OffLanDat
收藏arXiv2024-03-28 更新2024-08-06 收录
下载链接：
http://arxiv.org/abs/2403.02472v5
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资源简介：
OffLanDat是由奥本大学计算机科学与软件工程系开发的社区基础隐式攻击性语言数据集，包含8270条文本，针对38个不同的目标群体。该数据集通过ChatGPT生成，特别关注于捕捉不含明显攻击性关键词的隐式攻击性内容。数据集分为七个类别，包括种族/民族、宗教信仰、性别/性取向等，旨在通过这些多样化的数据提升对网络攻击性语言的检测能力。
OffLanDat is a community-based implicit offensive language dataset developed by the Department of Computer Science and Software Engineering at Auburn University. It contains 8,270 text samples targeting 38 distinct target groups. Generated via ChatGPT, this dataset specifically focuses on capturing implicit offensive content that lacks explicit offensive keywords. The dataset is divided into seven categories including race/ethnicity, religious beliefs, gender/sexual orientation and others, aiming to enhance the detection capability of online offensive language through these diverse data samples.
提供机构：
计算机科学与软件工程系，奥本大学
创建时间：
2024-03-05
