Implicit Aspect Sentiment Analysis using WordNet for Twitter Social Media Review Identification

Authors

  • Kale Santosh Shivnath, Sonawane Vijay Ramnath

DOI:

https://doi.org/10.17762/msea.v71i4.1838

Abstract

In this paper, we present an implicit sentiment analysis system for Twitter social media reviews based on the WordNet lexical database. The system uses WordNet to identify sentiment-bearing words, along with their associated sentiment aspects and polarities. Aspect sentiment detection is done using a rule-based approach, which is able to detect sentiment polarity for different aspects in a single review. The system is evaluated on a dataset containing 12,000 tweets and is shown to be able to achieve an accuracy of 82%.

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Published

2022-08-19

How to Cite

Kale Santosh Shivnath, Sonawane Vijay Ramnath. (2022). Implicit Aspect Sentiment Analysis using WordNet for Twitter Social Media Review Identification. Mathematical Statistician and Engineering Applications, 71(4), 10145–10152. https://doi.org/10.17762/msea.v71i4.1838

Issue

Section

Articles