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Author:

Dong, Xuefan (Dong, Xuefan.) | Lian, Xueying (Lian, Xueying.) | Lian, Ying (Lian, Ying.)

Indexed by:

SSCI EI Scopus SCIE

Abstract:

In the digital era, effectively managing rumors on social media during public health emergencies remains a significant challenge, highlighting a gap in understanding the optimal strategies for refutation. This study used the COVID-19 pandemic as a case to explore the effectiveness of different rumor refutation strategies on social media during acute public health emergencies, with a specific focus on the moderating effects of the elements contained in the refutation texts based on the 5 W theory. By leveraging the comprehensive and structured nature of the 5 W elements (What, When, Where, Who, and Why), this study provides a novel framework for evaluating and optimizing refutation strategies. A total of 22,648 refutation posts related to COVID-19 from the Weibo platform in 2020 were employed from empirical analysis. Findings indicate that the combination of direct refutation with factual clarification is more effective in enhancing the credibility and dissemination of reputation information compared to isolated strategies. Importantly, the study highlights the moderating role of specific rumor characteristics, such as the rumor's name, location, and the underlying reasons, on the effectiveness of these strategies. Furthermore, the study provides practical policy recommendations based on empirical findings. Overall, this research enriches the academic discourse on rumor management, offering innovative applications of the 5 W theory and detailed analysis of moderating effects, and provides empirical guidance for public health communicators and policymakers in tailoring refutation strategies to specific characteristics of rumors for more effective rumor containment.

Keyword:

Rumor refutation Public health emergency COVID-19 pandemic Crisis communication 5W theory

Author Community:

  • [ 1 ] [Dong, Xuefan]Beijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China
  • [ 2 ] [Lian, Xueying]Beijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China
  • [ 3 ] [Dong, Xuefan]Beijing Univ Technol, Res Base Beijing Modern Mfg Dev, Beijing 100124, Peoples R China
  • [ 4 ] [Lian, Ying]Commun Univ China, Sch Journalism, 1 Dingfuzhuang East St, Beijing 100024, Peoples R China

Reprint Author's Address:

  • [Lian, Ying]Commun Univ China, Sch Journalism, 1 Dingfuzhuang East St, Beijing 100024, Peoples R China

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Source :

INFORMATION PROCESSING & MANAGEMENT

ISSN: 0306-4573

Year: 2025

Issue: 4

Volume: 62

8 . 6 0 0

JCR@2022

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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