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A Sentiment Analysis System for Indian Language Tweets

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Mining Intelligence and Knowledge Exploration (MIKE 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9468))

Abstract

This paper reports about our work in the MIKE 2015, Shared Task on Sentiment Analysis in Indian Languages (SAIL) Tweets. We submitted runs for Hindi and Bengali. A multinomial Naïve Bayes based model has been used to implement our system. The system has been trained and tested on the dataset released for SAIL TWEET CONTEST 2015. Our system obtains accuracy of 50.75 %, 48.82 %, 41.20 %, and 40.20 % for Hindi constrained, Hindi unconstrained, Bengali constrained and Bengali unconstrained run respectively.

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Author information

Authors and Affiliations

  1. Computer Science and Engineering Department, Jadavpur University, Kolkata, 700032, India

    Kamal Sarkar

  2. Computer Science and Engineering Department, Hooghly Engineering and Technology College, Hooghly, 712103, India

    Saikat Chakraborty

Authors
  1. Kamal Sarkar
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  2. Saikat Chakraborty
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Corresponding author

Correspondence to Kamal Sarkar .

Editor information

Editors and Affiliations

  1. Norwegian Univ. of Science & Technology, Trondheim, Norway

    Rajendra Prasath

  2. Intl Inst of Info Tech Hyderabad, Hyderabad, India

    Anil Kumar Vuppala

  3. V.H.N.S.N.College (Autonomous), Virudhunagar, Tamil Nadu, India

    T. Kathirvalavakumar

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© 2015 Springer International Publishing Switzerland

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Sarkar, K., Chakraborty, S. (2015). A Sentiment Analysis System for Indian Language Tweets. In: Prasath, R., Vuppala, A., Kathirvalavakumar, T. (eds) Mining Intelligence and Knowledge Exploration. MIKE 2015. Lecture Notes in Computer Science(), vol 9468. Springer, Cham. https://doi.org/10.1007/978-3-319-26832-3_66

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  • DOI: https://doi.org/10.1007/978-3-319-26832-3_66

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26831-6

  • Online ISBN: 978-3-319-26832-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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