Classification of Online Toxic Comments using Machine Learning Algorithms

Abstract

Conversational toxicity is a problem that might drive people to cease truly expressing themselves and seeking out 
other people's opinions out of fear of being attacked or harassed. The purpose of this research is to employ natural 
language processing (NLP) techniques to detect toxicity in writing, which might be used to alert people before 
transmitting potentially toxic informational messages. Natural language processing (NLP) is a part of machine 
learning that enables computers to comprehend natural language. Understanding, analyzing, manipulating, and 
maybe producing human data language with the help of a machine are all possibilities. Natural Language Processing 
(NLP) is a type of artificial intelligence that allows machines to understand and interpret human language instead 
of simply reading it. Machines can understand written or spoken text and execute tasks such as speech recognition, 
sentiment analysis, text classification, and automatic text summarization using natural language processing (NLP). 

Convolutional neural networks, medical image analysis, machine learning, deep learning.