Linking Twitter and Survey Data: The Impact of Survey Mode and Demographics on Consent Rates Across Three UK Studies. (October 2020)

• Record Type: Journal Article
• Authors: Al Baghal, Tarek; Sloan, Luke; Jessop, Curtis; Williams, Matthew L.; Burnap, Pete
• Other Names: Stier Sebastian guest-editor.; Siegers Pascal guest-editor.; Breuer Johannes guest-editor.; Thorson Kjerstin guest-editor.
• Is Part Of: Social science computer review. Volume 38:Number 5(2020)
• Page Start: 517
• Page End: 532
• Publication Date: 2020-10
• Subjects: Twitter -- surveys -- consent -- linkage -- mode effects; Social sciences -- Data processing -- Periodicals; Computers -- Social aspects -- Periodicals; Microcomputers -- Periodicals; Sciences sociales -- Informatique -- Périodiques; Micro-ordinateurs -- Périodiques; 300.285
• DOI: 10.1177/0894439319828011
• Languages: English
• ISSNs: 0894-4393

Abstract

In light of issues such as increasing unit nonresponse in surveys, several studies argue that social media sources such as Twitter can be used as a viable alternative. However, there are also a number of shortcomings with Twitter data such as questions about its representativeness of the wider population and the inability to validate whose data you are collecting. A useful way forward could be to combine survey and Twitter data to supplement and improve both. To do so, consent within a survey is first needed. This study explores the consent decisions in three large representative surveys of the adult British population to link Twitter data to survey responses and the impact that demographics and survey mode have on these outcomes. Findings suggest that consent rates for data linkage are relatively low, and this is in part mediated by mode, where face-to-face surveys have higher consent rates than web versions. These findings are important to understand the potential for linking Twitter and survey data but also to the consent literature generally.