构建挑衅性仇恨言论数据集，区分普通仇恨与煽动仇恨
ProvocationProbe: Instigating Hate Speech Dataset from Twitter
- 从2万条推文提取9个全球争议事件，标注挑衅性仇恨言论
- 发现目标身份攻击和仇恨理由是区分煽动仇恨的关键特征
- 适合研究社交媒体内容安全、仇恨言论检测的学者使用
近年来，社交媒体充斥着种族主义、性别歧视、恐同等仇恨言论。为应对这一问题，各大平台采取了多项措施遏制仇恨言论传播。其中，'煽动仇恨'是重要概念，指针对特定群体（如种族、性别、宗教等）煽动敌意的行为。本文提出《ProvocationProbe》数据集，旨在探究煽动性仇恨言论与一般仇恨言论的差异。我们从推特收集约两万条推文，涵盖九个全球性争议话题，涉及种族、政治、宗教等领域。本文贡献包括：（i）对所有争议事件进行详尽分析后构建的标注数据集；（ii）通过识别目标身份攻击和仇恨原因等特征，揭示煽动性仇恨与普通仇恨的本质区别。
原文摘要 · Abstract (English)
In the recent years online social media platforms has been flooded with hateful remarks such as racism, sexism, homophobia etc. As a result, there have been many measures taken by various social media platforms to mitigate the spread of hate-speech over the internet. One particular concept within the domain of hate speech is instigating hate, which involves provoking hatred against a particular community, race, colour, gender, religion or ethnicity. In this work, we introduce \textit{ProvocationProbe} - a dataset designed to explore what distinguishes instigating hate speech from general hate speech. For this study, we collected around twenty thousand tweets from Twitter, encompassing a total of nine global controversies. These controversies span various themes including racism, politics, and religion. In this paper, i) we present an annotated dataset after comprehensive examination of all the controversies, ii) we also highlight the difference between hate speech and instigating hate speech by identifying distinguishing features, such as targeted identity attacks and reasons for hate.
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