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Steering opinion dynamics via containment control.
Computational Social Networks Pub Date : 2017-11-27 , DOI: 10.1186/s40649-017-0048-0
Pietro DeLellis 1 , Anna DiMeglio 1 , Franco Garofalo 1 , Francesco Lo Iudice 1
Affiliation  

In this paper, we model the problem of influencing the opinions of groups of individuals as a containment control problem, as in many practical scenarios, the control goal is not full consensus among all the individual opinions, but rather their containment in a certain range, determined by a set of leaders. As in classical bounded confidence models, we consider individuals affected by the confirmation bias, thus tending to influence and to be influenced only if their opinions are sufficiently close. However, here we assume that the confidence level, modeled as a proximity threshold, is not constant and uniform across the individuals, as it depends on their opinions. Specifically, in an extremist society, the most radical agents (i.e., those with the most extreme opinions) have a higher appeal and are capable of influencing nodes with very diverse opinions. The opposite happens in a moderate society, where the more connected (i.e., influential) nodes are those with an average opinion. In three artificial societies, characterized by different levels of extremism, we test through extensive simulations the effectiveness of three alternative containment strategies, where leaders have to select the set of followers they try to directly influence. We found that, when the network size is small, a stochastic time-varying pinning strategy that does not rely on information on the network topology proves to be more effective than static strategies where this information is leveraged, while the opposite happens for large networks where the relevance of the topological information is prevalent.

中文翻译:

通过围堵控制来指导意见动态。

在本文中,我们将影响个人意见的问题建模为一种遏制控制问题,因为在许多实际情况下,控制目标不是所有个人意见之间的完全共识,而是他们在一定范围内的遏制,由一组领导者决定。就像在经典的有界置信度模型中一样,我们考虑受确认偏差影响的个体,因此倾向于仅在其意见足够接近时才会受到影响。但是,这里我们假设以接近度阈值为模型的置信度在各个个体之间不是恒定不变的,因为它取决于他们的意见。具体而言,在极端主义社会中,最激进的特工(即 那些拥有最极端观点的人)具有更高的吸引力,并且能够以非常不同的观点影响节点。相反的情况发生在温和的社会中,其中联系更紧密(即有影响力)的节点是具有一般意见的节点。在三个以极端主义程度不同为特征的人工社会中,我们通过广泛的模拟测试了三种替代性遏制策略的有效性,其中领导人必须选择他们试图直接影响的一群追随者。我们发现,当网络规模较小时,一种不依赖于网络拓扑信息的随机时变固定策略被证明比利用静态信息的静态策略更有效,
更新日期:2017-11-27
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