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Citation

Dashtipour K, Gogate M, Gelbukh A & Hussain A (2021) Persian Sentence-level Sentiment Polarity Classification. In: TBC. ICOTEN 2021: International Congress of Advanced Technology and Engineering, Virtual, 04.07.2021-05.07.2021. Piscataway, NJ, USA: IEEE.

Abstract
Assigning positive and negative polarity into Persian sentences is difficult task, there are different approaches has been proposed in various languages such as English. However, there is not any approach available to identify the final polarity of the Persian sentences. In this paper, the novel approach has been proposed to detect polarity for Persian sentences using PerSent lexicon (Persian lexicon). For this, we have proposed two different algorithms to detect polarity in the sentence and finally SVM, MLP and Na¨?ve Bayes classifier has been used to evaluate the performance of the proposed method. The SVM received better results in comparison with Na¨?ve Bayes and MLP.

Keywords
Sentiment Analysis; Persian; Machine Learning

Notes
Output Status: Forthcoming

• Accepted manuscript