Clemm von Hohenberg, B., Stier, S., Cardenal, A. S., Guess, A. M., Menchen-Trevino, E., & Wojcieszak, M. (2024). Analysis of Web Browsing Data: A Guide. Social Science Computer Review, 0 (0). https://doi.org/10.1177/08944393241227868
The use of individual-level browsing data, that is, the records of a person’s visits to online content through a desktop or mobile browser, is of increasing importance for social scientists. Browsing data have characteristics that raise many questions for statistical analysis, yet to date, little hands-on guidance on how to handle them exists.
Reviewing extant research, and exploring data sets collected by four research teams spanning seven countries and several years, with over 14,000 participants and 360 million web visits, the authors derive recommendations along four steps:
- preprocessing the raw data;
- filtering out observations;
- classifying web visits; and
- modelling browsing behavior.