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A Review on Sentiment Analysis of Twitter Data

by Preeti Mehrotra, Devashri Anwekar, Amit Saxena
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 185 - Number 28
Year of Publication: 2023
Authors: Preeti Mehrotra, Devashri Anwekar, Amit Saxena
10.5120/ijca2023923025

Preeti Mehrotra, Devashri Anwekar, Amit Saxena . A Review on Sentiment Analysis of Twitter Data. International Journal of Computer Applications. 185, 28 ( Aug 2023), 1-5. DOI=10.5120/ijca2023923025

@article{ 10.5120/ijca2023923025,
author = { Preeti Mehrotra, Devashri Anwekar, Amit Saxena },
title = { A Review on Sentiment Analysis of Twitter Data },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2023 },
volume = { 185 },
number = { 28 },
month = { Aug },
year = { 2023 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume185/number28/32865-2023923025/ },
doi = { 10.5120/ijca2023923025 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:27:14.355016+05:30
%A Preeti Mehrotra
%A Devashri Anwekar
%A Amit Saxena
%T A Review on Sentiment Analysis of Twitter Data
%J International Journal of Computer Applications
%@ 0975-8887
%V 185
%N 28
%P 1-5
%D 2023
%I Foundation of Computer Science (FCS), NY, USA
Abstract

“Sentiment analysis is a sort of natural language processing” for measuring the sentiment of the public regarding a given product or issue. Sentiment analysis, that is often called “opinion mining”, includes in constructing a system to gather and analyse opinions about product stated through comments, reviews, blog posts or tweets. “Sentiment analysis” may be valuable in numerous ways. In reality, it has moved from computer science to the management sciences as well as social sciences because to its relevance to society and business as a whole. There has been much of effort in the topic of “sentiment analysis” of the twitter data.  This study focuses largely on “sentiment analysis” of the twitter data that is beneficial to assess the information in the tweets where views are very unstructured, varied and are either “negative, positive or neutral” in certain situations. In this work, we give a survey and a current methodology for the opinion mining.

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Index Terms

Computer Science
Information Sciences

Keywords

Sentiment Analysis Text Mining.

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