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SentiRusColl: Russian Collocation Lexicon for Sentiment Analysis

  • Anastasia Kotelnikova
  • Evgeny KotelnikovEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1119)

Abstract

Most sentiment lexicons include individual words rather than collocations. However, the use of collocations can improve the performance of sentiment analysis since the meaning of some collocations cannot be derived from the meaning of their constituents, for example, “ Open image in new window (“kick the bucket”) or “ Open image in new window (“it is impossible to take one’s eyes off something”). In our study, we create sentiment collocation lexicons for ten domains – reviews of books, movies, music, cars, computers, house appliances, phones, banks, hotels and restaurants. The lexicons are built on the basis of a semi-automatic approach using the corpora of reviews. What is more, we form a universal SentiRusColl lexicon with the help of union of created domain-oriented lexicons. We demonstrate the possibility of using the generated lexicon for various domains. In addition, we reveal the improved performance of sentiment analysis when union of SentiRusColl and existing lexicon – RuSentiLex – is used.

Keywords

Sentiment lexicons Sentiment analysis Opinion mining Collocations 

Notes

Acknowledgments

The reported study was funded by the Ministry of Education and Science of the Russian Federation according to the research project No. 34.2092.2017/4.6.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Vyatka State UniversityKirovRussia

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