K-MHaS: A Multi-label Hate Speech Detection Dataset in Korean Online News Comment

08/23/2022
by   Jean Lee, et al.
0

Online Hate speech detection has become important with the growth of digital devices, but resources in languages other than English are extremely limited. We introduce K-MHaS, a new multi-label dataset for hate speech detection that effectively handles Korean language patterns. The dataset consists of 109k utterances from news comments and provides multi-label classification from 1 to 4 labels, and handling subjectivity and intersectionality. We evaluate strong baselines on K-MHaS. KR-BERT with sub-character tokenizer outperforms, recognising decomposed characters in each hate speech class.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/26/2020

BEEP! Korean Corpus of Online News Comments for Toxic Speech Detection

Toxic comments in online platforms are an unavoidable social issue under...
research
05/30/2023

A Stutter Seldom Comes Alone – Cross-Corpus Stuttering Detection as a Multi-label Problem

Most stuttering detection and classification research has viewed stutter...
research
10/28/2022

Dysfluencies Seldom Come Alone – Detection as a Multi-Label Problem

Specially adapted speech recognition models are necessary to handle stut...
research
10/28/2022

"It's Not Just Hate”: A Multi-Dimensional Perspective on Detecting Harmful Speech Online

Well-annotated data is a prerequisite for good Natural Language Processi...
research
04/07/2022

Korean Online Hate Speech Dataset for Multilabel Classification: How Can Social Science Improve Dataset on Hate Speech?

We suggest a multilabel Korean online hate speech dataset that covers se...
research
05/05/2022

RaFoLa: A Rationale-Annotated Corpus for Detecting Indicators of Forced Labour

Forced labour is the most common type of modern slavery, and it is incre...
research
01/26/2023

A benchmark for toxic comment classification on Civil Comments dataset

Toxic comment detection on social media has proven to be essential for c...

Please sign up or login with your details

Forgot password? Click here to reset