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Hindi EmotionNet: A Scalable Emotion Lexicon for Sentiment Classification of Hindi Text

Published:07 June 2020Publication History
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Abstract

In this study, we create an emotion lexicon for the Hindi language called Hindi EmotionNet. It can assign emotional affinity to words in IndoWordNet. This lexicon contains 3,839 emotion words, with 1,246 positive and 2,399 negative words. We also introduce ambiguous (217 words) and neutral (95 words) emotions to Hindi. Positive emotion words covered nine types of positive emotions, negative emotion words covered eleven types of negative emotions, ambiguous emotion words covered seven types of ambiguous emotions, and neutral emotion words covered two neutral emotions. The proposed Hindi EmotionNet was then applied to opinion classification and emotion classification. We introduce a centrality-based approach for emotion classification that uses degree, closeness, betweenness, and page rank as centrality measures. We also created a dataset of Hindi based on screenplays, stories, and blogs in the language. We translated emotion data from SemEval 2017 into Hindi for further comparison. The proposed approach delivered promising results on opinion and emotion classification, with an accuracy of 85.78% for the former and 75.91% for the latter.

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    • Published in

      cover image ACM Transactions on Asian and Low-Resource Language Information Processing
      ACM Transactions on Asian and Low-Resource Language Information Processing  Volume 19, Issue 4
      July 2020
      291 pages
      ISSN:2375-4699
      EISSN:2375-4702
      DOI:10.1145/3391538
      Issue’s Table of Contents

      Copyright © 2020 ACM

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 7 June 2020
      • Online AM: 7 May 2020
      • Revised: 1 February 2020
      • Accepted: 1 February 2020
      • Received: 1 January 2019
      Published in tallip Volume 19, Issue 4

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