A Morpho-syntactic Analysis of Human-moderated Hate Speech Samples from Wykop.pl Web Service

Abstract

The dynamic increase in user-generated content on the web presents significant challenges in protecting Internet users from exposure to offensive material, such as cyberbullying and hate speech, while also minimizing the spread of wrongful conduct. However, designing automated detection models for such offensive content remains complex, particularly in languages with limited publicly available data. To address this issue, our research collaborates with the Wykop.pl web service to fine-tune a model using genuine content that has been banned by professional moderators. In this paper, we focus on the Polish language and discuss the notion of datasets and annotation frameworks, presenting our stylometric analysis of Wykop.pl content to identify morpho-syntactic structures that are commonly applied in cyberbullying and hate speech. By doing so, we contribute to the ongoing discussion on offensive language and hate speech in sociolinguistic studies, emphasizing the need to consider user-generated online content.