A review of techniques for sentiment analysis Of Twitter data

Author

Bhuta, Sagar ; Doshi, Aayushi ; Doshi, Uehit ; Narvekar, Meera

Author_Institution

Dwarkadas J. Sanghvi Coll. of Eng., Mumbai, India

fYear

2014

fDate

7-8 Feb. 2014

Firstpage

583

Lastpage

591

Abstract

There has been a rapid increase in the use of social networking websites in the last few years. People most conveniently express their views and opinions on a wide array of topics via such websites. Sentiment analysis of such data which comprises of people´s views is very important in order to gauge public opinion on a particular topic of interest. This paper reviews a number of techniques, both lexicon-based approaches as well as learning based methods that can be used for sentiment analysis of text. In order to adapt these techniques for sentiment analysis of data procured from one of the social networking websites, Twitter, a number of issues and challenges need to be addressed, which are put forward in this paper.

Keywords

learning (artificial intelligence); maximum entropy methods; pattern classification; social networking (online); support vector machines; text analysis; Twitter data; learning based methods; lexicon-based approach; public opinion; sentiment analysis; social networking Web sites; text analysis; Niobium; Noise measurement; Sentiment Analysis; Social Networks; Supervised Learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Issues and Challenges in Intelligent Computing Techniques (ICICT), 2014 International Conference on

Conference_Location

Ghaziabad

Type

conf

DOI

10.1109/ICICICT.2014.6781346

Filename

6781346