Hate Span Identification

The first human-annotated corpus containing 26k spans on 11k comments

TuPyE, an enhanced iteration of TuPy, encompasses a compilation of 43,668 meticulously annotated documents specifically selected for the purpose of hate speech detection within diverse social network contexts. This augmented dataset integrates supplementary annotations and amalgamates with datasets sourced from Fortuna et al. (2019), Leite et al. (2020), and Vargas et al. (2022), complemented by an infusion of 10,000 original documents from the TuPy-Dataset. In light of the constrained availability of annotated data in Portuguese pertaining to the English language, TuPyE is committed to the expansion and enhancement of existing datasets. This augmentation serves to facilitate the development of advanced hate speech detection models through the utilization of machine learning (ML) and natural language processing (NLP) techniques.

Arabic multi-dialectal hate speech dataset. It consists of 23,033 tweets labelled for Hate, Abusive and Normal in three Arabic dialects Egyptian, Lebaneese and Tunisian. How to cite this work: Badri, Nabil, Ferihane Kboubi, and Anja Habacha Chaibi. "Towards automatic detection of inappropriate content in multi-dialectic Arabic text." International Conference on Computational Collective Intelligence. Cham: Springer International Publishing, 2022.