From a computer science perspective, addressing on-line hate speech is a challenging task that is attracting the attention of both industry (mainly social media platform owners) and academia. In this chapter, we provide an overview of state-of-the-art data-science approaches - how they define hate speech, which tasks they solve to mitigate the phenomenon, and how they address these tasks. We limit our investigation mostly to (semi-)automatic detection of hate speech, which is the task that the majority of existing computer science works focus on. Finally, we summarize the challenges and the open problems in the current data-science research and the future directions in this field. Our aim is to prepare an easily understandable report, capable to promote the multidisciplinary character of hate speech research. Researchers from other domains (e.g., psychology and sociology) can thus take advantage of the knowledge achieved in the computer science domain but also contribute back and help improve how computer science is addressing that urgent and socially relevant issue which is the prevalence of hate speech in social media.
翻译:从计算机科学的角度来看,处理网上仇恨言论是一项具有挑战性的任务,吸引产业界(主要是社交媒体平台所有者)和学术界的注意。在本章中,我们概述了最先进的数据科学方法----它们如何定义仇恨言论,它们如何解决缓解这一现象的任务,以及它们如何应对这些任务。我们的调查主要局限于(半)自动发现仇恨言论,这是大多数现有计算机科学所关注的任务。最后,我们总结了当前数据科学研究中的挑战和公开的问题以及该领域的未来方向。我们的目标是编写一份易于理解的报告,能够促进仇恨言论研究的多学科性质。因此,其他领域(例如心理学和社会学)的研究人员可以利用在计算机科学领域获得的知识,但也为帮助改进计算机科学如何解决社会媒体中普遍存在的仇恨言论这一紧迫和具有社会相关性的问题作出贡献。