Title: Global affective computing research in the period 1997-2017: a bibliometric analysis

Authors: Maria Helena Pestana; Wan-Chen Wang; Luiz Abel Moutinho

Addresses: University Institute of Lisbon (ISCTE-IUL), Av. Forças Armadas, 1649-026, Lisbon, Portugal; Research and Education Unit on Ageing (UNIFAI, ICBAS, UP), Portugal; Universidade Europeia-Laureate International University, Quinta do Bom Nome, Estrada da Correia, 53, 1500-210-Lisboa, Portugal ' Feng Chia University, Taiwan, China ' University Suffolk, Ipswich, England; University of South Pacific Suva, Laucala Campus, Suva, Fiji

Abstract: Notable fallouts in marketing and financial market prediction have raised the interest by the scientific community and the business world in affective computing (AfC). Automatically recognising and responding to a user's affective states, AfC shows a great potential to improve companies capabilities of customer relationship management. The aim of this study is to evaluate this field of research during the last 20 years, identifying for one side its evolution, by the major publications, citations, journals, authors, productive countries, productive institutions, and collaboration patterns; and for another side, identifying its trends through the analysis of research hotspots, burst keywords, and areas of research done so far. This bibliometric analysis is based on the science citation index expanded (SCI-E), from the Institute of Scientific Information Web-of-Science, which is now firmly established as an integral part of research evaluation methodology especially within the scientific and applied fields. The results show a significant 4.19 rate of growth in AfC, doubling the number of publications in 4.02 years time. This field of interest is paving the way for creativity and innovation, and provides opportunities for its greater development.

Keywords: affective computing; bibliometric analysis; scientific outputs; collaboration network; research hotpots; research trends.

DOI: 10.1504/IJMDA.2018.096076

International Journal of Multivariate Data Analysis, 2018 Vol.1 No.4, pp.348 - 370

Available online: 05 Nov 2018 *

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