Emotion Analysis of the Text Using Fuzzy Affect Typing over Emotions

Krishna Asawa; Vikrant Verma; Surbhi Dhupar

Context-Aware Systems and Applications. First International Conference, ICCASA 2012, Ho Chi Minh City, Vietnam, November 26-27, 2012, Revised Selected Papers

Research Article

Emotion Analysis of the Text Using Fuzzy Affect Typing over Emotions

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@INPROCEEDINGS{10.1007/978-3-642-36642-0_25,
    author={Krishna Asawa and Vikrant Verma and Surbhi Dhupar},
    title={Emotion Analysis of the Text Using Fuzzy Affect Typing over Emotions},
    proceedings={Context-Aware Systems and Applications. First International Conference, ICCASA 2012, Ho Chi Minh City, Vietnam, November 26-27, 2012, Revised Selected Papers},
    proceedings_a={ICCASA},
    year={2013},
    month={2},
    keywords={Emotion prediction Affective content Hebbian learning Natural language processing},
    doi={10.1007/978-3-642-36642-0_25}
}

Krishna Asawa
Vikrant Verma
Surbhi Dhupar
Year: 2013
Emotion Analysis of the Text Using Fuzzy Affect Typing over Emotions
ICCASA
Springer
DOI: 10.1007/978-3-642-36642-0_25

Krishna Asawa¹^,*, Vikrant Verma¹^,*, Surbhi Dhupar¹^,*

1: JIIT-Noida

*Contact email: krishna.asawa@jiit.ac.in, vik.vikrantverma@gmail.com, surbhi.dhupar11@gmail.com

Abstract

This paper presents a novel approach of emotion estimation in the affective content of the textual messages or dialogues. The individual words in a sentence has been chopped and mapped onto the corresponding affective categories. An affective category is assigned to its membership value in the all basic 5 emotions viz. happy, surprise, neutral, anger and sad. To analyze the affective content effectively we use natural language processing for the lexical analysis and thereafter fuzzy affect typing over basic emotions with the membership modifier rules to handle various modifiers of affective contents. Machine learning based prediction approach has been suggested for new encountered words.

Keywords: Emotion prediction Affective content Hebbian learning Natural language processing

Published: 2013-02-04

: http://dx.doi.org/10.1007/978-3-642-36642-0_25