Analyzing Incentives and Extracting Valuable Information from Web URLs

Prof. Sebastian Stier, Scientific Director of Computational Social Science at GESIS and Professor of CSS at the University of Mannheim, discusses how web tracking data can inform social science questions.  We discuss the data structure of web browsing data, how it is collected, and the types of incentives used to recruit participants. Prof. Stier also shares his insights and research integrating web browsing data with survey data, as well as how LLMs are opening up new methodological avenues in simulated data.

Here are the resources mentioned in the episode: 

Analysis of Web Browsing Data: A Guide (2023)

Integrating Survey Data and Digital Trace Data: Key Issues in Developing an Emerging Field (2020)

Post Post-Broadcast Democracy? News Exposure in the Age of Online Intermediaries (2022)

The two R packages: webtrackR and adaR