中国物理B ›› 2011, Vol. 20 ›› Issue (1): 18902-018902.doi: 10.1088/1674-1056/20/1/018902

• INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY • 上一篇    下一篇

Community detection with consideration of non-topological information

邹盛荣1, 彭昱静1, 刘爱芬2, 徐秀莲2, 何大韧2   

  1. (1)College of Information Engineering, Yangzhou University, Yangzhou 225009, China; (2)College of Physics Science and Technology, Yangzhou University, Yangzhou 225009, China
  • 收稿日期:2010-06-07 修回日期:2010-07-21 出版日期:2011-01-15 发布日期:2011-01-15
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant Nos. 70671089 and 10635040).

Community detection with consideration of non-topological information

Zou Sheng-Rong(邹盛荣)a), Peng Yu-Jing(彭昱静)a),Liu Ai-Fen(刘爱芬)b), Xu Xiu-Lian(徐秀莲)b),and He Da-Ren(何大韧)b)†   

  1. a College of Information Engineering, Yangzhou University, Yangzhou 225009, China; b College of Physics Science and Technology, Yangzhou University, Yangzhou 225009, China
  • Received:2010-06-07 Revised:2010-07-21 Online:2011-01-15 Published:2011-01-15
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant Nos. 70671089 and 10635040).

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摘要： In a network described by a graph, only topological structure information is considered to determine how the nodes are connected by edges. Non-topological information denotes that which cannot be determined directly from topological information. This paper shows, by a simple example where scientists in three research groups and one external group form four communities, that in some real world networks non-topological information (in this example, the research group affiliation) dominates community division. If the information has some influence on the network topological structure, the question arises as to how to find a suitable algorithm to identify the communities based only on the network topology. We show that weighted Newman algorithm may be the best choice for this example. We believe that this idea is general for real-world complex networks.

Abstract: In a network described by a graph, only topological structure information is considered to determine how the nodes are connected by edges. Non-topological information denotes that which cannot be determined directly from topological information. This paper shows, by a simple example where scientists in three research groups and one external group form four communities, that in some real world networks non-topological information (in this example, the research group affiliation) dominates community division. If the information has some influence on the network topological structure, the question arises as to how to find a suitable algorithm to identify the communities based only on the network topology. We show that weighted Newman algorithm may be the best choice for this example. We believe that this idea is general for real-world complex networks.

Key words: community division, algorithm, topological structure, weighted network

中图分类号:  (Networks and genealogical trees)

  • 89.75.Hc
89.75.Fb (Structures and organization in complex systems)