Class sequential rules for emotion extraction from text

Theme of the paper is to develop automatic natural language processing system for extraction of emotions from text. Class Sequential Rules (CSR) are applied for obtaining the patterns. Algorithm developed is dataset independent. Proposed system has been evaluated with popular datasets and results of the proposed system has been compared with existing research work. Experiments found that datasets having high emotive contains and high annotator agreement can have better accuracy of emotion classification.