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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (4): 30-37    DOI: 10.11925/infotech.2096-3467.2017.04.04
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Recognizing Dynamic Academic Impacts of Scholars Based on Cooperative Network
Ruxia Fan1(),Jianxun Zeng1,Yaruixi Gao2
1Institute of Scientific and Technical Information of China, Beijing 100038, China
2China Defense Science and Technology Information Center, Beijing 100142, China
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Abstract  

[Objective] This paper tries to identify the high cooperative scholars and their dynamic academic impacts with the help of high cooperative scholar recognition algorithm and the scholar impact recognition algorithm. [Methods] First, we identified the high cooperation scholars based on the number of collaborators. Then, we estimated the impacts of these scholars and their teams with the amount of publications and degree of centrality. [Results] The number of highly cooperative scholars varied among the teams. The dynamic academic impacts of highly cooperative scholars were either growing steadily or fluctuating maturely. [Limitations] Only used two indicators to measure the impacts of scholars. More indicators were needed to analyze the complex cases. [Conclusions] The proposed method could effectively identify the highly cooperative scholars of the team and their dynamic academic impacts.

Key wordsAcademic Impact      Social Network Analysis      Dynamic Pattern     
Received: 29 December 2016      Published: 24 May 2017

Cite this article:

Ruxia Fan,Jianxun Zeng,Yaruixi Gao. Recognizing Dynamic Academic Impacts of Scholars Based on Cooperative Network. Data Analysis and Knowledge Discovery, 2017, 1(4): 30-37.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.04.04     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2017/V1/I4/30

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