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Multi-class Classification of Sentiments in Hindi Sentences Based on Intensities

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Towards Extensible and Adaptable Methods in Computing

Abstract

Sentiment analysis is a field of Natural Language Processing and Information Retrieval. Generally, the text has been classified as neutral, negative or positive. But, in this work, Hindi sentences have been classified among 5-classes and 7-classes based on their intensities (e.g. weakly positive, strongly positive, weakly negative and strongly negative). In this work, we have taken NLP approach to classify Hindi sentences taken from tagged movie corpora and tourism corpora created by IIT Bombay. In this work, language independent and dependent features both have been used for classification. A new term weighting scheme has been proposed in this work. Features used are unigrams and bigrams. A senti-lexicon Hindi-SentiWordNet has also been used. To implement this, hybrid fuzzy neural network (FNN) method has been used and its result has been compared with Naïve Bayes, SVM and MaxEnt. This approach has given the promising results.

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  1. 1.

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Acknowledgements

This work is supported by CSIR with file no. 09/263(1049)/2015-EMR-I

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Authors and Affiliations

  1. School of Computer and Systems Sciences, JNU, New Delhi, Delhi, India

    Kanika Garg & D. K. Lobiyal

Authors
  1. Kanika Garg
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  2. D. K. Lobiyal
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Corresponding author

Correspondence to Kanika Garg .

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Netaji Subhas Institute of Technology, University of Delhi, New Delhi, India

    Shampa Chakraverty

  2. SAP Canada, Waterloo, ON, Canada

    Anil Goel

  3. Department of Electrical and Information Engineering, Covenant University, Ota, Nigeria

    Sanjay Misra

Appendix

Appendix

This section contains all the Hindi sentences included in this paper and their corresponding English translation.

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Garg, K., Lobiyal, D.K. (2018). Multi-class Classification of Sentiments in Hindi Sentences Based on Intensities. In: Chakraverty, S., Goel, A., Misra, S. (eds) Towards Extensible and Adaptable Methods in Computing. Springer, Singapore. https://doi.org/10.1007/978-981-13-2348-5_19

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  • DOI: https://doi.org/10.1007/978-981-13-2348-5_19

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  • Online ISBN: 978-981-13-2348-5

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