Linking Surveys and Digital Trace Data: Insights From two Studies on Determinants of Data Sharing Behaviour. (9th November 2022)

• Record Type: Journal Article
• Authors: Silber, Henning; Breuer, Johannes; Beuthner, Christoph; Gummer, Tobias; Keusch, Florian; Siegers, Pascal; Stier, Sebastian; Weiß, Bernd
• Is Part Of: Journal of the Royal Statistical Society. Volume 185(2022)Supplement 2
• Page Start: S387
• Page End: S407
• Publication Date: 2022-11-09
• Subjects: consent -- data donation -- data linkage -- data sharing rates -- incentives -- social network sites; Social sciences -- Statistical methods -- Periodicals; Statistics -- Periodicals; 300.15195
• DOI: 10.1111/rssa.12954
• Languages: English
• ISSNs: 0964-1998

Abstract

Abstract: Combining surveys and digital trace data can enhance the analytic potential of both data types. We present two studies that examine factors influencing data sharing behaviour of survey respondents for different types of digital trace data: Facebook, Twitter, Spotify and health app data. Across those data types, we compared the relative impact of four factors on data sharing: data sharing method, respondent characteristics, sample composition and incentives. The results show that data sharing rates differ substantially across data types. Two particularly important factors predicting data sharing behaviour are the incentive size and data sharing method, which are both directly related to task difficulty and respondent burden. In sum, the paper reveals systematic variation in the willingness to share additional data which need to be considered in research designs linking surveys and digital traces.