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Reseach Article

Multi-Class Twitter Emotion Classification: A New Approach

by R C Balabantaray, Mudasir Mohammad, Nibha Sharma
International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 4 - Number 1
Year of Publication: 2012
Authors: R C Balabantaray, Mudasir Mohammad, Nibha Sharma

R C Balabantaray, Mudasir Mohammad, Nibha Sharma . Multi-Class Twitter Emotion Classification: A New Approach. International Journal of Applied Information Systems. 4, 1 ( September 2012), 48-53. DOI=10.5120/ijais12-450651

@article{ 10.5120/ijais12-450651,
author = { R C Balabantaray, Mudasir Mohammad, Nibha Sharma },
title = { Multi-Class Twitter Emotion Classification: A New Approach },
journal = { International Journal of Applied Information Systems },
issue_date = { September 2012 },
volume = { 4 },
number = { 1 },
month = { September },
year = { 2012 },
issn = { 2249-0868 },
pages = { 48-53 },
numpages = {9},
url = { },
doi = { 10.5120/ijais12-450651 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2023-07-05T10:46:52.695108+05:30
%A R C Balabantaray
%A Mudasir Mohammad
%A Nibha Sharma
%T Multi-Class Twitter Emotion Classification: A New Approach
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 4
%N 1
%P 48-53
%D 2012
%I Foundation of Computer Science (FCS), NY, USA

Micro blogging today has become a very popular communication tool among Internet users. Millions of users share opinions on different aspects of life every day. Therefore micro blogging web-sites are rich sources of data for opinion mining and sentiment analysis. Because micro blogging has appeared relatively recently, there are a few research works that are devoted to this topic. In this paper, we are focusing on using Twitter, the most popular micro blogging platform, for the task of Emotion analysis. We will show how to automatically collect a corpus for Emotion analysis and opinion mining purposes and then perform linguistic analysis of the collected corpus and explain discovered phenomena. Using the corpus, we will build a Emotion classifier that will be able to determine the emotion class of the person writing.

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Index Terms

Computer Science
Information Sciences


Emotion Analysis Sentiment Analysis Opinion Mining Text Classification