Proceedings of the XXth Conference of Open Innovations Association FRUCT (Nov 2018)

Sentiment Classification of Russian Texts Using Automatically Generated Thesaurus

  • Ksenia Lagutina,
  • Vladislav Larionov,
  • Vladislav Petryakov,
  • Nadezhda Lagutina,
  • Ilya Paramonov

Journal volume & issue
Vol. 602, no. 23
pp. 217 – 222

Abstract

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This paper is devoted to an approach for sentiment classification of Russian texts applying an automatic thesaurus of the subject area. This approach consists of a standard machine learning classifier and a procedure embedded into it, that uses the- saurus relationships for better sentiment analysis. The thesaurus is generated fully automatically and does not require expert’s involvement into classification process. Experiments conducted with the approach and four Russian-language text corpora, show effectiveness of thesaurus application to sentiment classification.

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