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A review of emotion sensing: categorization models and algorithms

Multimedia Tools and Applications volume 79, pages 35553–35582 (2020)Cite this article

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.

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Authors and Affiliations

  1. School of Information Systems, Singapore Management University, 80 Stamford Rd, Singapore, 178902, Singapore

    Zhaoxia Wang

  2. Institute of High Performance Computing, A*STAR, 1 Fusionopolis Way, Singapore, 138632, Singapore

    Seng-Beng Ho

  3. School of Computer Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore

    Erik Cambria

Authors
  1. Zhaoxia Wang
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  2. Seng-Beng Ho
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  3. Erik Cambria
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Correspondence to Erik Cambria.

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Appendices

Appendix 1

Table 7 A tree-structured list of emotions described in Shaver model and also featured by Parrott [5, 6]
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Appendix 2

Fig. 3
figure 3

The structure of emotions of the OCC Model [8]

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Appendix 3

Fig. 4
figure 4

A disambiguated, inheritance-based hierarchy of emotions of the OCC Model (Revised OCC Model)

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Appendix 4

Fig. 5
figure 5

Plutchik’s Wheel of Emotions [12, 13]

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Appendix 5

Table 8 Complex Emotions are a composition of basic emotions [12, 13]
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Appendix 6

Table 9 Second-level emotions derived from the combinations of different sentic levels of each of the affective dimensions [20]
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Appendix 7

Table 10 Eleven positive emotions and their causes and consequences [21]
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Appendix 8

Table 11 Eleven negative emotions and their causes and consequences [21]
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Appendix 9

Table 12 Emotion type specifications of the 65 emotions which are extended from reviewed literatures by this research
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Wang, Z., Ho, SB. & Cambria, E. A review of emotion sensing: categorization models and algorithms. Multimed Tools Appl 79, 35553–35582 (2020). https://doi.org/10.1007/s11042-019-08328-z

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  • DOI: https://doi.org/10.1007/s11042-019-08328-z

Keywords

  • Affective computing
  • Emotion definition
  • Emotion categorization model
  • Sentiment analysis