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Opinion Mining of GST Implementation using Supervised Machine Learning Approach

by Nandini Tomar, Ritesh Srivastava, Bindiya Ahuja
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 180 - Number 49
Year of Publication: 2018
Authors: Nandini Tomar, Ritesh Srivastava, Bindiya Ahuja
10.5120/ijca2018917283

Nandini Tomar, Ritesh Srivastava, Bindiya Ahuja . Opinion Mining of GST Implementation using Supervised Machine Learning Approach. International Journal of Computer Applications. 180, 49 ( Jun 2018), 1-7. DOI=10.5120/ijca2018917283

@article{ 10.5120/ijca2018917283,
author = { Nandini Tomar, Ritesh Srivastava, Bindiya Ahuja },
title = { Opinion Mining of GST Implementation using Supervised Machine Learning Approach },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2018 },
volume = { 180 },
number = { 49 },
month = { Jun },
year = { 2018 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume180/number49/29566-2018917283/ },
doi = { 10.5120/ijca2018917283 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:03:59.868375+05:30
%A Nandini Tomar
%A Ritesh Srivastava
%A Bindiya Ahuja
%T Opinion Mining of GST Implementation using Supervised Machine Learning Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 180
%N 49
%P 1-7
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Sentiment Analysis is a way to determine the emotions behind social media discussions. Analyzing social data plays a vital role in knowing people’s behavior about an entity or event occurring in the society. Sentiment analysis is widely used in a variety of applications like classifying, summarizing and aggregating reviews from the massive amount of unstructured data that may be available from customer comments, blogs, feedback and reviews on any product or social issue. The Goods & Service Tax(GST) was debated a lot in the social network as it impacts every citizen of India and there was a state of confusion among people about this amendment in the taxation system. If this state of people can be determined, then it can help in identifying how effectively GST scheme is executing. In this paper, we present Sentiment Analysis (SA) of GST by using the textual content of Twitter to determine the public opinion about GST.

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Index Terms

Computer Science
Information Sciences

Keywords

Sentiment Analysis GST Supervised Machine Learning.

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