Multilingual and Multi-Aspect Hate Speech Analysis

TL;DR

This paper introduces a new multilingual, multi-aspect hate speech dataset and evaluates state-of-the-art multilingual multitask learning methods on it, aiming to improve hate speech detection across languages and aspects.

Contribution

It provides a novel multilingual multi-aspect hate speech dataset and assesses current models, highlighting ways to enhance hate speech classification.

Findings

Multilingual multi-aspect dataset enables comprehensive hate speech analysis.

State-of-the-art models show varying performance across languages and aspects.

Discussion offers strategies to leverage annotations for better detection.

Abstract

Current research on hate speech analysis is typically oriented towards monolingual and single classification tasks. In this paper, we present a new multilingual multi-aspect hate speech analysis dataset and use it to test the current state-of-the-art multilingual multitask learning approaches. We evaluate our dataset in various classification settings, then we discuss how to leverage our annotations in order to improve hate speech detection and classification in general.