SENTIMENT ANALYSIS OF UNIVERSITY FEEDBACK OPINION OF STUDENTS ABOUT AN EDUCATIONAL PART IN KAZAKH LANGUAGE USING MULTIBINOMIAL NAIVE BAYES CLASSIFIER

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Date

2019

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Publisher

СДУ хабаршысы - 2019

Abstract

Abstract. In this paper, the system which identifies the sentiment, (aka meaning) of a kazakh phrase, (whether it is a positive, or a negative) have been implemented using MultiBinomial Naive Bayes Classifier and achieved accuracy approximately 71 % on the dataset about university feedback across students on its educational component in order to help administrative staff to evaluate the current state of education in the university and make some decisions on its basis. We consider it to be a good result, given that the data was small in size, so that there were only few collected samples. The importance of the work that we did not find any paper which performed sentiment analysis using MultiBinomial Naive Bayes classifier on an agglutinative language. It can be argued, that the model can be successfully generalized in other educational organizations pursuing the same cause as it was identified in the above-mentioned rationale. The limitation of the paper is that only one algorithm has been applied to it, and the dataset size is small.

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Keywords

sentiment analysis on kazakh language, sentiment analysis, nlp on kazakh text, agglutinative languages, bayes classifier nlp, СДУ хабаршысы - 2019, №3

Citation

А. Серек, М. Жапаров / A. Serek , M. Zhaparov / SENTIMENT ANALYSIS OF UNIVERSITY FEEDBACK OPINION OF STUDENTS ABOUT AN EDUCATIONAL PART IN KAZAKH LANGUAGE USING MULTIBINOMIAL NAIVE BAYES CLASSIFIER / СДУ хабаршысы - 2019