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Analyzing Public Opinion and Misinformation in a COVID-19 Telegram Group Chat
IEEE Internet Computing ( IF 3.7 ) Pub Date : 2020-12-11 , DOI: 10.1109/mic.2020.3040516
Lynnette Hui Xian Ng 1 , Jia Yuan Loke 2
Affiliation  

We analyze a Singapore-based COVID-19 Telegram group with more than 10000 participants. First, we study the group’s opinion over time, focusing on five dimensions: participation, sentiment, negative emotions, topics, and message types. We find that participation peaked when the Ministry of Health raised the disease alert level, but this engagement was not sustained. Second, we investigate the prevalence of, and reactions to, authority-identified misinformation in the group. We find that authority-identified misinformation is rare, and that participants affirm, deny, and question misinformation. Third, we explore searching for user skepticism as one strategy for identifying misinformation, finding misinformation not previously identified by authorities.

中文翻译:


分析 COVID-19 Telegram 群聊中的舆论和错误信息



我们分析了位于新加坡的一个拥有 10000 多名参与者的 COVID-19 Telegram 群组。首先,我们随着时间的推移研究该群体的观点,重点关注五个维度:参与、情绪、负面情绪、主题和消息类型。我们发现,当卫生部提高疾病警报级别时,参与度达到顶峰,但这种参与度并未持续。其次,我们调查了该群体中权威认定的错误信息的流行程度和反应。我们发现,权威认定的错误信息很少见,参与者肯定、否认和质疑错误信息。第三,我们探索寻找用户怀疑作为识别错误信息的一种策略,发现当局之前未识别的错误信息。
更新日期:2020-12-11
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