Rousseau and His Team’s Study on Gefura Measures  

作　　者：Li Weigang 

机构地区：[1]TransLab, Department of Computer Science, University of Brasilia, Brasilia-DF, Brazil

出　　处：《Social Networking》2015年第2期47-50,共4页社交网络（英文）

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.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.

关 键 词：COMPLEX Networks FOLLOW Model Gefura Measures Q-Measure ROUSSEAU 

分 类 号：R73[医药卫生—肿瘤]