仇恨信息：Discord上青少年产生的仇恨言论对话数据集
Hateful Messages: A Conversational Data Set of Hate Speech produced by Adolescents on Discord
AI总结：
本研究构建了包含88,395条Discord青少年聊天消息的匿名仇恨言论数据集，以解决青少年语言偏见，约6.42%被标注为仇恨言论，作者平均年龄低于20岁。
摘要：
随着社交媒体的兴起，可以观察到仇恨内容的增加。尽管对仇恨言论的理解和定义各不相同，但平台、社区和立法机构都承认这一问题。因此，青少年是社交媒体用户中一个新的且活跃的群体。大多数青少年经历过或目睹过在线仇恨言论。自动仇恨言论分类领域的研究一直在增加，并侧重于偏见、泛化能力和性能等方面。为了提高泛化能力和性能，理解数据中的偏见至关重要。本研究解决了仇恨言论分类中青少年语言的偏见问题，并通过提供一个现代且匿名的仇恨言论青少年语言数据集来做出贡献，该数据集包含88,395条带注释的聊天消息。该数据集由聊天平台Discord上公开可用的在线消息组成。约6.42%的消息被自行开发的注释模式分类为仇恨言论。对于35,553条消息，用户资料提供了年龄注释，将作者平均年龄设定为20岁以下。
英文摘要：
With the rise of social media, a rise of hateful content can be observed. Even though the understanding and definitions of hate speech varies, platforms, communities, and legislature all acknowledge the problem. Therefore, adolescents are a new and active group of social media users. The majority of adolescents experience or witness online hate speech. Research in the field of automated hate speech classification has been on the rise and focuses on aspects such as bias, generalizability, and performance. To increase generalizability and performance, it is important to understand biases within the data. This research addresses the bias of youth language within hate speech classification and contributes by providing a modern and anonymized hate speech youth language data set consisting of 88.395 annotated chat messages. The data set consists of publicly available online messages from the chat platform Discord. ~6,42% of the messages were classified by a self-developed annotation schema as hate speech. For 35.553 messages, the user profiles provided age annotations setting the average author age to under 20 years old.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
