Sentiment Analysis on Demonetization using SVM

Authors

  • Aggarwal U Department of Computer Science, Jagannath University, Bahadurgar, India
  • Aggarwal G Department of Computer Science, Jagannath University, NCR, Haryana, India

Keywords:

Sentiment Analysis, Classification, SVM, Machine learning

Abstract

Sentiment Analysis is an area of interest over the last decade. The social networking is one of the important sources for users to know express the views on different organizations, product, and politics. In this work, we focus on mining sentiments and analyzing public review on demonetization. Demonetization was one of the biggest political decisions taken in year 2016 which affected each and every person in India. In demonetization 500 and 1000 rupees currency was banned more over a new 2000 rupees note was introduced in currency. This affected economy, market and exposed black money also. We worked on twitter data for demonetization. It aims to analyzing positive and negative of tweets reviews as sentiment classification task. The raw dataset collected is preprocessed by cleaning unwanted text, tokenized and used for polarity classification of data corpus.

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Published

2025-11-11

How to Cite

[1]
U. Aggarwal and G. Aggarwal, “Sentiment Analysis on Demonetization using SVM”, Int. J. Comp. Sci. Eng., vol. 5, no. 6, pp. 183–187, Nov. 2025.

Issue

Vol. 5 No. 6 (2017): IJCSE June Edition

Section

Research Article

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