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Emotion Recognition in Poetry Using Ensemble of Classifiers

  • P. S. SreejaEmail author
  • G. S. Mahalakshmi
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 922)

Abstract

The poetic language is more expressive compared to ordinary text, which presents more challenges for emotion recognition. This paper presents an innovative approach to recognize emotion from poems. The proposed work is the first attempt to identify emotions from English poems. To accomplish the objective, we have created a corpus Poem Emotion Recognition Corpus [PERC] consists of 736 prominent poems of various poets. In this work, the emotion is classified into nine categories such as Love, Anger, Hate, Sadness, Joy, Surprise, Peace, Courage and Fear based on Indian classical Navarasa. The proposed emotion recognition model uses a novel ensemble classifier schema based on SVM, Logistic regression, NB Classifier, and Emotion Modifier Preserved Vector Space Model. The results show that the proposed model achieves satisfactory precision, Recall and F-measure in recognizing emotions from poems.

Keywords

Poem Emotion Recognition Corpus Poem emotion analysis Support Vector Machine Logistic Regression Ensemble model Naive Bayes Classifier Vector Space Model Natural language processing 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Hindustan Institute of Technology and ScienceChennaiIndia
  2. 2.Anna UniversityChennaiIndia

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