A review of emotion sensing: categorization models and algorithms

被引:76
作者
Wang, Zhaoxia [1 ]
Ho, Seng-Beng [2 ]
Cambria, Erik [3 ]
机构
[1] Singapore Management Univ, Sch Informat Syst, 80 Stamford Rd, Singapore 178902, Singapore
[2] ASTAR, Inst High Performance Comp, 1 Fusionopolis Way, Singapore 138632, Singapore
[3] Nanyang Technol Univ, Sch Comp Sci & Engn, 50 Nanyang Ave, Singapore 639798, Singapore
关键词
Affective computing; Emotion definition; Emotion categorization model; Sentiment analysis; FRAMEWORK; WORDS;
D O I
10.1007/s11042-019-08328-z
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:35553 / 35582
页数:30
相关论文
共 45 条
  • [1] [Anonymous], 1988, The Cognitive Structure of Emotions
  • [2] Ashkanasy NM, 2008, NEW HORIZ MANAG, P1
  • [3] Detecting implicit expressions of affect in text using EmotiNet and its extensions
    Balahur, Alexandra
    Hermida, Jesus M.
    Montoyo, Andres
    Munoz, Rafael
    [J]. DATA & KNOWLEDGE ENGINEERING, 2013, 88 : 113 - 125
  • [4] Cambria Erik, 2012, Cognitive Behavioural Systems (COST 2012). International Training School. Revised Selected Papers, P144, DOI 10.1007/978-3-642-34584-5_11
  • [5] Cambria E, 2018, AAAI CONF ARTIF INTE, P1795
  • [6] Sentiment Analysis Is a Big Suitcase
    Cambria, Erik
    Poria, Soujanya
    Gelbukh, Alexander
    Thelwall, Mike
    [J]. IEEE INTELLIGENT SYSTEMS, 2017, 32 (06) : 74 - 80
  • [7] The CLSA Model: A Novel Framework for Concept-Level Sentiment Analysis
    Cambria, Erik
    Poria, Soujanya
    Bisio, Federica
    Bajpai, Rajiv
    Chaturvedi, Iti
    [J]. COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING (CICLING 2015), PT II, 2015, 9042 : 3 - 22
  • [8] Sentic PROMs: Application of sentic computing to the development of a novel unified framework for measuring health-care quality
    Cambria, Erik
    Benson, Tim
    Eckl, Chris
    Hussain, Amir
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (12) : 10533 - 10543
  • [9] Cambria E, 2010, LECT NOTES COMPUT SC, V5967, P148
  • [10] Chafale D, 2014, INT J COMPUT SCI ENG, V2