The COVID-19 pandemic has disrupted people's lives driving them to act in fear, anxiety, and anger, leading to worldwide racist events in the physical world and online social networks. Though there are works focusing on Sinophobia during the COVID-19 pandemic, less attention has been given to the recent surge in Islamophobia. A large number of positive cases arising out of the religious Tablighi Jamaat gathering has driven people towards forming anti-Muslim communities around hashtags like #coronajihad, #tablighijamaatvirus on Twitter. In addition to the online spaces, the rise in Islamophobia has also resulted in increased hate crimes in the real world. Hence, an investigation is required to create interventions. To the best of our knowledge, we present the first large-scale quantitative study linking Islamophobia with COVID-19. In this paper, we present CoronaIslam dataset which focuses on anti-Muslim hate spanning four months, with over 410,990 tweets from 244,229 unique users. We use this dataset to perform longitudinal analysis. We find the relation between the trend on Twitter with the offline events that happened over time, measure the qualitative changes in the context associated with the Muslim community, and perform macro and micro topic analysis to find prevalent topics. We also explore the nature of the content, focusing on the toxicity of the URLs shared within the tweets present in the CoronaIslam dataset. Apart from the content-based analysis, we focus on user analysis, revealing that the portrayal of religion as a symbol of patriotism played a crucial role in deciding how the Muslim community was perceived during the pandemic. Through these experiments, we reveal the existence of anti-Muslim rhetoric around COVID-19 in the Indian sub-continent.
翻译:哥维迪-19大流行扰乱了人们的生命,使他们在恐惧、焦虑和愤怒中采取行动,导致在物质世界和在线社交网络中出现全世界种族主义事件。尽管在哥维迪-19大流行期间开展了以仇视华为焦点的工作,但最近仇视伊斯兰现象的激增却受到较少的注意。宗教Tabligihi Jamaat集会产生的大量积极案例促使人们围绕#coronajihad、#slibleghijamaat病毒等标签组成反穆斯林社区。除了在线空间外,仇视伊斯兰教的上升还导致在现实世界中仇恨犯罪增加。因此,需要进行调查,以建立干预措施。根据我们的知识,我们第一次大规模量化研究仇视哥维迪19事件。在本文中,Coronna伊斯兰数据集以反穆斯林仇恨为焦点,长达四个月,来自244,229个独特用户的410,990多条推特。我们利用这一数据集进行纵向分析。我们发现Twitter上的趋势与长期存在的离线性事件之间的关系。我们发现Twitter与长期发生的反面事件之间的关系,从穆斯林内部的内进行的分析,从宏观分析显示质量变化,从内部分析,从研究到内部分析,从一个核心分析到内部的数值分析,从研究,到内部的数值分析,从研究到内部的数值分析,从一个核心分析,从研究,到内部的数值分析,从一个核心分析,到内部的理论分析,从一个核心分析,到内部分析,从研究。在研究。