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Evolution of Opinions on Social Networks in the Presence of Competing Committed Groups

机译:参与竞争的群体对社交网络观点的演变

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摘要

Public opinion is often affected by the presence of committed groups of individuals dedicated to competing points of view. Using a model of pairwise social influence, we study how the presence of such groups within social networks affects the outcome and the speed of evolution of the overall opinion on the network. Earlier work indicated that a single committed group within a dense social network can cause the entire network to quickly adopt the group's opinion (in times scaling logarithmically with the network size), so long as the committed group constitutes more than about of the population (with the findings being qualitatively similar for sparse networks as well). Here we study the more general case of opinion evolution when two groups committed to distinct, competing opinions and , and constituting fractions and of the total population respectively, are present in the network. We show for stylized social networks (including Erdös-Rényi random graphs and Barabási-Albert scale-free networks) that the phase diagram of this system in parameter space consists of two regions, one where two stable steady-states coexist, and the remaining where only a single stable steady-state exists. These two regions are separated by two fold-bifurcation (spinodal) lines which meet tangentially and terminate at a cusp (critical point). We provide further insights to the phase diagram and to the nature of the underlying phase transitions by investigating the model on infinite (mean-field limit), finite complete graphs and finite sparse networks. For the latter case, we also derive the scaling exponent associated with the exponential growth of switching times as a function of the distance from the critical point.
机译:公众意见经常受到致力于竞争观点的坚定的个人群体的影响。使用成对的社会影响模型,我们研究了社交网络中此类群体的存在如何影响网络上总体意见的结果和发展速度。较早的工作表明,在一个密集的社交网络中,一个致力于的群体可以使整个网络迅速采纳该群体的观点(有时与网络规模成对数关系),只要该承诺的群体构成人口总数的大约一半以上(稀疏网络的发现在质量上也相似)。在这里,当网络中存在两个分别致力于截然不同的,相互竞争的观点的和,分别构成总人口的一部分和的时候,我们研究观点演化的更一般情况。对于程式化的社交网络(包括Erdös-Rényi随机图和Barabási-Albert无标度网络),我们证明了该系统在参数空间中的相图由两个区域组成,一个区域中两个稳定稳态共存,其余区域仅存在一个稳定的稳态。这两个区域由两条切线相交并终止于尖点(临界点)的折叠分叉(螺状)线隔开。通过研究无限(均值极限),有限完整图和有限稀疏网络上的模型,我们可以提供有关相图和基础相变本质的进一步见解。对于后一种情况,我们还得出与切换时间的指数增长相关的缩放指数,该缩放指数是与临界点的距离的函数。

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