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Sponsored by the Center for Science and Technology Development of the Ministry of Education
Supervised by Ministry of Education of the People's Republic of China
Modeling the evolution of networks is important to understand complex systems. Considering network structure and individual attributes, a force-based model is proposed to simulate the evolution of social networks. Each node is endowed with a series of attributes. We construct a multi-dimensional space as the evolution environment. An attribute vector represents a position in the space. Individuals interact with each other obeying a simple rule that each node tends to move to a low energy position driven by attraction from its immediate neighbors and repulsion from all other nodes. So the evolution can be viewed as interaction among nodes, moving close or far away. A new position means a change of attributes. Network structure updates at last of each round. Edge exists only when its two endpoints' similarity distance is lower than a threshold. We validate the model and simulations show that though individual attributes change, the network keeps the power-law degree distribution and clusters emerge in the process of evolution.
Keywords:Social networks; Network evolution; Individual attributes ; Attraction and repulsion