System for fine-grained sentiment analysis using a hybrid model and method thereof

Abstract

The present invention discloses a system and method for fine-grained sentiment analysis using a hybrid model which is extensible to multiple languages, wherein the system (100) comprises a polarity detection module (101) for continuously detecting the positive sentiments, negative sentiments, and neutral sentiments of one or more sentences in a document. Further, a sentiment classification module (102) predicts the intensity and classifies positive sentiments and negative sentiments into one or more pre-defined sentiment classes, wherein the sentiment classification module (102) provides a reference sentiment interval for the classified sentences in the document. Furthermore, a length-based sentiment scoring module (103) continuously assigns a score to the classified sentences in the document ranging between −s to +s, wherein −s indicates extremely negative sentiment of the sentence and +s indicates extremely positive sentiment of the sentence.

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