Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/162012
Title: A review of emotion sensing: categorization models and algorithms
Authors: Wang, Zhaoxia
Ho, Seng-Beng
Cambria, Erik
Keywords: Engineering::Computer science and engineering
Issue Date: 2020
Source: Wang, Z., Ho, S. & Cambria, E. (2020). A review of emotion sensing: categorization models and algorithms. Multimedia Tools and Applications, 79(47-48), 35553-35582. https://dx.doi.org/10.1007/s11042-019-08328-z
Journal: Multimedia Tools and Applications
Abstract: Sentiment analysis consists in the identification of the sentiment polarity associated with a target object, such as a book, a movie or a phone. Sentiments reflect feelings and attitudes, while emotions provide a finer characterization of the sentiments involved. With the huge number of comments generated daily on the Internet, besides sentiment analysis, emotion identification has drawn keen interest from different researchers, businessmen and politicians for polling public opinions and attitudes. This paper reviews and discusses existing emotion categorization models for emotion analysis and proposes methods that enhance existing emotion research. We carried out emotion analysis by inviting experts from different research areas to produce comprehensive results. Moreover, a computational emotion sensing model is proposed, and future improvements are discussed in this paper.
URI: https://hdl.handle.net/10356/162012
ISSN: 1380-7501
DOI: 10.1007/s11042-019-08328-z
Rights: © 2019 Springer Science+Business Media, LLC, part of Springer Nature. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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