Online extremism and Islamophobic language and sentiment when discussing the COVID-19 pandemic and misinformation on Twitter
Online extremism and Islamophobic language and sentiment when discussing the COVID-19 pandemic and misinformation on Twitter
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DOI：
10.1080/01419870.2022.2146449
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发表时间：
2022-12-10
影响因子：
2.5
通讯作者：
Lally, Harkereet
中科院分区：
文献类型：
--
作者：
Awan, Imran;Carter, Pelham;Lally, Harkereet
本文着眼于 COVID-19 大流行期间在 Twitter 上从事伊斯兰恐惧症语言/极端主义行为的人的概况。这个由两部分组成的分析考虑了匿名、会员长度和语言使用频率以及亲社会和反社会推文之间表达的情绪差异等因素。分析包括低、中和高匿名程度、邮寄频率和会员长度之间的比较，从而探索关键字使用的差异。我们的研究结果表明，匿名性的增加与仇视伊斯兰教的语言和错误信息的增加无关。情绪分析表明，愤怒、厌恶、恐惧、悲伤和信任等情绪与亲社交 Twitter 用户的相关性显着更高，而期待、喜悦和惊讶等情绪与反社交 Twitter 用户的相关性显着更高。在某些情况下，人们表达了对他人因大流行而遭受的痛苦感到高兴的证据。
This paper looks at the profiles of those who engaged in Islamophobic language/extremist behaviour on Twitter during the COVID-19 pandemic. This two-part analysis takes into account factors such as anonymity, membership length and postage frequency on language use, and the differences in sentiment expressed between pro-social and anti-social tweets. Analysis includes comparisons between low, moderate and high levels of anonymity, postage frequency and membership length, allowing for differences in keyword use to be explored. Our findings suggest that increased anonymity is not associated with an increase in Islamophobic language and misinformation. The sentiment analysis indicated that emotions such as anger, disgust, fear, sadness and trust were significantly more associated with pro-social Twitter users whereas sentiments such as anticipation, joy and surprise were significantly more associated with anti-social Twitter users. In some cases, evidence for joy in the suffering of others as a result of the pandemic was expressed.