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    陈慧敏, 金思辰, 林微, 朱泽宇, 仝凌波, 刘一芃, 叶奕宁, 姜维翰, 刘知远, 孙茂松, 金兼斌. 新冠疫情相关社交媒体谣言传播量化分析[J]. 计算机研究与发展, 2021, 58(7): 1366-1384. DOI: 10.7544/issn1000-1239.2021.20200818
    引用本文: 陈慧敏, 金思辰, 林微, 朱泽宇, 仝凌波, 刘一芃, 叶奕宁, 姜维翰, 刘知远, 孙茂松, 金兼斌. 新冠疫情相关社交媒体谣言传播量化分析[J]. 计算机研究与发展, 2021, 58(7): 1366-1384. DOI: 10.7544/issn1000-1239.2021.20200818
    Chen Huimin, Jin Sichen, Lin Wei, Zhu Zeyu, Tong Lingbo, Liu Yipeng, Ye Yining, Jiang Weihan, Liu Zhiyuan, Sun Maosong, Jin Jianbin. Quantitative Analysis on the Communication of COVID-19 Related Social Media Rumors[J]. Journal of Computer Research and Development, 2021, 58(7): 1366-1384. DOI: 10.7544/issn1000-1239.2021.20200818
    Citation: Chen Huimin, Jin Sichen, Lin Wei, Zhu Zeyu, Tong Lingbo, Liu Yipeng, Ye Yining, Jiang Weihan, Liu Zhiyuan, Sun Maosong, Jin Jianbin. Quantitative Analysis on the Communication of COVID-19 Related Social Media Rumors[J]. Journal of Computer Research and Development, 2021, 58(7): 1366-1384. DOI: 10.7544/issn1000-1239.2021.20200818

    新冠疫情相关社交媒体谣言传播量化分析

    Quantitative Analysis on the Communication of COVID-19 Related Social Media Rumors

    • 摘要: 新冠肺炎疫情的爆发伴随着大量的谣言在社交媒体平台传播,对网络秩序和社会稳定产生了不良影响.已有的疫情相关社交媒体谣言传播量化分析研究仅对谣言内容等单一传播要素展开分析,而忽略了构成信息传播的其他基础要素,包括传播者、受众以及传播效果等.同时,这些研究的谣言数据与真实的社交媒体谣言数据也存在分布偏差和信息缺失.因此,基于新浪微博平台对新冠疫情相关社交媒体谣言的传播展开更加全面的量化分析.具体而言,首先对谣言传播内容进行分析,包括其主题分析、涉及地区分析、事件倾向性分析以及情感分析;进一步对谣言参与用户进行分析,将参与用户分为3类:造谣者、传谣者和辟谣者,并分别对其基础属性、关注主题、个体情绪以及自网络属性进行探究;最后对谣言引发舆情进行分析,探究其情感的整体分布、与主题、关键词和地区的关系、以及情感的演变规律.该研究首次从信息传播的各个基础要素层面对疫情相关的社交媒体谣言传播展开量化分析,不仅对新冠肺炎疫情相关谣言传播有了更全面深刻的认识,同时对突发公共事件的谣言研究和谣言治理也具有十分重要的价值.

       

      Abstract: The outbreak of the COVID-19 pandemic is accompanied by numerous rumors spreading on the social media platform, which seriously affects the stability of society and the safety of public. Existing quantitative analyses of COVID-19 related social media rumors only focus on single element of communication, such as content, while ignoring other basic elements of communication, including communicator, audience, and effect. Besides, compared with the real social media rumor data, the rumor data of these studies have distribution bias and lack of information. Therefore, we conduct a more comprehensive quantitative analysis on the communication of COVID-19 related social media rumors based on the Sina Weibo platform. Specifically, we first analyze the communication content of rumors, including the analysis of the topic, involved regions, event tendency and sentiment. Further, we investigate the users engaged in rumor communication and divide the users into three categories, namely, rumor posters, rumor spreaders, and rumor informers. We explore the basic attributes, topic preferences, individual sentiments, and self-network characteristics of the engaged users. Finally, we study the public opinion triggered by rumors, including the overall sentiment distribution, its correlation with topics, keywords and regions, as well as the evolution of sentiment. To conclude, this study first quantitatively analyzes COVID-19 related social media rumors from the perspective of different basic elements in communication. It provides a more comprehensive and profound understanding of COVID-19 related social media rumors and is of great value for both research and management of rumor in public emergencies.

       

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