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Antecedents Driving the Intention to Share Unverified COVID-19 Information on Social Media

Antecedents Driving the Intention to Share Unverified COVID-19 Information on Social Media

Thong Bing Tai, Tze Wei Liew, Su-Mae Tan, Mohammad Tariqul Islam Khan
Copyright: © 2022 |Pages: 27
ISBN13: 9781799882350|ISBN10: 1799882357|ISBN13 Softcover: 9781799882367|EISBN13: 9781799882374
DOI: 10.4018/978-1-7998-8235-0.ch002
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MLA

Tai, Thong Bing, et al. "Antecedents Driving the Intention to Share Unverified COVID-19 Information on Social Media." Information Manipulation and Its Impact Across All Industries, edited by Maryam Ebrahimi, IGI Global, 2022, pp. 19-45. https://doi.org/10.4018/978-1-7998-8235-0.ch002

APA

Tai, T. B., Liew, T. W., Tan, S., & Khan, M. T. (2022). Antecedents Driving the Intention to Share Unverified COVID-19 Information on Social Media. In M. Ebrahimi (Ed.), Information Manipulation and Its Impact Across All Industries (pp. 19-45). IGI Global. https://doi.org/10.4018/978-1-7998-8235-0.ch002

Chicago

Tai, Thong Bing, et al. "Antecedents Driving the Intention to Share Unverified COVID-19 Information on Social Media." In Information Manipulation and Its Impact Across All Industries, edited by Maryam Ebrahimi, 19-45. Hershey, PA: IGI Global, 2022. https://doi.org/10.4018/978-1-7998-8235-0.ch002

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Abstract

Infodemic refers to the influx of inaccurate or deceptive information on social media during a pandemic. The sharing of unverified COVID-19 information on social media is pervasive in Malaysia, which leads to adverse consequences stemming from misinformation, disinformation, and mal-information. Drawing upon the cognitive load theory (CLT) and self-determination theory (SDT), this research examined the antecedents driving unverified COVID-19 information sharing on social media in Malaysia. Based on 309 validated online survey responses, the PLS-SEM analysis revealed that except for trust towards online information; the proposed factors, self-disclosure, information overload, entertainment, and fear of missing out (FoMo), were found to predict the intention to share unverified COVID-19 information sharing on social media in Malaysia. Theoretical implications are discussed through CLT and SDT, and practical recommendations for government agencies, social media administrators, and public members to curb unverified COVID-19 information sharing on social media in Malaysia are offered.

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