有限总体上的谣言消除过程
A process of rumor scotching on finite populations
摘要：
谣言传播是社会和技术网络中普遍存在的现象。传统的模型认为谣言是通过传播者和传播者之间的成对相互作用传播的。扩张器只有在接触扩张器或加劲器后才能变成加劲器。在这里，我们提出了一个模型，考虑到传统的假设，但stiflers是积极的，并试图苏格兰的谣言传播者。基于密度依赖马尔可夫链的收敛性理论，给出了一种分析方法，分析了在有限均匀混合种群中，最后一个比例解的渐近性.我们在随机图和无标度网络中进行了蒙特卡罗模拟，并验证了均匀混合种群的结果可以近似于随机图，但不适用于无标度网络。此外，关于一个异质混合人口的过程中，我们得到了一组微分方程，描述的概率，一个人在每个状态的时间演化。我们的模型可以应用于研究系统中，知情的代理人试图阻止谣言传播。此外，我们的研究结果可以被认为是制定最佳的信息传播策略和方法来控制谣言传播。
英文摘要：
Rumor spreading is a ubiquitous phenomenon in social and technological networks. Traditional models consider that the rumor is propagated by pairwise interactions between spreaders and ignorants. Spreaders can become stiflers only after contacting spreaders or stiflers. Here we propose a model that considers the traditional assumptions, but stiflers are active and try to scotch the rumor to the spreaders. An analytical treatment based on the theory of convergence of density dependent Markov chains is developed to analyze how the final proportion of ignorants behaves asymptotically in a finite homogeneously mixing population. We perform Monte Carlo simulations in random graphs and scale-free networks and verify that the results obtained for homogeneously mixing populations can be approximated for random graphs, but are not suitable for scale-free networks. Furthermore, regarding the process on a heterogeneous mixing population, we obtain a set of differential equations that describes the time evolution of the probability that an individual is in each state. Our model can be applied to study systems in which informed agents try to stop the rumor propagation. In addition, our results can be considered to develop optimal information dissemination strategies and approaches to control rumor propagation.
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