Multilingual and Multi-Aspect Hate Speech Analysis
This work addresses the need for more comprehensive hate speech analysis tools across languages and aspects, though it is incremental as it builds on existing multilingual multitask methods.
The authors tackled the problem of limited monolingual and single-task hate speech analysis by creating a new multilingual multi-aspect dataset, which they used to test state-of-the-art multilingual multitask learning approaches and evaluate in various classification settings.
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.