Assessing the relevance of node features for network structure

被引:147
作者
Bianconi, Ginestra [2 ]
Pin, Paolo [1 ,3 ]
Marsili, Matteo [2 ]
机构
[1] Univ Siena, Dipartimento Econ Polit, I-53100 Siena, Italy
[2] Abdus Salam Int Ctr Theoret Phys, I-34014 Trieste, Italy
[3] European Univ Inst, Max Weber Programme, I-50014 Fiesole, Italy
关键词
entropy; inference; social networks; communities; COMMUNITY STRUCTURE; COMPLEX NETWORKS; MODELS;
D O I
10.1073/pnas.0811511106
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Networks describe a variety of interacting complex systems in social science, biology, and information technology. Usually the nodes of real networks are identified not only by their connections but also by some other characteristics. Examples of characteristics of nodes can be age, gender, or nationality of a person in a social network, the abundance of proteins in the cell taking part in protein-interaction networks, or the geographical position of airports that are connected by directed flights. Integrating the information on the connections of each node with the information about its characteristics is crucial to discriminating between the essential and negligible characteristics of nodes for the structure of the network. In this paper we propose a general indicator T, based on entropy measures, to quantify the dependence of a network's structure on a given set of features. We apply this method to social networks of friendships in U. S. schools, to the protein-interaction network of Saccharomyces cerevisiae and to the U. S. airport network, showing that the proposed measure provides information that complements other known measures.
引用
收藏
页码:11433 / 11438
页数:6
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