10.35940/ijrte.A5814.0510121
https://zenodo.org/records/5832253
oai:zenodo.org:5832253
Abhishek Aggarwal
Abhishek Aggarwal
Bachelor of Technology in Electrical Engineering, Delhi Technological University, Delhi, India.
Atul Tiwari
Atul Tiwari
Bachelor of Technology in Electrical Engineering, Delhi Technological University, Delhi, India.
Multi Label Toxic Comment Classification using Machine Learning Algorithms
Zenodo
2021
Accuracy, Multilabel Classification, Machine Learning Algorithms, Toxic Comments
Blue Eyes Intelligence Engineering and Sciences Publication(BEIESP)
Blue Eyes Intelligence Engineering and Sciences Publication(BEIESP)
Publisher
2021-05-30
2277-3878
Creative Commons Attribution 4.0 International
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.