Han Lilei, Lin Zhaohua, Tang Ming, Zhou Jie, Zou Yong, Guan Shuguang
School of Physics and Electronic Science, East China Normal University, Shanghai 200241, China.
Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai 200241, China.
Phys Rev E. 2020 Apr;101(4-1):042308. doi: 10.1103/PhysRevE.101.042308.
Preferential contact process limited by contact capacity remarkably affects the spreading dynamics on complex networks, but the influence of this preferential contact in social contagions has not been fully explored. To this end, we propose a behavior spreading model based on the mechanism of preferential contact. The probability in the model that an adopted individual contacts and tries to transmit the behavioral information to one of his/her neighbors depends on the neighbor's degree. Besides, a preferential exponent determines the tendency to contact with either small-degree or large-degree nodes. We use a dynamic messaging method to describe this complex contagion process and verify that the method is accurate to predict the spreading dynamics by numerical simulations on strongly heterogeneous networks. We find that the preferential contact mechanism leads to a crossover phenomenon in the growth of final adoption size. By reducing the preferential exponent, we observe a change from a continuous growth to an explosive growth and then to a continuous growth with the transmission rate of behavioral information. Moreover, we find that there is an optimal preferential exponent which maximizes the final adoption size at a fixed information transmission rate, and this optimal preferential exponent decreases with the information transmission rate. The used theory can be extended to other types of dynamics, and our findings provide useful and general insights into social contagion processes in the real world.
受接触能力限制的优先接触过程对复杂网络上的传播动力学有显著影响，但这种优先接触在社会传播中的影响尚未得到充分探索。为此，我们基于优先接触机制提出了一种行为传播模型。模型中，一个已采用行为的个体接触并试图将行为信息传递给他/她的一个邻居的概率取决于该邻居的度。此外，一个优先指数决定了与低度或高度节点接触的倾向。我们使用一种动态消息传递方法来描述这种复杂的传播过程，并通过在强异质网络上的数值模拟验证该方法能够准确预测传播动力学。我们发现，优先接触机制在最终采用规模的增长中导致了一种交叉现象。通过降低优先指数，我们观察到随着行为信息传播速率的变化，从连续增长到爆发式增长再到连续增长的转变。此外，我们发现存在一个最优优先指数，在固定的信息传播速率下，该指数能使最终采用规模最大化，并且这个最优优先指数随着信息传播速率的降低而减小。所使用的理论可以扩展到其他类型的动力学，我们的研究结果为现实世界中的社会传播过程提供了有用且通用的见解。
