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Wang, X., Cao, X.C., Jin, D., Cao, Y.X. and He, D.X. (2016) The (Un)supervised NMF Methods for Discovering Overlapping Communities as Well as Hubs and Outliers in Networks. Physica A: Statistical Mechanics and Its Applications, 446, 22-34.
http://dx.doi.org/10.1016/j.physa.2015.11.016

has been cited by the following article:

• TITLE: Spreading Dynamics of a Social Information Model with Overlapping Community Structures on Complex Networks

  AUTHORS: Xiongding Liu, Tao Li, Yuanmei Wang, Chen Wan

  KEYWORDS: Social Information Spreading, Overlap Parameter, Community Structures, Complex Networks, Threshold Value

  JOURNAL NAME: Open Access Library Journal, Vol.3 No.5, May 30, 2016

  ABSTRACT: In this paper, we present a SARS (susceptible-adopted-removed-susceptible) social information spreading model with overlapping community structures on complex networks. Using the mean field theory, the spreading dynamic of the model has been studied. At first, we derived the spreading critical threshold value and equilibriums. Theoretical results indicate that the existence of equilibriums is determined by threshold value. The threshold value is obviously dependent on the topology of underlying networks. Furthermore, the globally asymptotically stable equilibriums are proved in detail. The overlap parameterof community structures can't change the threshold value, but it can influence the extent of the social information spreading. Numerical simulations confirmed the analytical results.