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Study of Twitter Sentiment Analysis using Machine Learning Algorithms on Python

by Bhumika Gupta, Monika Negi, Kanika Vishwakarma, Goldi Rawat, Priyanka Badhani
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 165 - Number 9
Year of Publication: 2017
Authors: Bhumika Gupta, Monika Negi, Kanika Vishwakarma, Goldi Rawat, Priyanka Badhani
10.5120/ijca2017914022

Bhumika Gupta, Monika Negi, Kanika Vishwakarma, Goldi Rawat, Priyanka Badhani . Study of Twitter Sentiment Analysis using Machine Learning Algorithms on Python. International Journal of Computer Applications. 165, 9 ( May 2017), 29-34. DOI=10.5120/ijca2017914022

@article{ 10.5120/ijca2017914022,
author = { Bhumika Gupta, Monika Negi, Kanika Vishwakarma, Goldi Rawat, Priyanka Badhani },
title = { Study of Twitter Sentiment Analysis using Machine Learning Algorithms on Python },
journal = { International Journal of Computer Applications },
issue_date = { May 2017 },
volume = { 165 },
number = { 9 },
month = { May },
year = { 2017 },
issn = { 0975-8887 },
pages = { 29-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume165/number9/27604-2017914022/ },
doi = { 10.5120/ijca2017914022 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:12:01.578894+05:30
%A Bhumika Gupta
%A Monika Negi
%A Kanika Vishwakarma
%A Goldi Rawat
%A Priyanka Badhani
%T Study of Twitter Sentiment Analysis using Machine Learning Algorithms on Python
%J International Journal of Computer Applications
%@ 0975-8887
%V 165
%N 9
%P 29-34
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Twitter is a platform widely used by people to express their opinions and display sentiments on different occasions. Sentiment analysis is an approach to analyze data and retrieve sentiment that it embodies. Twitter sentiment analysis is an application of sentiment analysis on data from Twitter (tweets), in order to extract sentiments conveyed by the user. In the past decades, the research in this field has consistently grown. The reason behind this is the challenging format of the tweets which makes the processing difficult. The tweet format is very small which generates a whole new dimension of problems like use of slang, abbreviations etc. In this paper, we aim to review some papers regarding research in sentiment analysis on Twitter, describing the methodologies adopted and models applied, along with describing a generalized Python based approach.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Sentiment analysis Machine Learning Natural Language Processing Python.

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