论文标题
在社交媒体上发现东亚偏见
Detecting East Asian Prejudice on Social Media
论文作者
论文摘要
当政府解决大流行的健康，经济和社会成本时，Covid-19的爆发使全世界的社会改变了世界。它还引起了人们对在线仇恨语言和偏见的传播的担忧，尤其是针对东亚的敌对情绪。在本文中，我们报告了一个分类器的创建，该分类器将来自Twitter的社交媒体帖子检测和分类为四个类别：对东亚的敌意，对东亚的批评，东亚偏见的元讨论和中立阶级。分类器在所有四个类中的F1得分为0.83。我们提供最终模型（在Python中进行了编码），以及用于制作分类器的新的20,000个推文培训数据集，与东亚偏见相关的两个主题标签和注释代码簿。分类器可以由其他研究人员实施，协助在线内容审核过程，并进一步研究这次全球大流行期间东亚偏见的动态，流行和影响。
The outbreak of COVID-19 has transformed societies across the world as governments tackle the health, economic and social costs of the pandemic. It has also raised concerns about the spread of hateful language and prejudice online, especially hostility directed against East Asia. In this paper we report on the creation of a classifier that detects and categorizes social media posts from Twitter into four classes: Hostility against East Asia, Criticism of East Asia, Meta-discussions of East Asian prejudice and a neutral class. The classifier achieves an F1 score of 0.83 across all four classes. We provide our final model (coded in Python), as well as a new 20,000 tweet training dataset used to make the classifier, two analyses of hashtags associated with East Asian prejudice and the annotation codebook. The classifier can be implemented by other researchers, assisting with both online content moderation processes and further research into the dynamics, prevalence and impact of East Asian prejudice online during this global pandemic.
