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摘要:
Guns and Rousseau’s recently published paper in FITEE gives a clear introduction about some important research results related to complex networks, which deepens people’s understanding of network characteristics, and puts forward new measures and models. The proposed gefura measures show the significance of appropriately using a “basic” normalization to describe the betweenness centrality of nodes, and then the “structural” normalization to pay more attention to the level of groups. The term “gefura measures” is from old Greek γεφυρα, meaning bridge measure, a more descriptive term with universal appeal. More specifically, they applied the Brandes algorithm to calculate the gefura measures, which makes their article easier to apply to practical cases. Even in academia, any new ideas, concepts, indicators and models should stand the test of time. The spirit of innovation of Rousseau and his team is highly recommendable. We sincerely hope that the study on gefura measures can raise more concerns, and can be recognized and used by social scientists, informetricians, and colleagues studying complex networks from all over the world as an important outcome.
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文献信息
篇名 Rousseau and His Team’s Study on Gefura Measures
来源期刊 社交网络(英文) 学科 医学
关键词 Complex NETWORKS FOLLOW Model Gefura Measures Q-Measure ROUSSEAU
年,卷(期) 2015,(2) 所属期刊栏目
研究方向 页码范围 47-50
页数 4页 分类号 R73
字数 语种
DOI
五维指标
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研究主题发展历程
节点文献
Complex
NETWORKS
FOLLOW
Model
Gefura
Measures
Q-Measure
ROUSSEAU
研究起点
研究来源
研究分支
研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
社交网络(英文)
季刊
2169-3285
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
112
总下载数(次)
0
总被引数(次)
0
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