hatexplain

Hatexplain是一个用于可解释仇恨言论检测的基准数据集，它涵盖了仇恨言论问题的多个方面。数据内容包括英文文本，规模为1万到10万条样本。每条帖子都从三个不同的角度进行标注：基本的3类分类（仇恨、冒犯或正常）、目标群体（帖子中仇恨/冒犯言论的受害者）以及理由（标注决策所依据的帖子部分）。数据采集自Twitter和Gab，经过了标准化处理，并通过众包方式进行标注。Hatexplain支持文本分类等任务，并采用CC-BY 4.0授权许可。

Hatexplain is a benchmark dataset for explainable hate speech detection, covering multiple facets of the hate speech issue. It contains English text samples totaling between 10,000 and 100,000 entries. Each post is annotated across three core dimensions: a three-category classification (hate, offensive, or normal), target victim groups (the groups targeted by hate or offensive speech in the post), and rationales (the specific segments of the post that underpin the annotation decisions). The dataset was collected from Twitter and Gab, standardized, and annotated via crowdsourcing. Hatexplain supports tasks including text classification, and is licensed under CC-BY 4.0.

搜集汇总

背景与挑战

背景概述

Hatexplain是一个用于可解释仇恨言论检测的英文基准数据集，规模在1万到10万条样本之间，数据来自Twitter和Gab平台。每条帖子都标注了基本分类、目标群体和理由，支持文本分类任务，采用CC-BY 4.0授权许可。