Multi Label Toxic Comment Classification using Machine Learning Algorithms

Author:

Aggarwal Abhishek, ,Tiwari Atul,

Abstract

Toxic comments are the comments found in the online forums that are rude, offensive, or unfair and usually cause many users to exit the conversation. The threat of bullying and abuse on the internet obstructs the free exchange of ideas by limiting people’s opposing viewpoints. Most of the Websites fail to successfully facilitate healthy conversations, leading them to either restrict or disable user comments entirely. This paper would explore the scope of online abuse and categorize them into different labels to assess the toxicity as accurately as possible using machine learning algorithms.

Publisher

Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP

Subject

Management of Technology and Innovation,General Engineering

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Analyzing the Feasibility of Bert Model for Toxicity Analysis of Text;International Conference on Innovative Computing and Communications;2023-10-26

2. Multi-Label Toxicity Detection: An Analysis;2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA);2023-08-03

3. Research of techniques used in toxicity detection;INTERNATIONAL CONFERENCE ON APPLIED COMPUTATIONAL INTELLIGENCE AND ANALYTICS (ACIA-2022);2023

4. Analysis of Multiple Toxicities Using ML Algorithms to Detect Toxic Comments;2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE);2022-04-28

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