Xian Teng

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In spreading dynamics in social networks, there exists an optimal set of influencers whose activation can induce a global-scale cascade of information. To find the optimal, or minimal, set of spreaders, a method based on collective influence theory has been proposed for spreading dynamics with a continuous phase transition that can be mapped to optimal(More)
Identifying highly susceptible individuals in spreading processes is of great significance in controlling outbreaks. In this paper, we explore the susceptibility of people in susceptible-infectious-recovered (SIR) and rumor spreading dynamics. We first study the impact of community structure on people's susceptibility. Despite that the community structure(More)
Identifying the most influential spreaders that maximize information flow is a central question in network theory. Recently, a scalable method called "Collective Influence (CI)" has been put forward through collective influence maximization. In contrast to heuristic methods evaluating nodes' significance separately, CI method inspects the collective(More)
In social networks, the collective behavior of large populations can be shaped by a small set of influencers through a cascading process induced by " peer pressure ". For large-scale networks, efficient identification of multiple influential spreaders with a linear algorithm in threshold models that exhibit a first-order transition still remains a(More)
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