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Natural Language Processing Based Sentimental Analysis of Hindi (SAH) Script an Optimization Approach

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Abstract

Sentimental analysis is one of the most common applications of Natural Language Processing (NLP). Sentiment analysis, the term itself refers to identify the emotions and opinions of people through written text. It is concerned with information extraction from any text based on the polarity in social behavior whether it may be positive, negative or neutral. This paper presents a practical dynamic approach on to find the polarity of any sentence and analyse the opinion of the particular sentence. The proposed Sentimental Analysis of Hindi (SAH) script have adopted two different classifier Naïve Bayes Classifier and Decision Tree Classifier is used for the text extraction. The positive, neutral and negative result validation shows a comparative result of sentimental analysis.

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Authors and Affiliations

  1. Department of Computer Science & Engineering, Madanapalle Institute of Technology & Science, Madanapalle, India

    Hewan Shrestha & Chandramohan Dhasarathan

  2. Department of Computer Science and Engineering, Vignan’s Foundation for Science Technology & Research (Deemed to be University), Guntur, Andhra Pradesh, India

    Shanmugam Munisamy

  3. School of Computing Science & Engineering, VIT Bhopal University, Bhopal, India

    Amudhavel Jayavel

Authors
  1. Hewan Shrestha
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  2. Chandramohan Dhasarathan
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  3. Shanmugam Munisamy
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  4. Amudhavel Jayavel
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Correspondence to Chandramohan Dhasarathan.

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Shrestha, H., Dhasarathan, C., Munisamy, S. et al. Natural Language Processing Based Sentimental Analysis of Hindi (SAH) Script an Optimization Approach. Int J Speech Technol 23, 757–766 (2020). https://doi.org/10.1007/s10772-020-09730-x

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  • DOI: https://doi.org/10.1007/s10772-020-09730-x

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