Supplementing and Substituting Survey Data with Big Data

Project Description

For many years, surveys were the standard tool to measure attitudes and behavior for social science research. In recent years, however, researchers have shifted their focus to new sources of data, especially in the online world. For instance, researchers have analyzed the potentials of replacing or supplementing survey data with data from Twitter, smart devices (e.g., smartphones or fitness tracker) and data from other places where people leave digital traces. In this project, we explore the feasibility of using behavioral records of individuals’ online activities to study political attitudes and behavior. Specifically, we explore the potentials of online behavioral data to substitute traditional survey data by inferring attitudes and behavior from the online data. In addition, we analyze how complete such data are as users may switch off data collection during certain activities they do not want recorded. Moreover, we study how (social) media use shapes attitudes and behavior in the offline world. This project is done in collaboration with Ashley Amaya (RTI International).


  • Amaya, A., Bach, R. L., Kreuter, F. und 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).
  • Bach, R. L. und Wenz, A. (2020). Studying health-related internet and mobile device use using web logs and smartphone records. PLOS ONE, 15, e0234663.
  • Bach, R. L., Kern, C., Amaya, A., Keusch, F., Kreuter, F., Hecht, J. und Heinemann, J. (2019). Predicting voting behavior using digital trace data. Social Science Computer Review : SSCORE.
  • Cernat, A. & Keusch, F. (2020). Do surveys change behaviour? Insights from digital trace data. International Journal of Social Research Methodology : IJSRM.