Fostering netizens to engage in rumour-refuting messages of government social media : a view of persuasion theory

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openAccess

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Volume Title

A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Date

2024

Major/Subject

Mcode

Degree programme

Language

en

Pages

25

Series

BEHAVIOUR AND INFORMATION TECHNOLOGY

Abstract

Government agencies have increasingly established their official accounts to disseminate information and publish rumourrefuting messages (RRMs) on social media platforms. However, little is known about what factors facilitate users to engage in RRMs posted by government accounts. To bridge this gap, our study borrows the lens of persuasion theory to frame a research model and unmask the precursors that foster social media users to engage in RRMs. By analysing RRMs published by 10 influential government official accounts spanning 9 years, a field study on Sina Weibo finds that the text length of an RRM is associated with a higher probability of liking, commenting on, and sharing the RRM, while the inclusion of links in RRMs is negatively linked to user engagement. The effect of the existence of photos and videos on user engagement in RRMs depends on different engaging behaviours. The inclusion of emojis in RRMs helps shorten users’ psychological distance from the authorities, thereby facilitating user engagement behaviours. Using rhetorical questions is associated with a higher level of user engagement (including liking and sharing) in RRMs by increasing personal relevance. This study offers new insights into online rumour governance and practical suggestions for promoting government social media publicity.

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Publisher Copyright: © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Keywords

Government social media engagement, persuasion theory, psychological distance, rhetoricals, rumour-refuting message

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Citation

Chen, J, Lin, Y, Tang, X & Deng, S 2024, ' Fostering netizens to engage in rumour-refuting messages of government social media : a view of persuasion theory ', BEHAVIOUR AND INFORMATION TECHNOLOGY, vol. 43, no. 10, pp. 2071-2095 . https://doi.org/10.1080/0144929X.2023.2241084