TEXTUAL EMOTION RECOGNITION FOR ENHANCING SOCIAL PRESENCE IN ONLINE COMMUNICATIONS

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dc.contributor.author Njeri, E.
dc.contributor.author Kimani, S.
dc.contributor.author Kimwele, M.
dc.date.accessioned 2017-06-22T12:33:51Z
dc.date.available 2017-06-22T12:33:51Z
dc.date.issued 2017-06-22
dc.identifier.isbn 9966 923 28 4
dc.identifier.uri http://journals.jkuat.ac.ke/index.php/jscp/article/view/1076
dc.identifier.uri http://hdl.handle.net/123456789/3367
dc.description.abstract This paper presents an emotion recognition model that assesses the affective content from textual messages. The focus is on emotion recognition from online non verbal textual symbols of vocalics (e.g., the use of capitals and use of punctuation “!” and “!!s!” or “?” and “???”, length of response, etc), and those of chronemics (e.g. time to respond to an email or to a discussion posting, the length of the response, etc) that are used in text. The model employs a supervised machine learning approach to recognize six basic emotions (anger, disgust, fear, happiness, sadness and surprise) using an emotion-annotated training set composed of online chat messages exchanged by university students. Naive Bayes algorithm is used to classify messages to the mentioned emotional classes based on a variety of features. The model also takes into consideration the evolving language particularly the language used in online chat where people tend to use an informal style of writing. Observations from informal experiments comparing a chat system integrated with the emotion estimation model with a conventional chat system suggest that an online interface that conveys emotional information helps online users to interact with each other more efficiently thus providing an enhanced social presence. en_US
dc.description.sponsorship JKUAT en_US
dc.language.iso en en_US
dc.publisher JKUAT en_US
dc.relation.ispartofseries Proceedings of the 2013 JKUAT Scientific Technological and Industrialization Conference;14-15th November 2013
dc.subject Affect recognition from text en_US
dc.subject emotions en_US
dc.subject text symbols en_US
dc.subject social presence en_US
dc.subject computer mediated communication en_US
dc.subject JKUAT en_US
dc.subject Kenya en_US
dc.title TEXTUAL EMOTION RECOGNITION FOR ENHANCING SOCIAL PRESENCE IN ONLINE COMMUNICATIONS en_US
dc.type Article en_US


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