• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

MFSC: Mean-Field-Theory and Spreading-Coefficient Based Degree Distribution Analysis in Social Network

Vol. 12, No. 8, August 30, 2018
10.3837/tiis.2018.08.006 , Download Paper (Free):

Abstract

Degree distribution can provide basic information for structural characteristics and internal relationship in social network. It is a critical procedure for social network topology analysis. In this paper, based on the mean-field theory, we study a special type of social network with exponential distribution of time intervals. First of all, in order to improve the accuracy of analysis, we propose a spreading coefficient algorithm based on intimate relationship, which determines the number of the joined members through the intimacy among members. Then, simulation show that the degree distribution of follows the power-law distribution and has small-world characteristics. Finally, we compare the performance of our algorithm with the existing algorithms, and find that our algorithm improves the accuracy of degree distribution as well as reducing the time complexity significantly, which can complete 29.04% higher precision and 40.94% lower implementation time.


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Cite this article

[IEEE Style]
C. Lin and Y. Zheng, "MFSC: Mean-Field-Theory and Spreading-Coefficient Based Degree Distribution Analysis in Social Network," KSII Transactions on Internet and Information Systems, vol. 12, no. 8, pp. 3630-3656, 2018. DOI: 10.3837/tiis.2018.08.006 .

[ACM Style]
Chongze Lin and Yi Zheng. 2018. MFSC: Mean-Field-Theory and Spreading-Coefficient Based Degree Distribution Analysis in Social Network. KSII Transactions on Internet and Information Systems, 12, 8, (2018), 3630-3656. DOI: 10.3837/tiis.2018.08.006 .