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Linking Surveys and Digital Trace Data: Insights From two Studies on Determinants of Data Sharing Behaviour
[journal article]
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... view more
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.... view less
Keywords
survey; social media; data; twitter; data exchange; survey research; data capture; digital media; facebook
Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Free Keywords
consent; data donation; data linkage; data sharing rates; incentives; social network sites
Document language
English
Publication Year
2022
Page/Pages
S387-S407
Journal
Journal of the Royal Statistical Society, Series A (Statistics in Society), 185 (2022) Suppl. 2
DOI
https://doi.org/10.1111/rssa.12954
ISSN
1467-985X
Status
Published Version; peer reviewed
Licence
Creative Commons - Attribution-NonCommercial 4.0
FundingGefördert durch die Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 491156185 / Funded by the German Research Foundation (DFG) - Project number 491156185