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Using data from reddit, public deliberation, and surveys to measure public opinion about autonomous vehicles.
- Source :
- Public Opinion Quarterly; 2021 Supplement, Vol. 85, p289-322, 34p, 12 Charts, 2 Graphs
- Publication Year :
- 2021
-
Abstract
- When and how can researchers synthesize survey data with analyses of social media content to study public opinion, and when and how can social media data complement surveys to better inform researchers and policymakers? This paper explores how public opinions might differ between survey and social media platforms in terms of content and audience, focusing on the test case of opinions about autonomous vehicles. The paper first extends previous overviews comparing surveys and social media as measurement tools to include a broader range of survey types, including surveys that result from public deliberation, considering the dialogic characteristics of different social media, and the range of issue publics and marginalized voices that different surveys and social media forums can attract. It then compares findings and implications from analyses of public opinion about autonomous vehicles from traditional surveys, results of public deliberation, and analyses of Reddit posts, applying a newly developed computational text analysis tool. Findings demonstrate that social media analyses can both help researchers learn more about issues that are uncovered by surveys and also uncover opinions from subpopulations with specialized knowledge and unique orientations toward a subject. In light of these findings, we point to future directions on how researchers and policymakers can synthesize survey and social media data, and the corresponding data integration techniques, to study public opinion. [ABSTRACT FROM AUTHOR]
- Subjects :
- PUBLIC opinion
AUTONOMOUS vehicles
SOCIAL media
SURVEYS
Subjects
Details
- Language :
- English
- ISSN :
- 0033362X
- Volume :
- 85
- Database :
- Complementary Index
- Journal :
- Public Opinion Quarterly
- Publication Type :
- Academic Journal
- Accession number :
- 152743639
- Full Text :
- https://doi.org/10.1093/poq/nfab021