Given the amount of misinformation being circulated on social media during the COVID-19 pandemic and its potential threat to public health, it is imperative to investigate ways to hinder its transmission. To this end, this study aimed to identify message features that may contribute to misinformation sharing on social media. Based on the theory of social sharing of emotion and the extant research on message credibility, this study examined if emotions and message credibility serve as mechanisms through which novelty and efficacy of misinformation influence sharing intention. An online experiment concerning COVID-19 misinformation was conducted by employing a 2 (novelty conditions: high vs. low) × 2 (efficacy conditions: high vs. low) between-subjects design using a national quota sample in South Korea (N = 1,012). The findings suggested that, contrary to the expectation, the overall effects of novelty on sharing intention were negative. The specific mechanisms played significant and unique roles in different directions: novelty increased sharing intention by evoking surprise, while also exerting a negative influence on sharing intention through an increase in negative emotions and a decrease in positive emotions and message credibility. Consistent with the expectation, efficacy exhibited positive total effects on sharing intention, which was explained by higher levels of (self- and response-) efficacy of protective action increasing positive emotions and message credibility but decreasing negative emotions. The implications and limitations of the study are discussed.
|Journal||Computers in Human Behavior|
|Publication status||Published - 2023 Jan|
Bibliographical noteFunding Information:
This work was supported by the Technology Innovation Program (or Industrial Strategic Technology Development Program-Source Technology Development and Commercialization of Digital Therapeutics) ( 20014967 , Development of Digital Therapeutics for Depression from COVID19) funded By the Ministry of Trade, Industry & Energy (MOTIE, Korea) , and also partially by Inha University Research Grant.
© 2022 Elsevier Ltd
All Science Journal Classification (ASJC) codes
- Arts and Humanities (miscellaneous)
- Human-Computer Interaction