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Sentiment Analysis of Twitter Data Using Text Classification And Clustering

Kumari Ashmita Sinha1 , Maanasa VKP2 , Nikhitha SP3 , Ramya S4 , Mangala CN5

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-15 , Page no. 69-72, May-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7si15.6972

Online published on May 16, 2019

Copyright © Kumari Ashmita Sinha, Maanasa VKP, Nikhitha SP, Ramya S, Mangala CN . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Kumari Ashmita Sinha, Maanasa VKP, Nikhitha SP, Ramya S, Mangala CN, “Sentiment Analysis of Twitter Data Using Text Classification And Clustering,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.15, pp.69-72, 2019.

MLA Style Citation: Kumari Ashmita Sinha, Maanasa VKP, Nikhitha SP, Ramya S, Mangala CN "Sentiment Analysis of Twitter Data Using Text Classification And Clustering." International Journal of Computer Sciences and Engineering 07.15 (2019): 69-72.

APA Style Citation: Kumari Ashmita Sinha, Maanasa VKP, Nikhitha SP, Ramya S, Mangala CN, (2019). Sentiment Analysis of Twitter Data Using Text Classification And Clustering. International Journal of Computer Sciences and Engineering, 07(15), 69-72.

BibTex Style Citation:
@article{Sinha_2019,
author = {Kumari Ashmita Sinha, Maanasa VKP, Nikhitha SP, Ramya S, Mangala CN},
title = {Sentiment Analysis of Twitter Data Using Text Classification And Clustering},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {07},
Issue = {15},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {69-72},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1203},
doi = {https://doi.org/10.26438/ijcse/v7i15.6972}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i15.6972}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1203
TI - Sentiment Analysis of Twitter Data Using Text Classification And Clustering
T2 - International Journal of Computer Sciences and Engineering
AU - Kumari Ashmita Sinha, Maanasa VKP, Nikhitha SP, Ramya S, Mangala CN
PY - 2019
DA - 2019/05/16
PB - IJCSE, Indore, INDIA
SP - 69-72
IS - 15
VL - 07
SN - 2347-2693
ER -

           

Abstract

Information and data has always been consideredas the lifeline to run any business. The stability of an organization, the growth of the business, the profit gained or the loss suffered, all these factors depend on the information gained about the market trends and also most importantly public opinion. The sentiments of the people are therefore considered as the most crucial data that the organizations use in order to take effective decisions with minimum risk.In this paper we gather data from a type of social media that is twitter. This is because the public nowadays express their opinions and their feedbacks largely to through social media. In this paper we attempt to perform sentiment analysis using text classification by Naïve Bayes and text Clustering by K-means.

Key-Words / Index Term

Twitter, Sentiment Analysis, Social Media, Naïve Bayes, K-means

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