论文标题
在共同行为中分析COVID-19大流行时的反社会行为
On Analyzing Antisocial Behaviors Amid COVID-19 Pandemic
论文作者
论文摘要
由于全球新闻报道，在线和离线社区的仇外心理和歧视急剧上升，因此，COVID-19的大流行不仅仅是生物危机。这种有毒的行为对社会造成了巨大的损失，尤其是在这些艰巨的时期。尽管这个问题引起了人们的严重性，但很少有研究在19009年大流行中研究了在线反社会行为。在本文中，我们通过收集和注释超过4000万个相关推文的大量数据集来填补研究空白。特别是，我们提出了一个注释框架来自动注释反社会行为。我们还对带注释的数据集进行了经验分析，并发现在COVID-19大流行中引入了新的滥用词典。我们的研究还确定了反社会行为的脆弱目标以及影响在线反社会含量传播的因素。
The COVID-19 pandemic has developed to be more than a bio-crisis as global news has reported a sharp rise in xenophobia and discrimination in both online and offline communities. Such toxic behaviors take a heavy toll on society, especially during these daunting times. Despite the gravity of the issue, very few studies have studied online antisocial behaviors amid the COVID-19 pandemic. In this paper, we fill the research gap by collecting and annotating a large dataset of over 40 million COVID-19 related tweets. Specially, we propose an annotation framework to annotate the antisocial behavior tweets automatically. We also conduct an empirical analysis of our annotated dataset and found that new abusive lexicons are introduced amid the COVID-19 pandemic. Our study also identified the vulnerable targets of antisocial behaviors and the factors that influence the spreading of online antisocial content.
