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A Study on Scale Free Social Network Evolution Model with Degree Exponent<2
主讲:李振鹏 地点: 中科院数学与系统科学研究院 南楼222会议室 时间:2018-11-10 09:30 字体<    >

报告人:李振鹏 副教授 大理大学数学与计算机学院

时间:2018年11月10日(周六) 9:30-11:00

地点:中科院数学与系统科学研究院 南楼222会议室

 

Inspired by real world phenomena, this talk presents a new power law evolutional network model with degree exponent β<2. We use combinatorial probabilistic methods to examine the evolution of on line social networks. In our model, each time stamp the number of links among a new added node and old ones follows Poisson distribution with parameter λ and selection
probability
p. We derive exact analytical relationship between the exponent of the power law β and the parameter λ, p. Through the computer simulations, we verify the correctness of the exponent β analytical solutions. Both theoretical solutions and simulation results show that the presented network evolution model with randomly growing edges conforms to degree exponent
β<2 and bending phenomena observed in real world network.
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