A Novel Approach for Detecting Emotion in Text

Objectives: In this paper, we present an experiment, which concerned with detection of emotion class at sentence level. Methods: Approach is based upon combination of both machine leaning and key word based approach. There is a large annotated data set which manually classified a sentence beyond six basic emotions: love, joy, anger, sadness, fear, surprise. Findings: Using annotated data set define an emotion vector of key word in input sentence. Novelty: Using an algorithm calculate the emotion vector of sentence by emotion vector of word. Then on the basis of emotion vector categorized the sentence into appropriate emotion class. Results are shown and found good in comparison to individual approach.