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arXiv 1012.2062math.PRcs.DMcs.GTcs.SIphysics.soc-ph
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随机网络中的扩散和级联行为

Diffusion and Cascading Behavior in Random Networks

Marc Lelarge

摘要:

新思想、新行为或新技术的传播已被广泛使用流行病模型进行了研究。在这里,我们考虑一个扩散模型中的个人的行为是一个战略选择的结果。我们研究了一个简单的二元选择协调对策,并给出了一个条件,使一个新的行动成为一个随机网络中的广泛传播。我们还分析了这个游戏的可能的均衡,并确定了两种策略在大的连通集共存的条件。最后,我们看看企业如何利用社交网络,以促进他们的目标与有限的信息。我们的结果与流行病模型的结果有很大的不同,表明连通性起着模糊的作用:当网络高度连通时,它允许扩散扩散,但扩散也受到高度稳定的节点的限制。

英文摘要:

The spread of new ideas, behaviors or technologies has been extensively studied using epidemic models. Here we consider a model of diffusion where the individuals' behavior is the result of a strategic choice. We study a simple coordination game with binary choice and give a condition for a new action to become widespread in a random network. We also analyze the possible equilibria of this game and identify conditions for the coexistence of both strategies in large connected sets. Finally we look at how can firms use social networks to promote their goals with limited information. Our results differ strongly from the one derived with epidemic models and show that connectivity plays an ambiguous role: while it allows the diffusion to spread, when the network is highly connected, the diffusion is also limited by high-degree nodes which are very stable.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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