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Communication Dans Un Congrès Année : 2021

Persian Sentence-level Sentiment Polarity Classification

Kia Dashtipour
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Mandar Gogate
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  • PersonId : 1098662
Amir Hussain
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Résumé

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 Naïve Bayes classifier has been used to evaluate the performance of the proposed method. The SVM received better results in comparison with Naïve Bayes and MLP.
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Dates et versions

hal-03258138 , version 1 (11-06-2021)

Identifiants

  • HAL Id : hal-03258138 , version 1

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Kia Dashtipour, Mandar Gogate, Alexander Gelbukh, Amir Hussain. Persian Sentence-level Sentiment Polarity Classification. ICOTEN, Jun 2021, Glasgow, United Kingdom. ⟨hal-03258138⟩
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