Analysis of Emotional Coloring of the Texts from Social Webs Based on Methods of Machine Learning

This work is aimed at studying the automatic classification of the emotional coloring of English texts. In the process of research, basic approaches to the automatic determination of the emotional color of the text, the main problems encountered in solving this problem and comparative analysis of the machine learning methods aimed at solving classification problems are examined. In addition, the relevant metrics and the optimal model of the text vectorization were determined. The main goal of this work is to implement several basic machine learning models capable of solving the task of determining the tonality of a text and having high predictive accuracy. All steps of the model implementation should rely on results of the theoretical conclusions of the study. The result will be a classification model selected among those implemented based on the test results.