Modeling complex networks with accelerating growth and aging effect

Publication date: Available online 5 February 2019Source: Physics Letters AAuthor(s): Jin Liu, Jian Li, Chen Yadang, Xianyi Chen, Zhili Zhou, Zejun Yang, Cheng-Jun ZhangAbstractNumerous empirical studies have revealed that a large number of real networks exhibit the property of accelerating growth, i.e. network size (nodes) increases superlinearly with time. Examples include the size of social networks, the output of scientists, the population of cities, and so on. In the literature, these real systems are widely represented by complex networks for analysis, and many network models have been proposed to explain the observed properties in these systems such as power-law degree distribution. However, most of these models (e.g. the well-known BA model) are based on linear growth of these systems. In this paper, we propose a network model with accelerating growth and aging effect, resulting in an emergence of super hubs which is consistent with the empirical observation in citation networks.
Source: Physics Letters A - Category: Physics Source Type: research
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