A HYBRID APPROACH FOR POLARITY SHIFT DETECTION

Abstract
Now-a-days sentiment analysis has become a hot research area. With the increasing use of internet, people express their views by using social media, blogs, etc. So there is a dire need to analyze people’s opinions. Sentiment classification is the main task of sentiment analysis. But while classifying sentiments, the problem of polarity shift occurs. Polarity shift is considered as a very crucial problem. Polarity shift changes a text from positive to negative and vice versa. In this paper, a hybrid approach is proposed for polarity shift detection of negation (explicit and implicit) and contrast. The hybrid approach consists of a rule-based approach for detecting explicit negation and contrast and a lexicon called SentiWordNet for detecting implicit negation. The proposed approach outperforms its baselines.

Authors
Michele Mistry, Prem Balani
G.H. Patel College of Engineering and Technology, India

Keywords
Sentiment Analysis, Sentiment Classification, Polarity Shift, Natural Language Processing, Lexicon
Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 7 , Issue: 4 )
Date of Publication :
July 2017
DOI :

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