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1 – 2 of 2Chen Luo, Yijia Zhu and Anfan Chen
Drawing upon the third-person effect (TPE) theory, this study focuses on two types of misinformation countering intentions (i.e. simple correction and correction with…
Abstract
Purpose
Drawing upon the third-person effect (TPE) theory, this study focuses on two types of misinformation countering intentions (i.e. simple correction and correction with justification). Accordingly, it aims to (1) assess the tenability of the third-person perception (TPP) in the face of misinformation on social media, (2) explore the antecedents of TPP and its relationship with individual-level misinformation countering intentions and (3) examine whether the mediating process is contingent on different social media usage conditions.
Design/methodology/approach
An online survey was conducted with 1,000 representative respondents recruited in Mainland China in January 2022 using quota sampling. Paired t-test, multiple linear regression and moderated mediation analysis were employed to examine the proposed hypotheses.
Findings
Results bolster the fundamental proposition of TPP that individuals perceive others as more susceptible to social media misinformation than they are. The self-other perceptual bias served as a mediator between the perceived consequence of misinformation and misinformation countering (i.e. simple correction and correction with justification) intentions. Furthermore, intensive social media users were likely to be motivated to counter social media misinformation derived from the indirect mechanism.
Originality/value
The findings provide further evidence for the role of TPE in explaining misinformation countering intention as prosocial and altruistic behavior rather than self-serving behavior. Practically, promising ways to combat rampant misinformation on social media include promoting the prosocial aspects and beneficial outcomes of misinformation countering efforts to others, as well as reconfiguring the strategies by impelling intensive social media users to participate in enacting countering actions
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2022-0507.
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Keywords
Anfan Chen, Zhuo Chen and Aaron Yikai Ng
This study examines the role of crowd wisdom in misinformation correction. Going beyond fact-checking, we investigate the mechanisms underlying laypeople’s participation in…
Abstract
Purpose
This study examines the role of crowd wisdom in misinformation correction. Going beyond fact-checking, we investigate the mechanisms underlying laypeople’s participation in misinformation correction. Drawing upon the Norm Activation Model (NAM), this study conceptualizes misinformation correction as a prosocial behavior and examines the impact of various media and social psychological factors on laypeople’s motivations to engage misinformation correction behavior.
Design/methodology/approach
Through a national survey of 1,022 respondents, we explore the norm activation process triggered by the perceived prevalence of online misinformation, which directly and indirectly impacts online misinformation correction intentions via awareness, norms, and efficacy. This mechanism was tested using structural equation modeling.
Findings
This study found that perceived prevalence of misinformation, self-efficacy, and outcome efficacy play multilayered roles in shaping misinformation correction intentions. The effects were mediated by the activation of personal norms, which showed the strongest direct relationship with correction intentions. However, these factors also demonstrated direct associations with correction intentions, indicating multiple paths in misinformation correction.
Originality/value
Differing from mainstream fact-checking approaches, this study provides a more comprehensive examination of the mechanisms underlying laypeople’s willingness to engage in social media misinformation correction behaviors. In addition, this study also extends NAM by incorporating media environment (perceived prevalence of online misinformation) into the model, identifying more paths affecting misinformation correction behaviors.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2023-0437
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