Yuan Ye, Chen Xuebo, Sun Qiubai, Huang Tianyun
School of Electronics and Information Engineering, University of Science and Technology Liaoning, Anshan, Liaoning, People's Republic of China.
Graduate School, University of Science and Technology Liaoning, Anshan, Liaoning, People's Republic of China.
PLoS One. 2017 Aug 23;12(8):e0183686. doi: 10.1371/journal.pone.0183686. eCollection 2017.
In the animal world, various kinds of collective motions have been found and proven to be efficient ways of carrying out some activities such as searching for food and avoiding predators. Many scholars research the interactions of collective behaviors of human beings according to the rules of collective behaviors of animals. Based on the Lennard-Jones potential function and a self-organization process, our paper proposes a topological communication model to simulate the collective behaviors of human beings. In the results of simulations, we find various types of collective behavior and fission behavior and discover the threshold for the emergence of collective behavior, which is the range five to seven for the number of topology K. According to the analysis of network properties of the model, the in-degree of individuals is always equal to the number of topology. In the stable state, the out-degrees of individuals distribute around the value of the number of topology K, except that the out-degree of a single individual is approximately double the out-degrees of the other individuals. In addition, under different initial conditions, some features of different kinds of networks emerge from the model. We also find the leader and herd mentality effects in the characteristics of the behaviors of human beings in our model. Thus, this work could be used to discover how to promote the emergence of beneficial group behaviors and prevent the emergence of harmful behaviors.
在动物世界中，人们已经发现并证明了各种集体运动是开展某些活动（如觅食和躲避捕食者）的有效方式。许多学者根据动物集体行为的规则来研究人类集体行为的相互作用。基于 Lennard-Jones 势函数和自组织过程，我们的论文提出了一种拓扑通信模型来模拟人类的集体行为。在模拟结果中，我们发现了各种类型的集体行为和裂变行为，并发现了集体行为出现的阈值，即拓扑 K 的数量范围为 5 到 7。根据对该模型网络属性的分析，个体的入度始终等于拓扑数量。在稳定状态下，个体的出度围绕拓扑 K 的数量值分布，除了单个个体的出度大约是其他个体出度的两倍。此外，在不同的初始条件下，模型会呈现出不同类型网络的一些特征。我们还在模型中人类行为的特征中发现了领导者和从众心理效应。因此，这项工作可用于发现如何促进有益群体行为的出现并防止有害行为的出现。
