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http://dx.doi.org/10.1633/JISTaP.2022.10.S.2

Changes in the Structure of Collaboration Network in Artificial Intelligence by National R&D Stage  

Hyun, Mi Hwan (KISTI Digital Curation Center)
Lee, Hye Jin (KISTI Digital Curation Center)
Lim, Seok Jong (KISTI Digital Curation Center)
Lee, KangSan DaJeong (KISTI Digital Curation Center)
Publication Information
Journal of Information Science Theory and Practice / v.10, no.spc, 2022 , pp. 12-24 More about this Journal
Abstract
This study attempted to investigate changes in collaboration structure for each stage of national Research and Development (R&D) in the artificial intelligence (AI) field through analysis of a co-author network for papers written under national R&D projects. For this, author information was extracted from national R&D outcomes in AI from 2014 to 2019. For such R&D outcomes, NTIS (National Science & Technology Information Service) information from the KISTI (Korea Institute of Science and Technology Information) was utilized. In research collaboration in AI, power function structure, in which research efforts are led by some influential researchers, is found. In other words, less than 30 percent is linked to the largest cluster, and a segmented network pattern in which small groups are primarily developed is observed. This means a large research group with high connectivity and a small group are connected with each other, and a sporadic link is found. However, the largest cluster grew larger and denser over time, which means that as research became more intensified, new researchers joined a mainstream network, expanding a scope of collaboration. Such research intensification has expanded the scale of a collaborative researcher group and increased the number of large studies. Instead of maintaining conventional collaborative relationships, in addition, the number of new researchers has risen, forming new relationships over time.
Keywords
co-author network analysis; social network analysis; researcher collaboration; artificial intelligence; national R&D project;
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Times Cited By KSCI : 3  (Citation Analysis)
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1 McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (2006). A proposal for the Dartmouth summer research project on artificial intelligence, August 31, 1955. AI Magazine, 27(4), 12. https://doi.org/10.1609/aimag.v27i4.1904.   DOI
2 Melin, G. (2000). Pragmatism and self-organization: Research collaboration on the individual level. Research Policy, 29(1), 31-40. https://doi.org/10.1016/S0048-7333(99)00031-1.   DOI
3 Ministry of Science and ICT. (2019). National strategy for artificial intelligence (AI). https://doc.msit.go.kr/SynapDocViewServer/viewer/doc.html?key=3186dcb6ace244e0870b2231aba980ae&convType=img&convLocale=ko_KR&contextPath=/SynapDocViewServer.
4 Mohr, J., & Spekman, R. (1994). Characteristics of partnership success: Partnership attributes, communication behavior, and conflict resolution techniques. Strategic Management Journal, 15(2), 135-152. https://doi.org/10.1002/smj.4250150205.   DOI
5 Newman, M. E. (2001b). Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. Physical Review E, Statistical, Nonlinear, and Soft Matter Physics, 64(1 Pt 2), 016132. https://doi.org/10.1103/PhysRevE.64.016132.   DOI
6 Hager, G. D., Drobnis, A., Fang, F., Ghani, R., Greenwald, A., Lyons, T., Parkes, D. C., Schultz, J., Saria, S., Smith, S. F., & Tambe, M. (2019). Artificial intelligence for social good. arXiv. https://doi.org/10.48550/arXiv.1901.05406.
7 Yang, H., Choi, B., Lee, J., Jang, H., Baek, S., & Kim, D. (2018). A prospective analysis of artificial intelligence(AI) technology and innovation policies: Focused on improving Korea's national AI R&D policy. Science and Technology Policy Institute.
8 Lee, S. (2018). International comparison of artificial intelligence research capabilities and implications. SPRI Insight Report, 2018(3), 1-15. https://spri.kr/posts/view/22461?code=data_all&study_type=ai_brief.
9 Newman, M. E. (2004). Coauthorship networks and patterns of scientific collaboration. Proceedings of the National Academy of Sciences of the United States of America, 101(Suppl 1), 5200-5205. https://doi.org/10.1073/pnas.0307545100.   DOI
10 Gang, J. Y., Seol, J. W., & Hwang, H. (2020). A study on the analysis of identification system and the linkage method of academic-information. Journal of Korean Library and Information Science Society, 51(1), 115-143. https://doi.org/10.16981/kliss.51.202003.115.   DOI
11 Park, S., Kim, J., & Kim, D. (2014). Exploratory study for research collaboration of social scientists in Korea: Focused on the researchers involved in Korea Social Science Research Support Program (SSK project). Discourse 201, 17(1), 5-37. https://doi.org/10.17789/discou.2014.17.1.001.   DOI
12 Turing, A. M. (1950). Computing machinery and intelligence. Mind, 59(236), 433-460. https://doi.org/10.1093/mind/LIX.236.433.   DOI
13 Gordon, M. (1980). A critical reassessment of inferred relations between multiple authorship, scientific collaboration, the production of papers and their acceptance for publication. Scientometrics, 2(3), 193-201. https://link.springer.com/article/10.1007/BF02016697.   DOI
14 Newman, M. E. (2001a). Scientific collaboration networks. I. Network construction and fundamental results. Physical Review E, Statistical, Nonlinear, and Soft Matter Physics, 64(1 Pt 2), 016131. https://doi.org/10.1103/PhysRevE.64.016131.   DOI
15 Choi, Y., & Lee, K. (2009). A small talk on the concept of performance of government-financed scientific & technical research institutes. Korean Public Management Review, 23(4), 401-430. https://doi.org/10.24210/kapm.2009.23.4.017.   DOI
16 Chung, M., Park, S., Chae, B., & Lee, J. (2017). Analysis of major research trends in artificial intelligence through analysis of thesis data. Journal of Digital Convergence, 15(5), 225-233. https://doi.org/10.14400/JDC.2017.15.5.225.   DOI
17 Cloodt, M., Hagedoorn, J., & Roijakkers, N. (2006). Trends and patterns in interfirm R&D networks in the global computer industry: An analysis of major developments, 1970-1999. The Business History Review, 80(4), 725-746. https://doi.org/10.2307/25097267.   DOI
18 Eun, J. (2020). An analysis on China's status within the international research network in the field of artificial intelligence. Journal of Sinology and China Studies, 82, 217-239. https://doi.org/10.18077/chss.2020.82..010.   DOI
19 Kuzhabekova, A. (2011). Impact of co-authorship strategies on research productivity: A social-network analysis of publications in Russian cardiology. (Unpublished doctoral dissertation). University of Minnesota, Minneapolis.
20 Kang, H. (2017). Innovation capabilities of public research institutions: Focusing on papers related to the 4th industrial revolution (artificial intelligence). Science & Technology Policy, 27(6), 62-68. https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE07193597.
21 Lee, H., & Lee, C. (2018). Factors changing dynamic research collaboration network in Korean nanobiotechnology. Journal of the Korean Society for Library and Information Science, 52(1), 231-258. https://doi.org/10.4275/KSLIS.2018.52.1.231.   DOI
22 Abbasi, A., Altmann, J., & Hossain, L. (2011). Identifying the effects of co-authorship networks on the performance of scholars: A correlation and regression analysis of performance measures and social network analysis measures. Journal of Informetrics, 5(4), 594-607. https://doi.org/10.1016/j.joi.2011.05.007.   DOI
23 Pan, Y. (2016). Heading toward artificial intelligence 2.0. Engineering, 2(4), 409-413. https://doi.org/10.1016/J.ENG.2016.04.018.   DOI
24 Bordons, M., & Gomez, I. (2000). Collaboration networks in science. In B. Cronin, & H. B. Atkins (Eds.), The web of knowledge: A Festschrift in honor of Eugene Garfield (pp. 197-213). Information Today.
25 Nudelman, A. E., & Landers, C. E. (1972). The failure of 100 divided by 3 to equal 33-1/3. In American Sociological Association (Ed.), The American Sociologist (pp. 9). American Sociological Association.
26 Onel, S., Zeid, A., & Kamarthi, S. (2011). The structure and analysis of nanotechnology co-author and citation networks. Scientometric, 89(1), 119-138. https://link.springer.com/article/10.1007/s11192-011-0434-6.   DOI
27 Shin, J., & Park, Y. (2010). Evolutionary optimization of a technological knowledge network. Technovation, 30(11-12), 612-626. https://doi.org/10.1016/j.technovation.2010.04.004.   DOI
28 Pravdic, N., & Oluic-Vukovic, V. (1986). Dual approach to multiple authorship in the study of collaboration/scientific output relationship. Scientometrics, 10(5-6), 259-280. https://link.springer.com/article/10.1007/BF02016774.   DOI