TY - JOUR
T1 - How Accurate Are Survey Responses on Social Media and Politics?
AU - Guess, Andrew
AU - Munger, Kevin
AU - Nagler, Jonathan
AU - Tucker, Joshua
N1 - Funding Information:
This study has been approved by the New York University Institutional Review Board (IRB-12-9058, IRB-FY2017-150). We are grateful to Samantha Luks at YouGov for facilitating survey data collection, Yvan Scher for research assistance, and Jona Ronen for development and technical assistance. Thanks to Rachel Gibson, workshop participants at the University of Manchester, the editors of this special issue, and to three anonymous reviewers for their helpful comments and feedback. This research was supported by the INSPIRE program of the National Science Foundation (Award SES-1248077).
Publisher Copyright:
© 2018, Copyright © 2018 Taylor & Francis Group, LLC.
PY - 2019/4/3
Y1 - 2019/4/3
N2 - How accurate are survey-based measures of social media use, in particular about political topics? We answer this question by linking original survey data collected during the U.S. 2016 election campaign with respondents’ observed social media activity. We use supervised machine learning to classify whether these Twitter and Facebook account data are content related to politics. We then benchmark our survey measures on frequency of posting about politics and the number of political figures followed. We find that, on average, our self-reported survey measures tend to correlate with observed social media activity. At the same time, we also find a worrying amount of individual-level discrepancy and problems related to extreme outliers. Our recommendations are twofold. The first is for survey questions about social media use to provide respondents with options covering a wider range of activity, especially in the long tail. The second is for survey questions to include specific content and anchors defining what it means for a post to be “about politics.”.
AB - How accurate are survey-based measures of social media use, in particular about political topics? We answer this question by linking original survey data collected during the U.S. 2016 election campaign with respondents’ observed social media activity. We use supervised machine learning to classify whether these Twitter and Facebook account data are content related to politics. We then benchmark our survey measures on frequency of posting about politics and the number of political figures followed. We find that, on average, our self-reported survey measures tend to correlate with observed social media activity. At the same time, we also find a worrying amount of individual-level discrepancy and problems related to extreme outliers. Our recommendations are twofold. The first is for survey questions about social media use to provide respondents with options covering a wider range of activity, especially in the long tail. The second is for survey questions to include specific content and anchors defining what it means for a post to be “about politics.”.
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U2 - 10.1080/10584609.2018.1504840
DO - 10.1080/10584609.2018.1504840
M3 - Article
AN - SCOPUS:85056107175
SN - 1058-4609
VL - 36
SP - 241
EP - 258
JO - Political Communication
JF - Political Communication
IS - 2
ER -