Research Article
Twitter Data Sentiment Analysis and Visualization
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 180 - Issue 20 |
| Published: Feb 2018 |
| Authors: R. S. Gound, Priyanka V. Tikone, Shivani S. Suryawanshi, Dipanshu Nagpal |
10.5120/ijca2018916463
|
R. S. Gound, Priyanka V. Tikone, Shivani S. Suryawanshi, Dipanshu Nagpal . Twitter Data Sentiment Analysis and Visualization. International Journal of Computer Applications. 180, 20 (Feb 2018), 14-16. DOI=10.5120/ijca2018916463
@article{ 10.5120/ijca2018916463,
author = { R. S. Gound,Priyanka V. Tikone,Shivani S. Suryawanshi,Dipanshu Nagpal },
title = { Twitter Data Sentiment Analysis and Visualization },
journal = { International Journal of Computer Applications },
year = { 2018 },
volume = { 180 },
number = { 20 },
pages = { 14-16 },
doi = { 10.5120/ijca2018916463 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2018
%A R. S. Gound
%A Priyanka V. Tikone
%A Shivani S. Suryawanshi
%A Dipanshu Nagpal
%T Twitter Data Sentiment Analysis and Visualization%T
%J International Journal of Computer Applications
%V 180
%N 20
%P 14-16
%R 10.5120/ijca2018916463
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Twitter is an online microblogging and social networking platform, which allows users to write short status, updates of maximum length 280 characters. These tweets reflect public sentiment about various topics and events happening. Analysing the public sentiment can help, firms trying to find out the response of their products in the market, predicting political elections and predicting socioeconomic phenomena like stock exchange. Sentiment analysis techniques are widely popular for this purpose. In this paper, we have tried to define and compare various sentiment classification approaches/methods for finding out the sentiments behind the tweet.
References
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