Identification and Classification of Toxic Statements by Machine Learning Methods
E. N. Platonov, V.Y. Rudenko · Modelling and Data Analysis · 2022
The number of comments left on social media platforms can reach several million per day, so their owners are interested in automatic content filtering. In this paper, the task of identifying offensive statements in texts is considered. When solving the problem, various methods of vector text conversion were considered: TF-IDF, Word2Vec, Glove, etc. The results of the application of classical text classification methods and neural network methods (LSTM, CNN) were also considered and presented.