Social Media, Sentiment and Public Opinions: Evidence from #Brexit and #USElection

Yuriy Gorodnichenko, Tho Pham and Oleksandr Talavera (oleksandr.talavera@gmail.com)

No 24631, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: This paper studies information diffusion in social media and the role of bots in shaping public opinions. Using Twitter data on the 2016 E.U. Referendum (“Brexit”) and the 2016 U.S. Presidential Election, we find that diffusion of information on Twitter is largely complete within 1-2 hours. Stronger interactions across agents with similar beliefs are consistent with the “echo chambers” view of social media. Bots have a tangible effect on the tweeting activity of humans but the degree of bots’ influence depends on whether bots provide information consistent with humans’ priors. Overall, our results suggest that the aggressive use of Twitter bots, coupled with the fragmentation of social media and the role of sentiment, could contribute to the vote outcomes.

JEL-codes: D72 D83 D84 (search for similar items in EconPapers)
Date: 2018-05
New Economics Papers: this item is included in nep-cdm, nep-pol and nep-soc
Note: PE POL
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Citations: View citations in EconPapers (14)

Published as Gorodnichenko, Yuriy & Pham, Tho & Talavera, Oleksandr, 2021. "Social media, sentiment and public opinions: Evidence from #Brexit and #USElection," European Economic Review, Elsevier, vol. 136(C).

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Related works:
Journal Article: Social media, sentiment and public opinions: Evidence from #Brexit and #USElection (2021)
Working Paper: Social media, sentiment and public opinions: Evidence from #Brexit and #USElection (2018)
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