ViHOS: Hate Speech Spans Detection for Vietnamese

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 pr...

Full description

Saved in:
Bibliographic Details
Published in:arXiv.org 2023-01
Main Authors: Hoang, Phu Gia, Luu, Canh Duc, Tran, Khanh Quoc, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen
Format: Article
Language:English
Subjects:
Annotations
Error analysis
Error detection
Moderators
Side effects
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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-R\(_{Large}\) achieved the best F1-scores in Single span detection and All spans detection, while PhoBERT\(_{Large}\) 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.
ISSN:2331-8422