Article 3453, 1–3.
Riehm, K. E., Holingue, C., Smail, E. J., Kapteyn, A., Bennett, D., Thrul, J., Kreuter, F., McGinty, E., Kalb, L. G., Veldhuis, C. B., Johnson, R. M., Fallin, M. D. and Stuart, E. A. (2021). Trajectories of mental distress among U.S. adults during the COVID-19 pandemic. Annals of Behavioral Medicine, 55, 93–102.
Sakshaug, J. W., Schmucker, A., Kreuter, F., Couper, M. P. and Holtmann, L. (2021). Respondent understanding of data linkage consent. Survey Methods : Insights from the Field, 2021, 1–15.
Salomon, J. A., Reinhart, A., Bilinski, A., Chua, E. J., La Motte-Kerr, W., Rönn, M. M., Reitsma, M. B., Morris, K. A., LaRocca, S., Farag, T. H., Kreuter, F., Rosenfeld, R. and Tibshirani, R. J. (2021). The US COVID-19 Trends and Impact Survey: continuous real-time measurement of COVID-19 symptoms, risks, protective behaviors, testing, and vaccination. Proceedings of the National Academy of Sciences of the United States of America : PNAS, 118, 1–9.
Sun, H., Conrad, F. G. and Kreuter, F. (2021). The relationship between interviewer-respondent rapport and data quality. Journal of Survey Statistics and Methodology : JSSAM, 9, 429–448.
Altmann, S., Milsom, L., Zillessen, H., Blasone, R., Gerdon, F., Bach, R. L., Kreuter, F., Nosenzo, D., Toussaert, S. and Abeler, J. (2020). Acceptability of app-based contact tracing for COVID-19: Cross-country survey study. JMIR mHealth and uHealth : JMU, 8, e19857.
Bach, R. L., Eckman, S. and Daikeler, J. (2020). Misreporting among reluctant respondents. Journal of Survey Statistics and Methodology : JSSAM, 8, 566–588.
Bach, R. L. and Wenz, A. (2020). Studying health-related internet and mobile device use using web logs and smartphone records. PLOS ONE, 15, e0234663.
Gilan, D., Röthke, N., Blessin, M., Kunzler, A., Stoffers-Winterling, J., Müssig, M., Yuen, K. S. L., Tüscher, O., Thrul, J., Kreuter, F., Sprengholz, P., Betsch, C., Stiglitz, R. D. and Lieb, K. (2020). Psychomorbidity, resilience, and exacerbating and protective factors during the SARS-CoV-2-pandemic'a systematic literature review and results from the German COSMO-Panel. Deutsches Ärzteblatt International, 117, 625–632.
Haas, G.-C., Trappmann, M., Keusch, F., Bähr, S. and Kreuter, F. (2020). Using geofences to collect survey data: Lessons learned from the IAB-SMART study. Survey Methods : Insights from the Field, 2020, 1–12.
Hobusch, G. M., Keusch, F., Tsuchiya, H., Joyce, M. and Windhager, R. (2020). What opinions do tumor reconstructive surgeons have about sports activity after megaprosthetic replacement in hip and knee? Results of the MoReSports expert opinion online survey. Journal of Clinical Medicine, 9, 1–15.
Holingue, C., Badillo-Goicoechea, E., Riehm, K. E., Veldhuis, C. B., Thrul, J., Johnson, R. M., Fallin, M. D., Kreuter, F., Stuart, E. A. and Kalb, L. G. (2020). Mental distress during the COVID-19 pandemic among US adults without a pre-existing mental health condition: Findings from American trend panel survey. Preventive Medicine : PM, 139, 1–8.
Holingue, C., Kalb, L. G., Riehm, K. E., Bennett, D., Kapteyn, A., Veldhuis, C. B., Johnson, R. M., Fallin, M. D., Kreuter, F., Stuart, E. A. and Thrul, J. (2020). Mental distress in the United States at the beginning of the COVID-19 pandemic. American Journal of Public Health : AJPH, 110, 1628-1634.
Kreuter, F., Barkay, N., Bilinski, A., Bradford, A., Chiu, S., Eliat, R., Fan, J., Galili, T., Haimovich, D., Kim, B., LaRocca, S., Li, Y., Morris, K., Presser, S., Salomon, J. A., Sarig, T., Stewart, K., Stuart, E. A. and Tibshirani, R. (2020). Partnering with Facebook on a university-based rapid turn-around global survey. Survey Research Methods : SRM, 14, 159–163.
Oberski, D. L. and Kreuter, F. (2020). Differential privacy and social science: An urgent puzzle. Harvard Data Science Review : HDSR, 2, 1–21.
Riehm, K. E., Holingue, C., Kalb, L. G., Bennett, D., Kapteyn, A., Jiang, Q., Veldhuis, C. B., Johnson, R. M., Fallin, M. D., Kreuter, F., Stuart, E. A. and Thrul, J. (2020). Associations between media exposure and mental distress among U.S. adults at the beginning of the COVID-19 pandemic. American Journal of Preventive Medicine : AJPM, 59, 630–638.
Sakshaug, J. W., Beste, J., Coban, M., Fendel, T., Haas, G.-C., Hülle, S., Kosyakova, Y., König, C., Kreuter, F., Küfner, B., Müller, B., Osiander, C., Schwanhäuser, S., Stephan, G., Vallizadeh, E., Volkert, M., Wenzig, C., Westermeier, C., Zabel, C. and Zins, S. (2020). Impacts of the COVID-19 pandemic on labor market surveys at the German Institute for Employment Research. Survey Research Methods : SRM, 14, 229–233.
Struminskaya, B. and Keusch, F. (2020). Editorial: From web surveys to mobile web to apps, sensors, and digital traces. Survey Methods : Insights from the Field, 2020, 1–7.
Struminskaya, B., Lugtig, P., Keusch, F. and Höhne, J. K. (2020). Augmenting surveys with data from sensors and apps: Opportunities and challenges. Social Science Computer Review : SSCORE, 1–13.

Kern, C., Bach, R. L., Mautner, H. and Kreuter, F. (2021). Fairness in algorithmic profiling: A German case study. Ithaca, NY: Cornell University.
Kuppler, M., Kern, C., Bach, R. L. and Kreuter, F. (2021). Distributive justice and fairness metrics in automated decision-making: How much overlap is there? Ithaca, NY: Cornell University.
Silber, H., Keusch, F., Breuer, J., Siegers, P., Beuthner, C., Stier, S., Gummer, T. and Weiß, B. (2021). Linking surveys and digital trace data: Insights from two studies on determinants of data sharing behavior. SocArXiv Papers. Ithaca, NY: Cornell University.
Badillo-Goicoechea, E., Chang, T.-H., Kim, E., LaRocca, S., Morris, K., Deng, X., Chiu, S., Bradford, A., Garcia, A., Kern, C., Cobb, C., Kreuter, F. and Stuart, E. A. (2020). Global trends and predictors of face mask usage during the COVID-19 pandemic. Ithaca, NY: Cornell University.

Simson, J., Draxler, F., Mehr, S. and Kern, C. (2025). Preventing harmful data practices by using participatory input to navigate the machine learning multiverse. In , Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (S. 1–30). , Association for Computing Machinery: New York, NY, USA.
Jaime, S. and Kern, C. (2024). Ethnic classifications in algorithmic fairness: Concepts, measures and implications in practice. In , FAccT '24, The 2024 ACM Conference on Fairness, Accountability, and Transparency, Rio de Janeiro Brazil, June 3–6, 2024 (S. 237–253). , Association for Computing Machinery: New York, NY.
Kraus, E. and Kern, C. (2024). Measurement modeling of predictors and outcomes in algorithmic fairness. In , Proceedings of the 3rd European Workshop on Algorithmic Fairness (EWAF24) : Mainz, Germany, July 1st to 3rd, 2024 (S. 1–18). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Simson, J., Fabris, A. and Kern, C. (2024). Lazy data practices harm fairness research. In , FAccT '24, The 2024 ACM Conference on Fairness, Accountability, and Transparency, Rio de Janeiro Brazil, June 3–6, 2024 (S. 642–659). , Association for Computing Machinery: New York, NY.
Simson, J., Fabris, A. and Kern, C. (2024). Unveiling the blindspots: Examining availability and usage of protected attributes in fairness datasets. In , Proceedings of the 3rd European Workshop on Algorithmic Fairness (EWAF24) : Mainz, Germany, July 1st to 3rd, 2024 (S. 1–6). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Simson, J., Pfisterer, F. and Kern, C. (2024). One model many scores: Using multiverse analysis to prevent fairness hacking and evaluate the influence of model design decisions. In , FAccT '24, The 2024 ACM Conference on Fairness, Accountability, and Transparency, Rio de Janeiro Brazil, June 3–6, 2024 (S. 1305-1320). , Association for Computing Machinery: New York, NY.
Strasser Ceballos, C. and Kern, C. (2024). Deciding the future of refugees: Rolling the dice or algorithmic location assignment? In , Proceedings of the 3rd European Workshop on Algorithmic Fairness (EWAF24) : Mainz, Germany, July 1st to 3rd, 2024 (S. 1–7). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Jaime, S. and Kern, C. (2023). Ethnic classifications in algorithmic decision-making processes. In , EWAF 2023: European Workshop on Algorithmic Fairness : proceedings of the 2nd European Workshop on Algorithmic Fairness, Winterthur, Switzerland, June 7th to 9th, 2023 (S. 1–5). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Kern, C., Bach, R. L., Mautner, H. and Kreuter, F. (2023). When small decisions have big impact: Fairness implications of algorithmic profiling schemes. In , EWAF 2023: European Workshop on Algorithmic Fairness : proceedings of the 2nd European Workshop on Algorithmic Fairness, Winterthur, Switzerland, June 7th to 9th, 2023 (S. 1–4). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Kern, C., Eckman, S., Beck, J., Chew, R., Ma, B. and Kreuter, F. (2023). Annotation sensitivity: Training data collection methods affect model performance. In , Findings of the Association for Computational Linguistics: EMNLP 2023 (S. 14874-14886). , Association for Computational Linguistics: Singapore.
Kolb, J.-P., Weiß, B. and Kern, C. (2020). Using predictive modelling to identify panel nonresponse. In , Proceeding ISI World Statistics Congress 2019 : Contributed paper session : 18 – 23 August 2019, Kuala Lumpur (S. 206–214). , Department of Statistics Malaysia (DOSM): Putrajaya.

Keusch, F. (2022). How to distinguish between passive and active mobile data collection. London: Sage Publications.
Keusch, F., Struminskaya, B., Hellwig, O., Oglesby, S., Stützer, C. M. and Wachenfeld-Schell, A. (eds.) (2021). 23rd General Online Research Conference : virtual, 08–10 September 2021, proceedings. Köln: Deutsche Gesellschaft für Online-Forschung (DGOF).
Foster, I., Ghani, R., Jarmin, R. S., Kreuter, F. and Lane, J. (eds.) (2021). Big data and social science : data science methods and tools for research and practice. Boca Raton ; London ; New York, NY: CRC Press.
Struminskaya, B., Keusch, F., Hellwig, O., Oglesby, S., Stützer, C. M. and Wachenfeld-Schell, A. (eds.) (2020). 22nd General Online Research Conference : virtual, 10–11 September 2020. Köln: Deutsche Gesellschaft für Online-Forschung (DGOF).
Olson, K., Smyth, J. D., Dykema, J., Holbrook, A. L., Kreuter, F. and West, B. T. (eds.) (2020). Interviewer effects from a total survey error perspective. Boca Raton, FL: CRC Press, Taylor & Francis Group.
Horn, C. and Kreuter, F. (2020). Die digitale Herausforderung : Tipping Points, die Ihr Unternehmen verändern werden. Freiburg ; München ; Stuttgart: Haufe Group.

Kreuter, F., Kern, C. and Schenk, P. O. (2023). Automatisierte Entscheidungen: Aspekte von Fairness, Datenqualität und Privacy. In Künstliche Intelligenz in der Medizin (S. 98–111). Berlin: Berlin-Brandenburgische Akademie der Wissenschaften.
Struminskaya, B. and Keusch, F. (2023). Mobile devices and the collection of social research data. In Research handbook on digital sociology (S. 101–114). Cheltenham ; Northampton, MA: Edward Elgar Publishing.
Keusch, F. and Kreuter, F. (2022). Digital trace data : Modes of data collection, applications, and errors at a glance. In Handbook of computational social science (S. 100–118). London: Routledge, Taylor & Francis Group.
Bach, R. (2021). A methodological framework for the analysis of panel conditioning effects. In Measurement error in longitudinal data (S. 19–41). Oxford ; New York, NY: Oxford University Press.
Malich, S., Keusch, F., Bähr, S., Haas, G.-C., Kreuter, F. and Trappmann, M. (2021). Mobile Datenerhebung in einem Panel Die IAB-SMART Studie. In Sozialwissenschaftliche Datenerhebung im digitalen Zeitalter (S. 45–69). Wiesbaden: Springer VS.
Amaya, A., Bach, R. L., Kreuter, F. and Keusch, F. (2020). Measuring the strength of attitudes in social media data. In Big data meets survey science : a collection of innovative methods (S. 163–192). Hoboken, NJ: John Wiley & Sons.
Brian, K., Kern, C., Scott, M. J., Hunter, C. and Kumar, A. (2020). Workbooks. In Big data and social science : data science methods and tools for research and practice (S. 333–340). Milton ; Boca Raton, FL: CRC Press.
Haas, G.-C., Kreuter, F., Keusch, F., Trappmann, M. and Bähr, S. (2020). Effects of incentives in smartphone data collection. In Big data meets survey science : a collection of innovative methods (S. 387–414). Hoboken, NJ: John Wiley & Sons.
Horwitz, R., Brockhaus, S., Henninger, F., Kieslich, P. J., Schierholz, M., Keusch, F. and Kreuter, F. (2020). Learning from mouse movements: Improving questionnaires and respondents' user experience through passive data collection. In Advances in questionnaire design, development, evaluation, and testing (S. 403–425). Hoboken, NJ: Wiley.
Kern, C. (2020). Machine learning interpretation tools. In SAGE research methods: Foundations (S. 1–12). London: SAGE Publications.
Keusch, F. and Kreuter, F. (2020). Zukunft der Aus- und Weiterbildung in der Markt- und Sozialforschung. In Marktforschung für die Smart Data World : Chancen, Herausforderungen und Grenzen (S. 3–25). Wiesbaden: Springer Gabler.
Keusch, F., Struminskaya, B., Kreuter, F. and Weichbold, M. (2020). Combining active and passive mobile data collection : A survey of concerns. In Big data meets survey science : a collection of innovative methods (S. 657–682). Hoboken, NJ: John Wiley & Sons.
Keusch, F. and Yan, T. (2020). Impact of response scale features on survey responses to behavioral questions. In Experimental methods in survey research : techniques that combine random sampling with random assignment (S. 131–149). New Jersey, NJ: Wiley.
Kreuter, F., Eckman, S. and Tourangeau, R. (2020). The salience of survey burden and its effects on response behavior to skip questions: Experimental results from telephone and web-surveys. In Advances in questionnaire design, development, evaluation, and testing (S. 213–227). Hoboken, NJ: Wiley.
Olson, K., Smyth, J. D., Dykema, J., Holbrook, A. L., Kreuter, F. and West, B. T. (2020). The past, present, and future of research on interviewer effects. In Interviewer effects from a total survey error perspective (S. 3–16). Boca Raton, FL: Chapman and Hall/CRC Press.
Samoilova, E., Wolbring, T. and Keusch, F. (2020). Datenqualität umfragebasierter Workload-Messungen: Eine Mixed-Methods-Studie auf Grundlage von Learning Analytics und kognitiven Interviews. In Studentischer Workload (S. 205–229). Wiesbaden: Springer Fachmedien Wiesbaden.
Schwanhäuser, S., Sakshaug, J. W., Kosyakova, Y. and Kreuter, F. (2020). Statistical identification of fraudulent interviews in surveys: Improving interviewer controls. In Interviewer effects from a total survey error perspective (S. 91–106). Boca Raton: Chapman and Hall/CRC.
West, B. T., Yan, T., Kreuter, F., Josten, M. and Schroeder, H. (2020). Examining the utility of interviewer observations on the survey response process. In Interviewer effects from a total survey error perspective (S. 107–120). Boca Raton: Chapman and Hall/CRC.

Gerdon, F. (2024). Challenges of data-driven technologies for social inequality and privacy: empirical research on context and public perceptions. Dissertation. Mannheim.
Achimescu, V. (2022). Measuring online perceptions and offline consequences of misinformation, disinformation, and computational propaganda. Dissertation. Mannheim.
Haas, G. (2021). Modernization of data collection methods. Dissertation. Mannheim.
Haensch, A. (2021). Dealing with various flavors of missing data in ex-post survey harmonization and beyond. Dissertation. Mannheim.
Leonard, M. (2020). Honor violence, Crimes d'honneur, Ehrenmorde: Improving the identification, risk assessment, and estimation of honor crimes internationally. Dissertation. Mannheim.

Keusch, F. (2020). Gamification in web surveys. In , SAGE research methods foundations (S. 1–8). London: Sage.

Brinkmann, M. M., Gerdon, F. and Kühne, S. (2023). Diskriminierungswahrnehmung und Herkunftsregion : eine Befragung von Menschen mit vielfältigen Migrationsgeschichten.
Hänsch, A. (2020). IPSDS in times of Corona.

Bach, R. (2024). Applied statistical learning — With case studies in Stata by Matthias Schonlau, Springer, 2023, 332pp, €128.39 (Hardback), ISBN: 978-3-031-33389-7. Review, Journal of the Royal Statistical Society. Series A, Statistics in Society

Gerdon, F. (2025). Integrating contextual integrity into cross-country comparative research on acceptance of data uses. 7th Annual PrivaCI Symposium, Brussel, Belgium.
Gerdon, F. (2024). How are public preferences relevant to the ethical use of AI? Theoretical considerations and empirical findings. 15. Wissenschaftliche Tagung des ADM, der ASI und des Statistischen Bundesamtes, “Datenerhebung, Datenqualität und Datenethik in Zeiten von künstlicher Intelligenz”, Wiesbaden, Germany.
Gerdon, F., Bach, R. L., Kern, C. and Kreuter, F. (2024). Research avenues for studying effects of algorithmic decision-making systems on social inequality. Digital Inequalities Symposium for Early-Career Researchers, Paris, France.
Gerdon, F., Szafran, D., Kappenberger, J., Bach, R. L. and Kern, C. (2023). Using survey experiments and agent-based modeling to simulate mobility behavior in smart cities. European Survey Research Association (ESRA) Conference 2023, Milano, Italy.
Gerdon, F., von der Heyde, L. and Kreuter, F. (2023). Using survey experiments to longitudinally study privacy as contextual integrity. European Survey Research Association (ESRA) Conference 2023, Milano, Italy.
Kern, C., Gerdon, F., Bach, R. L., Keusch, F. and Kreuter, F. (2023). Humans vs. Machines: Who is Perceived to Decide Fairer? An Experiment about Citizens’ Attitudes. Hybrid Human-Artificial Intelligence (HHAI) 2023, München, Germany.
Wenz, A. and Keusch, F. (2022). The second-level smartphone divide: A typology of smartphone usage based on frequency of use, skills, and types of activities. 72nd Annual ICA Media Sociology Hybrid Post-Conference, Paris, France, Hybrid.
Bähr, S., Haas, G.-C., Keusch, F., Kreuter, F. and Trappmann, M. (2021). Social networks on smartphones. Congruency of online and offline networks and their effect on labor market outcomes. International Conference What People Leave Behind: Marks, Traces, Footprints and their Significance for Social Sciences, Online.
Bähr, S., Keusch, F., Haas, G.-C., Kreuter, F. and Trappmann, M. (2021). Social networks on smartphones. Congruence of online and offline networks and their effect on labor market outcomes. 2nd Mobile Apps and Sensors in Surveys (MASS) Workshop 2021, Online.
Gerdon, F., Kern, C., Bach, R. L., Theil, C. K., Kreuter, F., Stuckenschmidt, H. and Eckert, K. (2021). From bias to impact: How can algorithmic decision-making affect social inequality? DigiMeet 2021, Digitalisation Research and Network Meeting, Online.
Gerdon, F., Nissenbaum, H., Bach, R. L., Kreuter, F. and Zins, S. (2021). Pandemic effects on privacy attitudes : Changes in acceptance of using health data for private and public benefit. Annual Symposium on Applications of Contextual Integrity (03. : 2021), Chicago, IL.
Gerdon, F., Nissenbaum, H., Bach, R. L., Kreuter, F. and Zins, S. (2021). Privacy attitudes in times of crisis: Acceptance of data sharing for public health. AAPOR 76th Annual Conference, Online.
Gerdon, F., Nissenbaum, H., Bach, R. L., Kreuter, F. and Zins, S. (2021). Privacy attitudes in times of crisis: Acceptance of data sharing for public health? Joint Statistical Meetings 2021, Online.
Kapousouz, E., Beuthner, C., Keusch, F., Silber, H., Weiß, B. and Johnson, T. P. (2021). Validation of survey-based health indicators through health app data. AAPOR 76th Annual Conference, American Association for Public Opinion Research, Online.
Keusch, F. (2021). Data collection using smartphones: Concerns about data sharing and framing effects. JSM 2021, Joint Statistical Meetings Conference, Online.
Keusch, F., Wenz, A. and Conrad, F. G. (2021). Measuring everyday behavior with smartphone sensors: Potential bias due to device usage. AAPOR 76th Annual Conference, American Association for Public Opinion Research, Online.
Malich, S., Bähr, S., Haas, G.-C., Keusch, F., Kreuter, F. and Trappmann, M. (2021). Auswertung von Smartphone-Daten für die Sozialforschung. Gemeinsamer Kongress der Deutschen Gesellschaft für Soziologie (DGS) und der Österreichischen Gesellschaft für Soziologie (ÖGS) – Die Post-Corona-Gesellschaft? Pandemie, Krise und ihre Folgen, Wien, Austria, Online.
Silber, H., Gerdon, F., Bach, R. L., Kern, C., Keusch, F. and Kreuter, F. (2021). A vignette experiment on determinants of health data sharing behavior: Willingness to donate sensor data, medical records, and biomarkers. Science and Politics: Changing Attitudes and Emerging Methodologies, Online.
Struminskaya, B. and Keusch, F. (2021). Concerns about privacy when sharing data collected using smartphones. AAPOR 76th Annual Conference, American Association for Public Opinion Research, Online.
Struminskaya, B. and Keusch, F. (2021). The role of technological skills and privacy concerns in willingness to share smartphone sensor data. 2nd Mobile Apps and Sensors in Surveys (MASS) Workshop 2021, Online.
Wenz, A. and Keusch, F. (2021). The smartphone usage divide: Differences in people's smartphone behavior and implications for mobile data collection. AAPOR 76th Annual Conference, American Association for Public Opinion Research, Online.
Bähr, S., Haas, G.-C., Keusch, F., Kreuter, F. and Trappmann, M. (2020). Social networks on smartphones – Congruency of online and offline networks and their effect on labor market outcomes. 32nd Annual SASE Meeting 2020, Society for the Advancement of Socio-Economics, Online.
Cernat, A. and Keusch, F. (2020). Do surveys change behavior? Insights from digital trace data. IC2S2 2020, 6th International Conference on Computational Social Science, Cambridge, MA, Online.
Gerdon, F. (2020). Data sharing for the public good? A factorial survey experiment on contextual privacy norms. 22. General Online Research Konferenz GOR 2020, Online.
Gerdon, F., Theil, C. K., Kern, C., Bach, R. L., Kreuter, F., Stuckenschmidt, H. and Eckert, K. (2020). Exploring impacts of artificial intelligence on urban societies with social simulations. 40. Kongress der Deutschen Gesellschaft für Soziologie, Online.
Haas, G.-C., Trappmann, M., Keusch, F., Bähr, S. and Kreuter, F. (2020). Using geofences to trigger surveys in an app. GOR 2020, 22nd General Online Research Conference, Online.
Kapousouz, E., Beuthner, C., Keusch, F., Silber, H., Weiß, B. and Johnson, T. P. (2020). The combination of survey and health app data: Sharing behavior, quality assessment, and validation of survey-based health indicators. BigSurv20, Big Data Meets Survey Science, Online.
Keusch, F., Bach, R. L. and Cernat, A. (2020). Social desirability in digital trace data collection. BigSurv20, Big Data Meets Survey Science, Online.
Keusch, F., Bähr, S., Haas, G.-C., Kreuter, F. and Trappmann, M. (2020). Combining self-reports with passive mobile data collection: New forms of data collection lead to new forms of nonresponse. International Workshop on Household Survey Nonresponse, Online.
Keusch, F., Bähr, S., Haas, G.-C., Kreuter, F. and Trappmann, M. (2020). Participation rates and bias in a smartphone study collecting self-reports and passive mobile measurement using a research app. AAPOR 75th Annual Conference, American Association for Opinion Public Research, Online.
Keusch, F., Kreuter, F., Haas, G.-C., Trappmann, M. and Bähr, S. (2020). Social networks on smartphones. Congruence of online and offline networks and their effect on labor market outcomes. IC2S2 2020, 6th International Conference on Computational Social Science, Cambridge, MA, Online.
Silber, H., Breuer, J., Beuthner, C., Siegers, P., Weiß, B., Stier, S., Keusch, F. and Gummer, T. (2020). Linking surveys and digital trace data: Experiences from two pilot studies on factors influencing informed consent. BigSurv20, Big Data Meets Survey Science, Online.

Selected Publications

Professorship for Social Data Science and Methodology

FORUM