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Exploring sentiment analysis on Twitter data

Publication Type : Conference Paper

Publisher : Eighth International Conference on Contemporary Computing (IC3)

Source : Eighth International Conference on Contemporary Computing (IC3), IEEE (2015)

Url :

Campus : Bengaluru

School : Department of Computer Science and Engineering, School of Engineering

Department : Computer Science, Mathematics

Year : 2015

Abstract : The growing popularity of microblogging websites has transformed these into rich resources for sentiment mining. Even though opinion mining has more than a decade of research to boost about, it is mostly confined to the exploration of formal text patterns like online reviews, news articles etc. Exploration of the challenges offered by informal and crisp microblogging have taken roots but there is scope for a large way ahead. The proposed work aims at developing a hybrid model for sentiment classification that explores the tweet specific features and uses domain independent and domain specific lexicons to offer a domain oriented approach and hence analyze and extract the consumer sentiment towards popular smart phone brands over the past few years. The experiments have proved that the results improve by around 2 points on an average over the unigram baseline.

Cite this Research Publication : Manju Venugopalan and Dr. Deepa Gupta, “Exploring sentiment analysis on Twitter data”, in Eighth International Conference on Contemporary Computing (IC3), 2015.

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