Linking Surveys and Digital Trace Data: Insights From two Studies on Determinants of Data Sharing Behaviour

Author:

Silber Henning1,Breuer Johannes,Beuthner Christoph1,Gummer Tobias,Keusch Florian2,Siegers Pascal3,Stier Sebastian3,Weiß Bernd1

Affiliation:

1. GESIS – Leibniz Institute for the Social Sciences , Mannheim , Germany

2. University of Mannheim , Mannheim , Germany

3. GESIS - Leibniz Institute for the Social Sciences , Cologne , Germany

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.

Publisher

Oxford University Press (OUP)

Subject

Statistics, Probability and Uncertainty,Economics and Econometrics,Social Sciences (miscellaneous),Statistics and Probability

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