Global Collaboration in Artificial Intelligence: Bibliometrics and Network Analysis from 1985 to 2019

doi:10.2478/jdis-2020-0027

Abstract

Abstract:

Purpose: This study aims to explore the trend and status of international collaboration in the field of artificial intelligence (AI) and to understand the hot topics, core groups, and major collaboration patterns in global AI research.

Design/methodology/approach: We selected 38,224 papers in the field of AI from 1985 to 2019 in the core collection database of Web of Science (WoS) and studied international collaboration from the perspectives of authors, institutions, and countries through bibliometric analysis and social network analysis.

Findings: The bibliometric results show that in the field of AI, the number of published papers is increasing every year, and 84.8% of them are cooperative papers. Collaboration with more than three authors, collaboration between two countries and collaboration within institutions are the three main levels of collaboration patterns. Through social network analysis, this study found that the US, the UK, France, and Spain led global collaboration research in the field of AI at the country level, while Vietnam, Saudi Arabia, and United Arab Emirates had a high degree of international participation. Collaboration at the institution level reflects obvious regional and economic characteristics. There are the Developing Countries Institution Collaboration Group led by Iran, China, and Vietnam, as well as the Developed Countries Institution Collaboration Group led by the US, Canada, the UK. Also, the Chinese Academy of Sciences (China) plays an important, pivotal role in connecting the these institutional collaboration groups.

Research limitations: First, participant contributions in international collaboration may have varied, but in our research they are viewed equally when building collaboration networks. Second, although the edge weight in the collaboration network is considered, it is only used to help reduce the network and does not reflect the strength of collaboration.

Practical implications: The findings fill the current shortage of research on international collaboration in AI. They will help inform scientists and policy makers about the future of AI research.

Originality/value: This work is the longest to date regarding international collaboration in the field of AI. This research explores the evolution, future trends, and major collaboration patterns of international collaboration in the field of AI over the past 35 years. It also reveals the leading countries, core groups, and characteristics of collaboration in the field of AI.

Key words: Artificial intelligence, International collaboration, Collaboration pattern, Bibliometric analysis, Social network analysis

Hu, Haotian, Dongbo Wang, and Sanhong Deng. "Global Collaboration in Artificial Intelligence: Bibliometrics and Network Analysis from 1985 to 2019." Journal of Data and Information Science, vol.5, no.4, 2020, pp.86-115. DOI: 10.2478/jdis-2020-0027

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References 21

[1]	Aleixandre-Tudó, J.L., Castelló-Cogollos, L., Aleixandre, J.L., & Aleixandre-Benavent, R. (2019). Renewable energies: Worldwide trends in research, funding and international collaboration. Renewable Energy, 139, 268-278. doi: 10.1016/j.renene.2019.02.079
[2]	Cai, Y., Ramis Ferrer, B & Luis Martinez Lastra, J. (2019). Building University-Industry Co-Innovation Networks in Transnational Innovation Ecosystems: Towards a Transdisciplinary Approach of Integrating Social Sciences and Artificial Intelligence. Sustainability, 11(17), 4633. doi: 10.3390/su11174633
[3]	Chen, X., Xie, H., Wang, F.L., Liu, Z., Xu, J., & Hao, T. (2018). A bibliometric analysis of natural language processing in medical research. BMC Medical Informatics and Decision Making, 18(1), 14. doi: 10.1186/s12911-018-0594-x
[4]	Dinić, B.M., & Jevremov, T. (2019). Trends in research related to the Dark Triad: A bibliometric analysis. Current Psychology, 1-10. doi: 10.1007/s12144-020-00761-w pmid: 32421031
[5]	Doğan, G., & Kayır, S. (2020). Global scientific outputs of brain death publications and evaluation according to the religions of countries. Journal of Religion and Health, 59(1), 96-112. doi: 10.1007/s10943-019-00886-8 pmid: 31317465
[6]	Frey, C.D., Wilson, T.A., Decamillis, M., Wilson, T., Wilson, J.A., Wolfe, S.Q., & Fargen, K.M. (2017). A pilot study of the level of evidence and collaboration in published neurosurgical research. World Neurosurgery, 108, 901-908. doi: 10.1016/j.wneu.2017.09.011 pmid: 28899833
[7]	Gao, F., Jia, X., Zhao, Z., Chen, C.C., Xu, F., Geng, Z., & Song, X. (2019). Bibliometric analysis on tendency and topics of artificial intelligence over last decade. Microsystem Technologies, 1-13. doi: 10.1007/s00542-020-05051-w pmid: 33041523
[8]	Godoy, D., Zunino, A., & Mateos, C. (2015). Publication practices in the Argentinian Computer Science community: a bibliometric perspective. Scientometrics, 102(2), 1795-1814. doi: 10.1007/s11192-014-1450-0
[9]	Hu, H.T., Wang, D.B., & Huang, S.Q. (2019). International collaboration in the field of artificial intelligence: global trends and networks at the country level. In Proceedings of the17th International Conference on Scientometrics and Informetrics, ISSI2019, v2 (pp. 2501-2502).
[10]	Koehler, W. (2001). Information science as “Little Science”: The implications of a bibliometric analysis of the Journal of the American Society for Information Science. Scientometrics, 51(1), 117-132. doi: 10.1023/A:1010516712215
[11]	Miller, T. (2019). Explanation in artificial intelligence: Insights from the social sciences. Artificial Intelligence, 267, 1-38. doi: 10.1016/j.artint.2018.07.007
[12]	Niu, J., Tang, W., Xu, F., Zhou, X., & Song, Y. (2016). Global research on artificial intelligence from 1990-2014: Spatially-explicit bibliometric analysis. ISPRS International Journal of Geo-Information, 5(5), 66. doi: 10.3390/ijgi5050066
[13]	Pan, W., Jian, L., & Liu, T. (2019). Grey system theory trends from 1991 to 2018: A bibliometric analysis and visualization. Scientometrics, 121(3), 1407-1434. doi: 10.1007/s11192-019-03256-z
[14]	Pee, L.G., Pan, S.L., & Cui, L. (2019). Artificial intelligence in healthcare robots: A social informatics study of knowledge embodiment. Journal of the Association for Information Science and Technology, 70(4), 351-369. doi: 10.1002/asi.2019.70.issue-4
[15]	Peng, X., & Dai, J. (2018). A bibliometric analysis of neutrosophic set: Two decades review from 1998 to 2017. Artificial Intelligence Review, 1-57. doi: 10.1007/s10462-020-09852-3 pmid: 32836651
[16]	Shukla, A.K., Janmaijaya, M., Abraham, A., & Muhuri, P.K. (2019). Engineering applications of artificial intelligence: A bibliometric analysis of 30 years (1988-2018). Engineering Applications of Artificial Intelligence, 85, 517-532. doi: 10.1016/j.engappai.2019.06.010
[17]	Sohn, E., Noh, K.R., Lee, B., & Kwon, O.J. (2018). Bibliometric network analysis and visualization of research and development trends in Precision Medicine. In Proceedings of 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)(pp. 727-730). IEEE.
[18]	Tang, K.Y., Chou, T.L., & Tsai, C.C. (2019). A content analysis of computational thinking research: An international publication trends and research typology. The Asia-Pacific Education Researcher, 1-11.
[19]	Tarazona-Alvarez, B., Lucas-Dominguez, R., Paredes-Gallardo, V., Alonso-Arroyo, A., & Vidal-Infer, A. (2019). A bibliometric analysis of scientific production in the field of lingual orthodontics. Head & Face Medicine, 15(1), 23. doi: 10.1186/s13005-019-0207-7 pmid: 31493796
[20]	Tsay, M.Y. (2011). A bibliometric analysis and comparison on three information science journals: JASIST, IPM, JOD, 1998-2008. Scientometrics, 89(2), 591. doi: 10.1007/s11192-011-0460-4
[21]	Wu, Y., & Duan, Z. (2015). Social network analysis of international scientific collaboration on psychiatry research. International Journal of Mental Health Systems, 9(1), 2. doi: 10.1186/1752-4458-9-2 pmid: 25598839

Rank	Journals	Papers	Percent (%)
1	EXPERT SYSTEMS WITH APPLICATIONS	461	1.206%
2	IEEE ACCESS	290	0.759%
3	AI MAGAZINE	233	0.610%
4	ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE	220	0.576%
5	APPLIED SOFT COMPUTING	192	0.502%
6	ARTIFICIAL INTELLIGENCE	191	0.500%
7	SENSORS	152	0.398%
8	NEUROCOMPUTING	139	0.364%
9	ARTIFICIAL INTELLIGENCE REVIEW	122	0.319%
10	NEURAL COMPUTING & APPLICATIONS	122	0.319%
11	JOURNAL OF INTELLIGENT & FUZZY SYSTEMS	114	0.298%
12	MINDS AND MACHINES	111	0.290%
13	INFORMATION SCIENCES	105	0.275%
14	KNOWLEDGE-BASED SYSTEMS	104	0.272%
15	ENERGIES	103	0.269%
16	ARTIFICIAL INTELLIGENCE IN MEDICINE	99	0.259%
17	APPLIED ARTIFICIAL INTELLIGENCE	96	0.251%
18	EUROPEAN JOURNAL OF OPERATIONAL RESEARCH	96	0.251%
19	AGRO FOOD INDUSTRY HI-TECH	94	0.246%
20	KYBERNETES	93	0.243%

Rank	Country/region	Total papers	Collaborative papers	Percentage of collaborative papers
1	Vietnam	189	170	89.95%
2	Saudi Arabia	344	277	80.52%
3	U Arab Emirates	128	99	77.34%
4	Pakistan	301	229	76.08%
5	Sweden	332	251	75.60%
6	Switzerland	365	266	72.88%
7	Denmark	173	126	72.83%
8	Netherlands	578	402	69.55%
9	Tunisia	158	109	68.99%
10	Iran	1,279	880	68.80%
11	Slovenia	156	107	68.59%
12	Malaysia	737	499	67.71%
13	Portugal	461	310	67.25%
14	Belgium	310	206	66.45%
15	France	1,444	954	66.07%
16	Egypt	262	173	66.03%
17	Australia	1,180	773	65.51%
18	New Zealand	152	99	65.13%
19	Singapore	455	289	63.52%
20	Colombia	133	84	63.16%
21	Serbia	160	101	63.13%
22	Finland	234	146	62.39%
23	Israel	218	136	62.39%
24	Spain	1,960	1,218	62.14%
25	Italy	1,377	855	62.09%
26	Turkey	909	561	61.72%
27	Mexico	459	283	61.66%
28	Norway	191	117	61.26%
29	UK	3,070	1,863	60.68%
30	Canada	1,463	877	59.95%
31	Taiwan	888	532	59.91%
32	South Korea	869	516	59.38%
33	Brazil	1,077	638	59.24%
34	Greece	500	291	58.20%
35	Germany	1,538	892	58.00%
36	Austria	337	193	57.27%
37	USA	7,763	4,436	57.14%
38	Japan	1,239	697	56.26%
39	China	6,444	3,596	55.80%
40	Ireland	206	114	55.34%
41	Algeria	204	111	54.41%
42	Thailand	151	80	52.98%
43	Indonesia	180	95	52.78%
44	India	2,080	1,092	52.50%
45	South Africa	205	105	51.22%
46	Hungary	159	81	50.94%
47	Russia	540	267	49.44%
48	Czech Republic	379	164	43.27%
49	Slovakia	143	61	42.66%
50	Romania	627	263	41.95%
51	Poland	866	360	41.57%

Rank	Institution	Country	BC	Degree
1	Chinese Academy of Sciences	China	0.405336672	4
2	Ton Duc Thang University	Vietnam	0.384635685	18
3	Georgia Institute of Technology	USA	0.371527778	3
4	University of Alberta	Canada	0.350694444	4
5	University of Kurdistan	Iran	0.295375309	14
6	Islamic Azad University	Iran	0.288076771	11
7	Duy Tan University	Vietnam	0.223353933	13
8	MIT	USA	0.203373016	4
9	University of Tabriz	Iran	0.153155313	7
10	Oxford	UK	0.12202381	5
11	University of Technology Malaysia	Malaysia	0.095804022	5
12	Penn State University	USA	0.091765873	3
13	University of Tehran	Iran	0.039564365	3
14	University of Technology Sydney	Australia	0.036280213	5
15	Near East University	Turkey	0.033982326	3
16	Sejong University	South Korea	0.032871873	5
17	University of Malaya	Malaysia	0.031909121	3
18	GTEV ReX Ltd	UK	0.03125	2
19	University of Toronto	Canada	0.03125	2
20	Hong Kong Polytechnic University	China	0.03125	3
21	National University of Singapore	Singapore	0.030505952	4
22	Johns Hopkins University	USA	0.030505952	4
23	University of Southern Queensland	Australia	0.028754488	4
24	University of Salamanca	Spain	0.015376984	3
25	Osaka Institute of Technology	Japan	0.015376984	3
26	Korea Institute of Geoscience & Mineral Resources KIGAM	South Korea	0.006101012	4
27	Korea University of Science & Technology	South Korea	0.005030213	3
28	University of South Eastern Norway	Norway	0.005030213	2
29	University College of Southeast Norway	Norway	0.003571429	2
30	UTM	Malaysia	0.003515133	4
31	Xi’an University of Science & Technology	China	0.001070799	3
32	Nanjing Normal University	China	0.001070799	2
33	Hanoi University	Vietnam	0.000907137	2
34	Obuda University	Hungary	0.000496032	3