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New Technology of Library and Information Service  2015, Vol. 31 Issue (9): 68-75    DOI: 10.11925/infotech.1003-3513.2015.09.10
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The Discovery and Evaluation of Research Team Under the Mode of Weighted Co-Author Network
Ren Ni, Zhou Jiannong
Institute of Agricultural Economics and Information, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
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Abstract  

[Objective] Discovering, analyzing and evaluating the research team of an organization or subject through the study of the weighted co-author network. [Methods] Build a comprehensive weighted model of the co-author network with the factors of co-author frequency, number, ranking, cited frequency and so on. Make an empirical research on the discovery and evaluation of research team with the method of social network analysis. [Results] The virtual team and its evaluating results got from this method is consistent with the research results about the actual team.The method can synthesize multiple influence factors, and objectively evaluate the structure and influence of the research team. [Limitations] In order to ensure the physical details of the actual team can be got to verify the research results, the authors choose their own institution as the evaluation object, and which makes the range of empirical research is narrow. The data type is unitary. [Conclusions] The method is suitable for the discovery of research team, the analysis of the relationship, and the evaluation of the construction within some scopes. These results are helpful to quickly know the team well, and provide the information for team optimization.

Received: 02 December 2014      Published: 06 April 2016
:  G353.1  

Cite this article:

Ren Ni, Zhou Jiannong. The Discovery and Evaluation of Research Team Under the Mode of Weighted Co-Author Network. New Technology of Library and Information Service, 2015, 31(9): 68-75.

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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2015.09.10     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2015/V31/I9/68

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