Linking surveys and digital trace data: Insights from two studies on determinants of data sharing behavior


Silber, Henning ; Keusch, Florian ; Breuer, Johannes ; Siegers, Pascal ; Beuthner, Christoph ; Stier, Sebastian ; Gummer, Tobias ; Weiss, Bernd


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DOI: https://doi.org/10.31235/osf.io/dz93u
URL: https://madoc.bib.uni-mannheim.de/58906
Additional URL: https://osf.io/preprints/socarxiv/dz93u/
URN: urn:nbn:de:bsz:180-madoc-589069
Document Type: Working paper
Year of publication: 2021
The title of a journal, publication series: SocArXiv Papers
Place of publication: Ithaca, NY
Publishing house: Cornell University
Publication language: English
Institution: School of Social Sciences > Statistik u. Sozialwiss. Methodenlehre (Juniorprofessur) (Keusch 2016-)
Pre-existing license: Creative Commons Attribution 4.0 International (CC BY 4.0)
Subject: 300 Social sciences, sociology, anthropology
310 Statistics
Abstract: Combining surveys and digital trace data can enhance the analytic potential of both data types. We present two studies on factors influencing data sharing behavior for different types of digital trace data: Facebook, Twitter, Spotify, and health app data. Across those data types, we compare the relative impact of five factors on data sharing: data type, data sharing method, respondent characteristics, sample composition, and incentives. The results show large differences between the data types and sharing methods, especially related to task difficulty and respondent burden. Higher incentives generally increase data sharing rates, whereas the influence of respondent characteristics depends on the respective data types.

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Das Dokument wird vom Publikationsserver der Universitätsbibliothek Mannheim bereitgestellt.




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