Twitter Misinformation Labels vs. Scientist’s Fact-Checking Responses? Evaluating the Strategies Debunking Misinformation About COVID-19 on Twitter

Jiemin Looi*, Won-ki Moon, Patrick Jamar, Nichole Bennett, Anthony Dudo

*Corresponding author for this work

Research output: Contribution to conferenceConference paperpeer-review

Abstract

Utilizing the source credibility framework and MAIN model, this study examined how non-content credibility indicators affected individuals’ beliefs and behavioral intentions about COVID-19 on Twitter. Using quota sampling, 310 participants participated in a 3 (misinformation source: politician vs. journalist vs. ordinary user) X 2 (fact-checking source: Twitter vs. scientist) between-subjects factorial experiment. Misinformation from journalists enhanced participants’ belief in misinformation the most. Meanwhile, misinformation from politicians enhanced participants’ intention to share misinformation the most. Notably, scientists enhanced participants’ beliefs and intentions to share fact-checking responses more than Twitter misinformation warning labels. Theoretical contributions, practical implications, and future research are discussed.

Conference

Conference71st Annual International Communication Association Conference, ICA 2021
Period27/05/2131/05/21
Internet address

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