Unraveling Disagreement Constituents in Hateful Speech

This paper presents a probabilistic semantic approach to identifying disagreement-related textual constituents in hateful content. Several methodologies to exploit the selected constituents to determine if a message could lead to disagreement have been defined. The proposed approach is evaluated on 4 datasets made available for the SemEval 2023 Task 11 shared task, highlighting that a few constituents can be used as a proxy to identify if a sentence could be perceived differently by multiple readers. The source code of our approaches is publicly available ( https://github.com/MIND-Lab/Unrevealing-Disagreement-Constituents-in-Hateful-Speech ).