Systematic review of computational modeling of mood and emotion

n the recent years, more studies that aim to make computers understand, experience and respond to affects accordingly through computational models have been widely researched. Although many studies have defined and distinguished the words affect, mood and emotion, such terms are still used interchan...

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Bibliographic Details
Main Authors: Handayani, Dini, Yaacob, Hamwira Sakti, Abdul Rahman, Abdul Wahab, Sediono, Wahju, Shah, Asadullah
Format: Conference or Workshop Item
Language:English
English
Published: IEEE 2014
Subjects:
Online Access:http://irep.iium.edu.my/39657/
http://irep.iium.edu.my/39657/
http://irep.iium.edu.my/39657/
http://irep.iium.edu.my/39657/7/39657-Systematic%20Review%20of%20Computational%20Modeling%20of%20Mood%20and%20Emotion.pdf
http://irep.iium.edu.my/39657/8/39657-Systematic%20Review%20of%20Computational%20Modeling%20of%20Mood%20and%20Emotion_SCOPUS.pdf
Description
Summary:n the recent years, more studies that aim to make computers understand, experience and respond to affects accordingly through computational models have been widely researched. Although many studies have defined and distinguished the words affect, mood and emotion, such terms are still used interchangeably. Thus, in this study, a systematic literature review was implemented to summarize and evaluate the current states of the arts on computational modeling of mood. From three online databases including IEEE Xplore, ScienceDirect and Springer Link, 825 scientific articles were extracted. Furthermore, through the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta Analyses) Statement, 9 articles were selected for the review. These resulting articles were reviewed based on several categories including the aim of the study, the study population, the measurement of mood, the basic emotion dimension, and proposed computational model, as well as evaluation. As a result, the systematic literature review has provided a good starting point in the study of the computational modeling of mood and emotion.