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官方机构与在线社交网络中谣言控制有影响力用户之间的互动。

Interaction between official institutions and influential users of rumor control in online social networks.

作者信息

Bai Shizhen, Wu Wenya, Jiang Man

机构信息

School of Management, Harbin University of Commerce, Harbin, China.

出版信息

Front Psychol. 2022 Aug 2;13:937296. doi: 10.3389/fpsyg.2022.937296. eCollection 2022.

DOI:10.3389/fpsyg.2022.937296
PMID:35983205
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9379133/
Abstract

Online interactions have become major channels for people to obtain and disseminate information during the new normal of COVID-19, which can also be a primary platform for rumor propagation. There are many complex psychological reasons for spreading rumors, but previous studies have not fully analyzed this problem from the perspective of the interaction between official institutions and influential users. The purpose of this study is to determine optimal strategies for official institutions considering the impact of two different influential user types (trolls and reputed personalities) by designing two game-theoretic models, namely "Rumor Clarification and Interaction Model" and "Rumor Verification and Interaction Model," which can, respectively decide whether to clarify and when to clarify. The results of this article show that clarification strategies can be decided according to the characteristics of rumors and the influential user's reactions. Meanwhile, publishing verified information prevents trolls' "loophole advantages" and prevents reputed personalities from spreading false information due to the vague authenticity of rumors. Results also show that the verification strategy is limited by cost, period, and verification index.

摘要

在新冠疫情常态化期间,线上互动已成为人们获取和传播信息的主要渠道,而这也可能成为谣言传播的主要平台。谣言传播存在诸多复杂的心理原因,但以往的研究尚未从官方机构与有影响力的用户之间的互动角度对这一问题进行充分分析。本研究的目的是通过设计两个博弈论模型,即“谣言澄清与互动模型”和“谣言核实与互动模型”,来确定官方机构在考虑两种不同类型有影响力用户(恶意用户和知名人士)影响时的最优策略,这两个模型可以分别决定是否澄清以及何时澄清。本文的结果表明,可以根据谣言的特征和有影响力用户的反应来决定澄清策略。同时,发布经过核实的信息可防止恶意用户的“漏洞优势”,并防止知名人士因谣言真实性模糊而传播虚假信息。结果还表明,核实策略受到成本、时间和核实指标的限制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1571/9379133/dd023b6d50ef/fpsyg-13-937296-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1571/9379133/ec1a988d69d8/fpsyg-13-937296-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1571/9379133/186e5f513112/fpsyg-13-937296-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1571/9379133/7139caa77047/fpsyg-13-937296-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1571/9379133/e66353a6a339/fpsyg-13-937296-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1571/9379133/ca0f58e2a202/fpsyg-13-937296-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1571/9379133/dd023b6d50ef/fpsyg-13-937296-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1571/9379133/ec1a988d69d8/fpsyg-13-937296-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1571/9379133/186e5f513112/fpsyg-13-937296-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1571/9379133/7139caa77047/fpsyg-13-937296-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1571/9379133/e66353a6a339/fpsyg-13-937296-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1571/9379133/ca0f58e2a202/fpsyg-13-937296-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1571/9379133/dd023b6d50ef/fpsyg-13-937296-g006.jpg

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本文引用的文献

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The "Parallel Pandemic" in the Context of China: The Spread of Rumors and Rumor-Corrections During COVID-19 in Chinese Social Media.中国背景下的“平行大流行”:新冠疫情期间谣言及辟谣信息在中国社交媒体上的传播
Am Behav Sci. 2021 Dec;65(14):2014-2036. doi: 10.1177/00027642211003153.
2
Rumors clarification with minimum credibility in social networks.社交网络中可信度极低的谣言澄清
Comput Netw. 2021 Jul 5;193:108123. doi: 10.1016/j.comnet.2021.108123. Epub 2021 Apr 18.
3
A two-stage social network intervention for reducing alcohol and other drug use in residential colleges: Protocol for a feasibility trial.
两阶段社交网络干预减少住宿学院中学生的酒精和其他药物使用:可行性试验方案。
Contemp Clin Trials. 2022 Jul;118:106779. doi: 10.1016/j.cct.2022.106779. Epub 2022 Apr 28.
4
Sharing or Not: Psychological Motivations of Brand Rumors Spread and the Stop Solutions.分享与否:品牌谣言传播的心理动机及制止策略
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5
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6
Identification of influencers in online social networks: measuring influence considering multidimensional factors exploration.在线社交网络中影响者的识别:考虑多维度因素探索的影响力测量
Heliyon. 2021 Apr 15;7(4):e06472. doi: 10.1016/j.heliyon.2021.e06472. eCollection 2021 Apr.
7
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8
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9
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10
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