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

Authors :
Sebastian Stier
Christoph Beuthner
Henning Silber
Johannes Breuer
Tobias Gummer
Florian Keusch
Pascal Siegers
Bernd Weiss
Source :
Journal of the Royal Statistical Society, Series A (Statistics in Society), Suppl. 2, S387-S407
Publication Year :
2022
Publisher :
Oxford University Press (OUP), 2022.

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.

Details

ISSN :
1467985X and 09641998
Volume :
185
Database :
OpenAIRE
Journal :
Journal of the Royal Statistical Society Series A: Statistics in Society
Accession number :
edsair.doi.dedup.....ffcd0a99af6d90c8b58cc9f7102283e8