T-HSAB: A Tunisian Hate Speech and Abusive Dataset

Abstract

Since the Jasmine Revolution at 2011, Tunisia has entered a new era of ultimate freedom of expression with a full access into social media. This has been associated with an unrestricted spread of toxic contents such as Abusive and Hate speech. Considering the psychological harm, let alone the potential hate crimes that might be caused by these toxic contents, automatic Abusive and Hate speech detection systems become a mandatory. This evokes the need for Tunisian benchmark datasets required to evaluate Abusive and Hate speech detection models. Being an underrepresented dialect, no previous Abusive or Hate speech datasets were provided for the Tunisian dialect. In this paper, we introduce the first publicly-available Tunisian Hate and Abusive speech (T-HSAB) dataset with the objective to be a benchmark dataset for automatic detection of online Tunisian toxic contents. We provide a detailed review of the data collection steps and how we design the annotation guidelines such that a reliable dataset annotation is guaranteed. This was later emphasized through the comprehensive evaluation of the annotations as the annotation agreement metrics of Cohen's Kappa (k) and Krippendorff's alpha (alpha) indicated the consistency of the annotations.