Liu Quan-Hui, Zhong Lin-Feng, Wang Wei, Zhou Tao, Eugene Stanley H
Web Sciences Center, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
Center for Polymer Studies and Department of Physics, Boston, Massachusetts 02215, USA.
Chaos. 2018 Jan;28(1):013120. doi: 10.1063/1.5010002.
What we are learning about the ubiquitous interactions among multiple social contagion processes on complex networks challenges existing theoretical methods. We propose an interactive social behavior spreading model, in which two behaviors sequentially spread on a complex network, one following the other. Adopting the first behavior has either a synergistic or an inhibiting effect on the spread of the second behavior. We find that the inhibiting effect of the first behavior can cause the continuous phase transition of the second behavior spreading to become discontinuous. This discontinuous phase transition of the second behavior can also become a continuous one when the effect of adopting the first behavior becomes synergistic. This synergy allows the second behavior to be more easily adopted and enlarges the co-existence region of both behaviors. We establish an edge-based compartmental method, and our theoretical predictions match well with the simulation results. Our findings provide helpful insights into better understanding the spread of interactive social behavior in human society.
我们对复杂网络上多种社会传染过程之间普遍存在的相互作用的了解，对现有的理论方法提出了挑战。我们提出了一种交互式社会行为传播模型，其中两种行为在复杂网络上依次传播，一种接一种。采用第一种行为对第二种行为的传播具有协同或抑制作用。我们发现，第一种行为的抑制作用会导致第二种行为传播的连续相变变得不连续。当采用第一种行为的效果变得协同时，第二种行为的这种不连续相变也可以变为连续相变。这种协同作用使第二种行为更容易被采用，并扩大了两种行为的共存区域。我们建立了一种基于边的划分方法，我们的理论预测与模拟结果吻合良好。我们的研究结果为更好地理解人类社会中交互式社会行为的传播提供了有益的见解。
