Convergence in (Social) Influence Networks

机译：（社会）影响力网络中的融合

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We study the convergence of influence networks, where each node changes its state according to the majority of its neighbors. Our main result is a new Ω(n~2/ log~2 n) bound on the convergence time in the synchronous model, solving the classic "Democrats and Republicans" problem. Furthermore, we give a bound of θ(n~2) for the sequential model in which the sequence of steps is given by an adversary and a bound of θ(n) for the sequential model in which the sequence of steps is given by a benevolent process.

机译：我们研究影响网络的收敛性，其中每个节点根据其大多数邻居改变其状态。我们的主要结果是在同步模型的收敛时间上得到一个新的Ω（n〜2 / log〜2 n）界线，从而解决了经典的“民主与共和党”问题。此外，对于由对手给出步骤顺序的顺序模型，给定θ（n〜2）的界线，由a给出步骤序列的顺序模型，给定θ（n）的界线。仁慈的过程。

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《International symposium on distributed computing》|2013年|433-446|共14页
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Silvio Frischknecht; Barbara Keller; Roger Wattenhofer;
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Social Networks; Stabilization; Democrats and Republicans; Majority Function; Equilibrium;

机译：社交网络;稳定;民主党人和共和党人;多数功能;平衡;

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Convergence in (Social) Influence Networks

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