Affective computing scholarship and the rise of China: a view from 25 years of bibliometric data
Abstract Affective computing, also known as emotional artificial intelligence (AI), is an emerging and cutting-edge field of AI research. It draws on computer science, engineering, psychology, physiology, and neuroscience to computationally model, track, and classify human emotions and affective sta...
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2021
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oai:doaj.org-article:a6bd6bd0f8a543a29474cc0ba93863252021-11-21T12:28:29ZAffective computing scholarship and the rise of China: a view from 25 years of bibliometric data10.1057/s41599-021-00959-82662-9992https://doaj.org/article/a6bd6bd0f8a543a29474cc0ba93863252021-11-01T00:00:00Zhttps://doi.org/10.1057/s41599-021-00959-8https://doaj.org/toc/2662-9992Abstract Affective computing, also known as emotional artificial intelligence (AI), is an emerging and cutting-edge field of AI research. It draws on computer science, engineering, psychology, physiology, and neuroscience to computationally model, track, and classify human emotions and affective states. While the US once dominated the field in terms of research and citation from 1995–2015, China is now emerging as a global contender in research output, claiming second place for the most cited country from 2016–2020. This article maps the rhizomatic growth and development of scientific publications devoted to emotion-sensing AI technologies. It employs a bibliometric analysis that identifies major national contributors and international alliances in the field over the past 25 years. Contrary to the ongoing political rhetoric of a new Cold War, we argue that there are in fact vibrant AI research alliances and ongoing collaborations between the West and China, especially with the US, despite competing interests and ethical concerns. Our observations of historical data indicate two major collaborative networks: the “US/Asia-Pacific cluster” consisting of the US, China, Singapore, Japan and the “European” cluster of Germany, the UK, and the Netherlands. Our analysis also uncovers a major shift in the focus of affective computing research away from diagnosis and detection of mental illnesses to more commercially viable applications in smart city design. The discussion notes the state-of-the-art techniques such as the ensemble method of symbolic and sub-symbolic AI as well as the absence of Russia in the list of top countries for scientific output.Manh-Tung HoPeter MantelloHong-Kong T. NguyenQuan-Hoang VuongSpringer NaturearticleHistory of scholarship and learning. The humanitiesAZ20-999Social SciencesHENHumanities & Social Sciences Communications, Vol 8, Iss 1, Pp 1-14 (2021) |
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History of scholarship and learning. The humanities AZ20-999 Social Sciences H |
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History of scholarship and learning. The humanities AZ20-999 Social Sciences H Manh-Tung Ho Peter Mantello Hong-Kong T. Nguyen Quan-Hoang Vuong Affective computing scholarship and the rise of China: a view from 25 years of bibliometric data |
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Abstract Affective computing, also known as emotional artificial intelligence (AI), is an emerging and cutting-edge field of AI research. It draws on computer science, engineering, psychology, physiology, and neuroscience to computationally model, track, and classify human emotions and affective states. While the US once dominated the field in terms of research and citation from 1995–2015, China is now emerging as a global contender in research output, claiming second place for the most cited country from 2016–2020. This article maps the rhizomatic growth and development of scientific publications devoted to emotion-sensing AI technologies. It employs a bibliometric analysis that identifies major national contributors and international alliances in the field over the past 25 years. Contrary to the ongoing political rhetoric of a new Cold War, we argue that there are in fact vibrant AI research alliances and ongoing collaborations between the West and China, especially with the US, despite competing interests and ethical concerns. Our observations of historical data indicate two major collaborative networks: the “US/Asia-Pacific cluster” consisting of the US, China, Singapore, Japan and the “European” cluster of Germany, the UK, and the Netherlands. Our analysis also uncovers a major shift in the focus of affective computing research away from diagnosis and detection of mental illnesses to more commercially viable applications in smart city design. The discussion notes the state-of-the-art techniques such as the ensemble method of symbolic and sub-symbolic AI as well as the absence of Russia in the list of top countries for scientific output. |
format |
article |
author |
Manh-Tung Ho Peter Mantello Hong-Kong T. Nguyen Quan-Hoang Vuong |
author_facet |
Manh-Tung Ho Peter Mantello Hong-Kong T. Nguyen Quan-Hoang Vuong |
author_sort |
Manh-Tung Ho |
title |
Affective computing scholarship and the rise of China: a view from 25 years of bibliometric data |
title_short |
Affective computing scholarship and the rise of China: a view from 25 years of bibliometric data |
title_full |
Affective computing scholarship and the rise of China: a view from 25 years of bibliometric data |
title_fullStr |
Affective computing scholarship and the rise of China: a view from 25 years of bibliometric data |
title_full_unstemmed |
Affective computing scholarship and the rise of China: a view from 25 years of bibliometric data |
title_sort |
affective computing scholarship and the rise of china: a view from 25 years of bibliometric data |
publisher |
Springer Nature |
publishDate |
2021 |
url |
https://doaj.org/article/a6bd6bd0f8a543a29474cc0ba9386325 |
work_keys_str_mv |
AT manhtungho affectivecomputingscholarshipandtheriseofchinaaviewfrom25yearsofbibliometricdata AT petermantello affectivecomputingscholarshipandtheriseofchinaaviewfrom25yearsofbibliometricdata AT hongkongtnguyen affectivecomputingscholarshipandtheriseofchinaaviewfrom25yearsofbibliometricdata AT quanhoangvuong affectivecomputingscholarshipandtheriseofchinaaviewfrom25yearsofbibliometricdata |
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