A review of emotion sensing: Categorization models and algorithms

• Main Authors: WANG, Zhaoxia, HO, Seng-Beng, CAMBRIA, Erik
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Affective computing; Emotion definition; Emotion categorization model; Sentiment analysis; Computer Engineering; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/5365; https://ink.library.smu.edu.sg/context/sis_research/article/6369/viewcontent/A_review_of_emotion_sensing__categorization_models_and_algorithms.pdf
• Institution: Singapore Management University

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.