Abstract
AbstractThe article is focused on the problem of identifying the sentiment of texts in Russian. This problem has a significant impact on a wide range of natural language processing tasks such as online feedback processing and review analysis. There are many approaches for solution of this problem, such as using fuzzy logic techniques, keyword techniques, machine learning, and knowledge-based techniques. All these approaches are described and comparatively analysed in the article. As a result of the research, a new model for sentiment extraction from natural language text was proposed and a software module was developed to prove the proposed method. The developed module was integrated into an existing software system based on the semantic network and frame semantics. The effectiveness of the developed system was tested on the previously data set that was evaluated by experts. The test results show the competitiveness of the proposed method in comparison with previous data.KeywordsTonality of the textSentiment analysisNatural language textText tonality processingNatural language processingOCC model
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