A HYBRID APPROACH FOR POLARITY SHIFT DETECTION

ICTACT Journal on Soft Computing

卷:7

Prem Balani¹  Michele Mistry¹ 

[1] G.H. Patel College of Engineering and Technology, India;

关键词: Sentiment Analysis;    Sentiment Classification;    Polarity Shift;    Natural Language Processing;    Lexicon;   

DOI  :  10.21917/ijsc.2017.0211

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown