Abstract
How to discover and rank the scientific research team from the huge amount of literatures is a hard challenge for scientific researchers. Therefore, based on social network analysis with bibliometrics, a comprehensive method to discover and rank collaborative research teams is proposed in this paper. With the data from 2010–2015 in CIMS as the sample, of a Chinese journal of CIMS as the samples, n-clique and snow ball sampling method is used to identify collaborative research teams. Then, the research teams are ranked using indexes which include both scientific research outcomes and the close degree of Co-author networks. Case study shows that the method is more comprehensive than the ranking method which considers bibliometrics or network properties only.
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Acknowledgments
This work is based upon research work supported by the National Natural Science Foundation of China under grant No. 71171019 and No. 06198040; the Fundamental Research Funds for the Central Universities under grant FRF-SD-13-004B and FRF-TP-14-055A2; and the Program for China Postdoctoral Science Foundation under grant No. 2013T60064.
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Zhang, M., Zhang, X., Hu, Y. (2015). Ranking of Collaborative Research Teams Based on Social Network Analysis and Bibliometrics. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2015. Lecture Notes in Computer Science(), vol 9320. Springer, Cham. https://doi.org/10.1007/978-3-319-24132-6_30
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DOI: https://doi.org/10.1007/978-3-319-24132-6_30
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