The rise in hateful and offensive language directed at other users is one of
the adverse side effects of the increased use of social networking platforms.
This could make it difficult for human moderators to review tagged comments
filtered by classification systems. To help address this issue, we present the
ViHOS (Vietnamese Hate and Offensive Spans) dataset, the first human-annotated
corpus containing 26k spans on 11k comments. We also provide definitions of
hateful and offensive spans in Vietnamese comments as well as detailed
annotation guidelines. Besides, we conduct experiments with various
state-of-the-art models. Specifically, XLM-RLarge​ achieved the best
F1-scores in Single span detection and All spans detection, while
PhoBERTLarge​ obtained the highest in Multiple spans detection. Finally,
our error analysis demonstrates the difficulties in detecting specific types of
spans in our data for future research.
Disclaimer: This paper contains real comments that could be considered
profane, offensive, or abusive.Comment: EACL 202