Cycle-Based versus Degree-based Classification of Social Networks.
Year: 2009
Type: article
Abstract: ABSTRACT: Complex networks can be classi fi ed in three main types: random networks, small-world networks and scale-free networks. Two approaches are tested and compared to identify and classify social networks: one is based on vertex degree and the other on cycle degree. The former approach inaccurately concludes the type of the real network whereas the later ac-curately identi fi es the type of the real network. The cycle-based approach reveals Gaussian distribution of the cycles. Cycles distributions of random, small world and scale free networks have one universal Gaussian function. The proposed equation can be used to model, identify and classify any network includ-ing social networks. Categories and Subject DescriptorsC.2.1 [Network Architecture and Design]: G.1.4 [Quadrature and Numerical Differentiation]; Gaussian quadrature General Terms Network classifi cation, Social networks Keywords Network analysis, Gaussian distribution, Social networks,Received: 18 May 2009; Revised 29 July 2009; Accepted 1 August 2009.
Authors: Khaled Mahdi, Maytham Safar, Ibrahim Sorkhoh, Ali Kassem
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W90158599