• Heterogeneous classifier ensemble for sentiment analysis of Bengali and Hindi tweets

    • Fulltext


        Click here to view fulltext PDF

      Permanent link:

    • Keywords


      Bengali tweets; hindi tweets; sentiment polarity detection; machine learning; ensemble; classifier combination; deep learning

    • Abstract


      Sentiment analysis is an essential step for analysing social media texts such as tweets and other posts on the various micro-blogging sites. The basic step of sentiment analysis is sentiment polarity detection, which identifies whether an input piece of social media text is positive, negative or neutral. In this paper, wepresent an approach that combines heterogeneous classifiers in an ensemble for sentiment polarity detection in Bengali and Hindi tweets. Our proposed method constructs an ensemble of three different base classifiers where the feature set for each base classifier is different from each other. We have also incorporated an external knowledge base called sentiment lexicon to augment tweet words with sentiment polarity information retrieved from the sentiment lexicon. Experimental results show the effectiveness of our proposed heterogeneous ensemble model for sentiment polarity detection for both Bengali and Hindi languages. It has been shown that our system outperforms other existing Bengali and Hindi sentiment classification systems to which it is compared.

    • Author Affiliations



      1. Department of Computer Science and Engineering, Jadavpur University, Kolkata, India
    • Dates

  • Sadhana | News

    • Editorial Note on Continuous Article Publication

      Posted on July 25, 2019

      Click here for Editorial Note on CAP Mode

© 2021-2022 Indian Academy of Sciences, Bengaluru.