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

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

Department of Communication Studies

Research output: Contribution to conference › Conference paper › peer-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.

Original language	English
Publication status	Published - 27 May 2021
Event	71st Annual International Communication Association Conference, ICA 2021 - Virtual Duration: 27 May 2021 → 31 May 2021 https://cdn.ymaws.com/www.icahdq.org/resource/resmgr/conference/2021/2021-printprogram.pdf (Conference program)

Conference

Conference	71st Annual International Communication Association Conference, ICA 2021
Period	27/05/21 → 31/05/21
Other	Engaging the Essential Work of Care: Communication, Connectedness, and Social Justice
Internet address	https://cdn.ymaws.com/www.icahdq.org/resource/resmgr/conference/2021/2021-printprogram.pdf (Conference program)

Cite this

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title = "Twitter Misinformation Labels vs. Scientist{\textquoteright}s Fact-Checking Responses?: Evaluating the Strategies Debunking Misinformation About COVID-19 on Twitter",

abstract = "Utilizing the source credibility framework and MAIN model, this study examined how non-content credibility indicators affected individuals{\textquoteright} 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{\textquoteright} belief in misinformation the most. Meanwhile, misinformation from politicians enhanced participants{\textquoteright} intention to share misinformation the most. Notably, scientists enhanced participants{\textquoteright} beliefs and intentions to share fact-checking responses more than Twitter misinformation warning labels. Theoretical contributions, practical implications, and future research are discussed.",

author = "Jiemin Looi and Won-ki Moon and Patrick Jamar and Nichole Bennett and Anthony Dudo",

year = "2021",

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day = "27",

language = "English",

note = "71st Annual International Communication Association Conference, ICA 2021 ; Conference date: 27-05-2021 Through 31-05-2021",

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}

Twitter Misinformation Labels vs. Scientist’s Fact-Checking Responses? Evaluating the Strategies Debunking Misinformation About COVID-19 on Twitter. / Looi, Jiemin; Moon, Won-ki; Jamar, Patrick et al.
2021. Paper presented at 71st Annual International Communication Association Conference, ICA 2021.

Research output: Contribution to conference › Conference paper › peer-review

TY - CONF

T1 - Twitter Misinformation Labels vs. Scientist’s Fact-Checking Responses?

T2 - 71st Annual International Communication Association Conference, ICA 2021

AU - Looi, Jiemin

AU - Moon, Won-ki

AU - Jamar, Patrick

AU - Bennett, Nichole

AU - Dudo, Anthony

PY - 2021/5/27

Y1 - 2021/5/27

N2 - 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.

AB - 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.

M3 - Conference paper

Y2 - 27 May 2021 through 31 May 2021

ER -

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

Abstract

Conference

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