Comparison of machine learning methods for sentiment analysis

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Every day the amount of text data containing the subjective evaluation of the author is increasing thanks to the Internet. This information is used, for example, by numerous companies to assess the loyalty of their target audience. Due to the incredibly fast growth of the volume of such texts, their manual processing becomes impractical. It is in such situations that automated sentiment analysis is used, which is an actively developing area of natural language processing. We collected a corpus of medical service reviews, on the basis of which three classifiers were trained. We also performed acomparative analysis of the obtained results of the models, which belong to traditional or deep machine learning. Our corpus of texts is public and can be useful for other researchers.