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Understanding Community Effects on Information Diffusion

机译:了解社区对信息传播的影响

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In social network research, community study is one flourishing aspect which leads to insightful solutions to many practical challenges. Despite the ubiquitous existence of communities in social networks and their properties of depicting users and links, they have not been explicitly considered in information diffusion models. Previous studies on social networks discovered that links between communities function differently from those within communities. However, no information diffusion model has yet considered how the community structure affects the diffusion process. Motivated by this important absence, we conduct exploratory studies on the effects of communities in information diffusion processes. Our observations on community effects can help to solve many tasks in the studies of information diffusion. As an example, we show its application in solving one of the most important problems about information diffusion: the influence maximization problem. We propose a community-based fast influence (CFI) model which leverages the community effects on the diffusion of information and provides an effective approximate algorithm for the influence maximization problem.
机译:在社交网络研究中,社区研究是一个蓬勃发展的方面,它为许多实际挑战提供了有见地的解决方案。尽管社交网络中普遍存在社区,并且社区具有描述用户和链接的属性,但尚未在信息传播模型中明确考虑它们。先前对社交网络的研究发现,社区之间的链接与社区内部的链接具有不同的功能。但是,还没有信息传播模型考虑社区结构如何影响传播过程。出于这种重要缺席的动机,我们对社区在信息传播过程中的影响进行了探索性研究。我们对社区影响的观察可以帮助解决信息传播研究中的许多任务。例如,我们展示了它在解决有关信息传播的最重要问题之一:影响最大化问题中的应用。我们提出了一种基于社区的快速影响(CFI)模型,该模型利用社区对信息传播的影响,并为影响最大化问题提供了有效的近似算法。

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