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Pestana, M. H., Wang, W.-C. & Moutinho, L. (2018). The knowledge domain of affective computing: a scientometric review. In Mladen Sokele and Luiz Moutinho (Ed.), Innovative Research Methodologies in Management: Volume II: Futures, Biometrics and Neuroscience Research. (pp. 83-101). Cham: Palgrave Macmillan.

M. H. Pestana et al.,  "The knowledge domain of affective computing: a scientometric review", in Innovative Research Methodologies in Management: Volume II: Futures, Biometrics and Neuroscience Research, Mladen Sokele and Luiz Moutinho, Ed., Cham, Palgrave Macmillan, 2018, pp. 83-101

@incollection{pestana2018_1732203284533,
	author = "Pestana, M. H. and Wang, W.-C. and Moutinho, L.",
	title = "The knowledge domain of affective computing: a scientometric review",
	chapter = "",
	booktitle = "Innovative Research Methodologies in Management: Volume II: Futures, Biometrics and Neuroscience Research",
	year = "2018",
	volume = "",
	series = "",
	edition = "",
	pages = "83-83",
	publisher = "Palgrave Macmillan",
	address = "Cham",
	url = "https://link.springer.com/chapter/10.1007%2F978-3-319-64400-4_4"
}

TY  - CHAP
TI  - The knowledge domain of affective computing: a scientometric review
T2  - Innovative Research Methodologies in Management: Volume II: Futures, Biometrics and Neuroscience Research
AU  - Pestana, M. H.
AU  - Wang, W.-C.
AU  - Moutinho, L.
PY  - 2018
SP  - 83-101
DO  - 10.1007/978-3-319-64400-4_4
CY  - Cham
UR  - https://link.springer.com/chapter/10.1007%2F978-3-319-64400-4_4
AB  - Purpose – The aim of this study is to investigate the bibliographical information about Affective Computing identifying advances, trends, major papers, connections, and areas of research. Design/methodology/approach – A scientometric analysis was applied using CiteSpace, of 5,078 references about Affective Computing imported from the Web-of-Science Core Collection, covering the period of 1991-2016. 
Findings – The most cited, creative, burts  and central references are displayed by areas of research, using metrics and througout-time visualization. 
Research limitations/implications – Interpretation is limited to references retrieved from theWeb-of-Science Core Collection in the fields of management, psychology and marketing. Nevertheless, the richness of bibliographical data obtained, largely compensates this limitation.
Practical implications – The study provides managers with a sound body of knowledge on Affective Computing, with which they can capture general public emotion in respect of their products and services, and on which they can base their marketing intelligence gathering, and strategic planning.
Originality/value – The paper provides new opportunities for companies to enhance their capabilities in terms of customer relationships.
ER  -