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Emotion Recognition from Text-A Survey


Affiliations
1 Pune Institute of Computer Technology, India
2 Department of Information Technology, Pune University of Computer Technology, India
     

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Emotion is a very important facet of human behaviour which affect on the way people interact in the society. In recent year many methods on human emotions recognition have been published such as recognizing emotion from facial expression and gestures, speech and by written text. This paper focuses on classification of emotion expressed by the online text, based on pre-defined list of emotion. The collection of dataset is the basic step, which is collected from the various sources like daily used sentences, user status from various social networking websites such as facebook and twitter. Using this data set we target only on the keywords that show human emotions. The targeted keywords are extracted from the dataset and translated into the format which can be processed by the classifier to finally generate the Predicting model which is further compared by the test dataset to give the emotions in the input sentences or documents.

Keywords

Affective Computing, Classification, Document Categorization, Emotion Detections.
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  • Emotion Recognition from Text-A Survey

Abstract Views: 245  |  PDF Views: 2

Authors

Pallavi D. Phalke
Pune Institute of Computer Technology, India
M. Emmanuel
Department of Information Technology, Pune University of Computer Technology, India

Abstract


Emotion is a very important facet of human behaviour which affect on the way people interact in the society. In recent year many methods on human emotions recognition have been published such as recognizing emotion from facial expression and gestures, speech and by written text. This paper focuses on classification of emotion expressed by the online text, based on pre-defined list of emotion. The collection of dataset is the basic step, which is collected from the various sources like daily used sentences, user status from various social networking websites such as facebook and twitter. Using this data set we target only on the keywords that show human emotions. The targeted keywords are extracted from the dataset and translated into the format which can be processed by the classifier to finally generate the Predicting model which is further compared by the test dataset to give the emotions in the input sentences or documents.

Keywords


Affective Computing, Classification, Document Categorization, Emotion Detections.