Data Abstraction and Centrality Measures to Scientific Social Network Analysis
2017 IEEE 21st International Conference on Computer Supported Cooperative Work in Design (CSCWD)(2017)
摘要
Analyzing social iterations in a scientific environment will assist researchers in expanding their collaborative networks. Scientific social networks represent the researchers' social iterations in an academic environment. The analysis of these networks requires a detailed study of their structure and it is important the use of visual resources in order to a better understanding of how the social iterations occur. In this paper we will use centrality metrics and a clustering algorithm to analyze the structure of a Brazilian scientific social network. A scientific social network visualization tool will be used to allow a visual analysis of the collaboration between researchers from different educational institutions.
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关键词
Scientific Social Network Analysis,Researchers' Importance Analysis,Centrality Metrics,Clustering Algorithm
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