A review of emotion sensing: categorization models and algorithms
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This paper reviews and discusses existing emotion categorization models for emotion analysis and proposes methods that enhance existing emotion research.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.read more
Citations
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A Systematic Review on Affective Computing: Emotion Models, Databases, and Recent Advances
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TL;DR: This systematic overview of affective computing systematically review recent advances, survey and taxonomize state-of-the-art unimodal affects recognition and multimodal affective analysis in terms of their detailed architectures and performances, and concludes with an indication of the most promising future directions.
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