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A Community Structure Detection Method based on Field Effect

Volume 13, Number 6, October 2017 - Paper 16  - pp. 956-965
DOI: 10.23940/ijpe.17.06.p16.956965

Ru Zhang*, Zongwei Ren

School of Management, Harbin University of Commerce, Harbin, 150028, People’s Republic of China

(Submitted on May 18, 2017; Revised on August 20, 2017; Accepted on September 15, 2017)

Abstract:

The information expressed by vertex is influenced by the environment in the semantic social networks, which is the result of natural and social factors. The field effect theory can explain the relationship between social environment and psychological environment. Therefore,a community discovery based on field effect is proposed by the perspective of pattern classification. The algorithm based on secondary classification ideology can be simply described as follows: the social networks are first divided into several original communities based on networks structure and the results of classification are assigned to each vertex of the networks as the label; secondly, the labels spread based on field effect that is computed by natural and social factors; ultimately the vertices which have same labels can be divided into a community. It is a process of secondary classification that can reduce uncertainty of the labels setting and randomness of labels propagation effectively. Experimental results show that the improved algorithm can get better information similarity based on field effect of vertex and make the inner node more closely.

 

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