The University of Southampton
University of Southampton Institutional Repository

Science behind AI: the evolution of trend, mobility, and collaboration

Science behind AI: the evolution of trend, mobility, and collaboration
Science behind AI: the evolution of trend, mobility, and collaboration
In this era of interdisciplinary science, many scientific achievements, such as artificial intelligence (AI), have brought dramatic revolutions to
human society. The increasing availability of digital data on scholarly outputs offers unprecedented opportunities to explore science of science (SciSci). Despite many significant works have been done on SciSci, substantial disciplinary differences in different domains make some insights inadequate within particular fields. One thing standing out is that knowledge concerning the science behind AI is sorely lacking. In this work, we study the evolution of AI from three dimensions, including the evolution of trend, mobility, and collaboration. We find that the AI research hotspots have shifted from theory to application. The USA, which has the largest number of distinguished AI scientists, appeals most to the global AI talents. The brain drain problem of AI scientists is increasingly serious in developing countries. The ties among the AI elites are highly clustered in the collaboration network. Overall, our work aims to serve as a starter and support the development of AI exploring in a visionary way.
993–1013
Sha Yuan,
6f6848c5-8f20-47fe-a303-aba482271e66
Shao, Zhou
2762e4e9-e550-4f18-a11c-f57520cf8b53
Wei, Xingxing
0033e7a2-762d-417b-81b7-f750b06241e4
Tang, Jie
69c44bae-b1fa-45eb-a01d-3ac5b00fa749
Hall, Wendy
11f7f8db-854c-4481-b1ae-721a51d8790c
Wang, Yongli
e9a93aae-8484-4b88-8cb2-6cdbe5f31fb8
Wang, Ying
252187b6-5482-4ab1-992c-46eab09cd2c6
Wang, Ye
5387321c-74c2-4dd6-8fd7-13e455f888bb
Sha Yuan,
6f6848c5-8f20-47fe-a303-aba482271e66
Shao, Zhou
2762e4e9-e550-4f18-a11c-f57520cf8b53
Wei, Xingxing
0033e7a2-762d-417b-81b7-f750b06241e4
Tang, Jie
69c44bae-b1fa-45eb-a01d-3ac5b00fa749
Hall, Wendy
11f7f8db-854c-4481-b1ae-721a51d8790c
Wang, Yongli
e9a93aae-8484-4b88-8cb2-6cdbe5f31fb8
Wang, Ying
252187b6-5482-4ab1-992c-46eab09cd2c6
Wang, Ye
5387321c-74c2-4dd6-8fd7-13e455f888bb

Sha Yuan, , Shao, Zhou, Wei, Xingxing, Tang, Jie, Hall, Wendy, Wang, Yongli, Wang, Ying and Wang, Ye (2020) Science behind AI: the evolution of trend, mobility, and collaboration. Scientometrics, 124, 993–1013. (doi:10.1007/s11192-020-03423-7).

Record type: Article

Abstract

In this era of interdisciplinary science, many scientific achievements, such as artificial intelligence (AI), have brought dramatic revolutions to
human society. The increasing availability of digital data on scholarly outputs offers unprecedented opportunities to explore science of science (SciSci). Despite many significant works have been done on SciSci, substantial disciplinary differences in different domains make some insights inadequate within particular fields. One thing standing out is that knowledge concerning the science behind AI is sorely lacking. In this work, we study the evolution of AI from three dimensions, including the evolution of trend, mobility, and collaboration. We find that the AI research hotspots have shifted from theory to application. The USA, which has the largest number of distinguished AI scientists, appeals most to the global AI talents. The brain drain problem of AI scientists is increasingly serious in developing countries. The ties among the AI elites are highly clustered in the collaboration network. Overall, our work aims to serve as a starter and support the development of AI exploring in a visionary way.

Text
Science behind AI the evolution of trend, mobility, and collaboration - Accepted Manuscript
Download (4kB)

More information

Accepted/In Press date: 14 March 2020
e-pub ahead of print date: 10 June 2020

Identifiers

Local EPrints ID: 443059
URI: http://eprints.soton.ac.uk/id/eprint/443059
PURE UUID: e3480572-a5c1-4875-baf1-d0b493a3e932
ORCID for Wendy Hall: ORCID iD orcid.org/0000-0003-4327-7811

Catalogue record

Date deposited: 07 Aug 2020 16:36
Last modified: 15 Sep 2021 05:41

Export record

Altmetrics

Contributors

Author: Sha Yuan
Author: Zhou Shao
Author: Xingxing Wei
Author: Jie Tang
Author: Wendy Hall ORCID iD
Author: Yongli Wang
Author: Ying Wang
Author: Ye Wang

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×