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Aspect-based Sentiment Analysis using Dependency Parsing

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Published:13 December 2021Publication History
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Abstract

In this paper, an aspect-based Sentiment Analysis (SA) system for Hindi is presented. The proposed system assigns a separate sentiment towards the different aspects of a sentence as well as it evaluates the overall sentiment expressed in a sentence. In this work, Hindi Dependency Parser (HDP) is used to determine the association between an aspect word and a sentiment word (using Hindi SentiWordNet) and works on the idea that closely connected words come together to express a sentiment about a certain aspect. By generating a dependency graph, the system assigns the sentiment to an aspect having a minimum distance between them and computes the overall polarity of the sentence. The system achieves an accuracy of 83.2% on a corpus of movie reviews and its results are compared with baselines as well as existing works on SA. From the results, it has been observed that the proposed system has the potential to be used in emerging applications like SA of product reviews, social media analysis, etc.

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          cover image ACM Transactions on Asian and Low-Resource Language Information Processing
          ACM Transactions on Asian and Low-Resource Language Information Processing  Volume 21, Issue 3
          May 2022
          413 pages
          ISSN:2375-4699
          EISSN:2375-4702
          DOI:10.1145/3505182
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          Publication History

          • Published: 13 December 2021
          • Accepted: 1 September 2021
          • Revised: 1 May 2021
          • Received: 1 February 2021
          Published in tallip Volume 21, Issue 3

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