Li Qian, Braunstein Lidia A, Havlin Shlomo, Stanley H Eugene
Department of Physics and Center for Polymer Studies, Boston University, Boston, Massachusetts 02215, USA.
Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Dec;84(6 Pt 2):066101. doi: 10.1103/PhysRevE.84.066101. Epub 2011 Dec 1.
We introduce an inflexible contrarian opinion (ICO) model in which a fraction p of inflexible contrarians within a group holds a strong opinion opposite to the opinion held by the rest of the group. At the initial stage, stable clusters of two opinions, A and B, exist. Then we introduce inflexible contrarians which hold a strong B opinion into the opinion A group. Through their interactions, the inflexible contrarians are able to decrease the size of the largest A opinion cluster and even destroy it. We see this kind of method in operation, e.g., when companies send free new products to potential customers in order to convince them to adopt their products and influence others to buy them. We study the ICO model, using two different strategies, on both Erdös-Rényi and scale-free networks. In strategy I, the inflexible contrarians are positioned at random. In strategy II, the inflexible contrarians are chosen to be the highest-degree nodes. We find that for both strategies the size of the largest A cluster decreases to 0 as p increases as in a phase transition. At a critical threshold value, p(c), the system undergoes a second-order phase transition that belongs to the same universality class of mean-field percolation. We find that even for an Erdös-Rényi type model, where the degrees of the nodes are not so distinct, strategy II is significantly more effective in reducing the size of the largest A opinion cluster and, at very small values of p, the largest A opinion cluster is destroyed.
我们引入了一种顽固逆向观点(ICO)模型,其中群体内一部分比例为p的顽固逆向者持有与群体其他成员相反的强烈观点。在初始阶段,存在A和B两种观点的稳定集群。然后我们将持有强烈B观点的顽固逆向者引入持有A观点的群体中。通过它们之间的相互作用,顽固逆向者能够减小最大的A观点集群的规模,甚至将其摧毁。我们能看到这种方法在实际中发挥作用,例如,当公司向潜在客户发送免费新产品以说服他们采用其产品并影响其他人购买时。我们在厄多斯 - 雷尼网络和无标度网络上使用两种不同策略研究ICO模型。在策略I中,顽固逆向者随机定位。在策略II中,顽固逆向者被选为度数最高的节点。我们发现,对于这两种策略,随着p的增加,最大的A集群规模会像在相变过程中一样减小到0。在一个临界阈值p(c)处,系统经历二阶相变,该相变属于平均场渗流的同一普适类。我们发现,即使对于节点度数差异不大的厄多斯 - 雷尼型模型,策略II在减小最大的A观点集群规模方面也显著更有效,并且在p非常小的值时,最大的A观点集群会被摧毁。