Work

Automatically Detecting Cyberbullying Comments on Online Game Forums

Year: 2021

Type: conference-paper

Abstract: Online game forums are popular to most of game players. They use it to communicate and discuss the strategy of the game, or even to make friends. However, game forums also contain abusive and harassment speech, disturbing and threatening players. Therefore, it is necessary to automatically detect and remove cyberbullying comments to keep the game forum clean and friendly. We use the Cyberbullying dataset collected from World of Warcraft (WoW) and League of Legends (LoL) forums and train classification models to automatically detect whether a comment of a player is abusive or not. The result obtains 82.69% of macro F1-score for LoL forum and 83.86% of macro F1-score for WoW forum by the Toxic-BERT model on the Cyberbullying dataset.

Source: RIVF International Conference on Computing and Communication Technologies (RIVF)

DOI: 10.1109/rivf51545.2021.9642116

Authors: Hanh Hong-Phuc Vo, Hieu Trung Tran, Son T. Luu

Institutions: Vietnam National University Ho Chi Minh City, University of Information Technology

Language: English

Topic: Hate Speech and Cyberbullying Detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W3169969412

FWCI: 1.271

Cites: 27

Cited by: 20

Related to: 10