@inproceedings{markov-daelemans-2022-role,
    title = "The Role of Context in Detecting the Target of Hate Speech",
    author = "Markov, Ilia  and
      Daelemans, Walter",
    editor = "Kumar, Ritesh  and
      Ojha, Atul Kr.  and
      Zampieri, Marcos  and
      Malmasi, Shervin  and
      Kadar, Daniel",
    booktitle = "Proceedings of the Third Workshop on Threat, Aggression and Cyberbullying (TRAC 2022)",
    month = oct,
    year = "2022",
    address = "Gyeongju, Republic of Korea",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2022.trac-1.5/",
    pages = "37--42",
    abstract = "Online hate speech detection is an inherently challenging task that has recently received much attention from the natural language processing community. Despite a substantial increase in performance, considerable challenges remain and include encoding contextual information into automated hate speech detection systems. In this paper, we focus on detecting the target of hate speech in Dutch social media: whether a hateful Facebook comment is directed against migrants or not (i.e., against someone else). We manually annotate the relevant conversational context and investigate the effect of different aspects of context on performance when adding it to a Dutch transformer-based pre-trained language model, BERTje. We show that performance of the model can be significantly improved by integrating relevant contextual information."
}