Dong Wei, Tao Jinhu, Xia Xiaolin, Ye Lin, Xu Hanli, Jiang Peiye, Liu Yangyang
School of Education, Tianjin University, Tianjin, China.
School of Media and Communication, Shanghai Jiaotong University, Shanghai, China.
J Med Internet Res. 2020 Nov 25;22(11):e21933. doi: 10.2196/21933.
BACKGROUND: Various online rumors have led to inappropriate behaviors among the public in response to the COVID-19 epidemic in China. These rumors adversely affect people's physical and mental health. Therefore, a better understanding of the relationship between public emotions and rumors during the epidemic may help generate useful strategies for guiding public emotions and dispelling rumors. OBJECTIVE: This study aimed to explore whether public emotions are related to the dissemination of online rumors in the context of COVID-19. METHODS: We used the web-crawling tool Scrapy to gather data published by People's Daily on Sina Weibo, a popular social media platform in China, after January 8, 2020. Netizens' comments under each Weibo post were collected. Nearly 1 million comments thus collected were divided into 5 categories: happiness, sadness, anger, fear, and neutral, based on the underlying emotional information identified and extracted from the comments by using a manual identification process. Data on rumors spread online were collected through Tencent's Jiaozhen platform. Time-lagged cross-correlation analyses were performed to examine the relationship between public emotions and rumors. RESULTS: Our results indicated that the angrier the public felt, the more rumors there would likely be (r=0.48, P<.001). Similar results were observed for the relationship between fear and rumors (r=0.51, P<.001) and between sadness and rumors (r=0.47, P<.001). Furthermore, we found a positive correlation between happiness and rumors, with happiness lagging the emergence of rumors by 1 day (r=0.56, P<.001). In addition, our data showed a significant positive correlation between fear and fearful rumors (r=0.34, P=.02). CONCLUSIONS: Our findings confirm that public emotions are related to the rumors spread online in the context of COVID-19 in China. Moreover, these findings provide several suggestions, such as the use of web-based monitoring methods, for relevant authorities and policy makers to guide public emotions and behavior during this public health emergency.
背景：各种网络谣言导致中国公众在应对新冠疫情时出现不当行为。这些谣言对人们的身心健康产生了不利影响。因此，更好地了解疫情期间公众情绪与谣言之间的关系，可能有助于制定引导公众情绪和辟谣的有效策略。 目的：本研究旨在探讨在新冠疫情背景下，公众情绪与网络谣言传播是否相关。 方法：我们使用网络爬虫工具Scrapy收集了2020年1月8日之后《人民日报》在新浪微博（中国一个受欢迎的社交媒体平台）上发布的数据。收集了每条微博帖子下网民的评论。通过人工识别过程，根据从评论中识别和提取的潜在情绪信息，将收集到的近100万条评论分为5类：快乐、悲伤、愤怒、恐惧和中性。通过腾讯较真平台收集网络传播谣言的数据。进行了时间滞后交叉相关分析，以检验公众情绪与谣言之间的关系。 结果：我们的结果表明，公众越愤怒，可能出现的谣言就越多（r = 0.48，P <.001）。恐惧与谣言之间的关系（r = 0.51，P <.001）以及悲伤与谣言之间的关系（r = 0.47，P <.001）也观察到了类似结果。此外，我们发现快乐与谣言之间存在正相关，快乐比谣言出现滞后1天（r = 0.56，P <.001）。此外，我们的数据显示恐惧与恐惧类谣言之间存在显著正相关（r = 0.34，P =.02）。 结论：我们的研究结果证实，在中国新冠疫情背景下，公众情绪与网络传播的谣言相关。此外，这些发现为相关部门和政策制定者在这一突发公共卫生事件期间引导公众情绪和行为提供了一些建议，如使用基于网络的监测方法。
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