Hateful Messages: A Conversational Data Set of Hate Speech Produced by Adolescents on Discord

With the rise of social media, an increase of hateful content online can be observed. Even though the understanding and definitions of hate speech vary, platforms, communities, and legislature all acknowledge the challenge. 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. For 35.553 messages, the user profiles provided age annotations, setting the average author age to under 20 years old. 6,4% of the total messages were classified as hate speech using the annotation schema, which was adapted for this data set.