• Corpus ID: 236493331

Detecting Abusive Albanian

@article{Nurce2021DetectingAA,
  title={Detecting Abusive Albanian},
  author={Erida Nurce and Jorgel Keci and Leon Derczynski},
  journal={ArXiv},
  year={2021},
  volume={abs/2107.13592}
}

• Erida Nurce, Jorgel Keci, Leon Derczynski
• Published 28 July 2021
• Computer Science
• ArXiv

The ever growing usage of social media in the recent years has had a direct impact on the increased presence of hate speech and offensive speech in online platforms. Research on effective detection of such content has mainly fo-cused on English and a few other widespread languages, while the leftover majority fail to have the same work put into them and thus cannot benefit from the steady advancements made in the field. In this paper we present Shaj , an annotated Albanian dataset for hate speech and offensive speech that has been constructed from user-generated content on various social media platforms. Its annotation follows the hi-erarchical schema introduced in Zampieri et al. (2019b). The dataset is tested using three different classification models, the best of which achieves an F1 score of 0.77 for the identification of offensive language, 0.64 F1 score for the automatic categorization of offensive types and lastly, 0.52 F1 score for the offensive language target identification.