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    Influence Diffusion Dynamics and Influence Maximization in Complex Social Networks
    Update time: 2011-12-05
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    Title:Influence Diffusion Dynamics and Influence Maximization in Complex Social Networks
    Speaker:Dr.Wei Chen, Microsoft Research Asia
    Time:2:00pm—3:00pm, November 29th, 2011 (Tuesday)
    Place:Room 440, 4th Floor, ICT, CAS
    Online social and information networks such as Facebook and Twitter provide large platforms for studying the diffusion of news, ideas, innovations, adoption of products, etc., which we all refer to as influence diffusion. Several influence diffusion models have been proposed, such as the independent cascade (IC) model and the linear threshold (LT) model. Influence maximization is the problem of selecting a small number of seed nodes in a social network such that their influence coverage after the influence diffusion process is maximized. In this talk, I will first present our recent results on designing scalable influence maximization algorithms for the IC and LT models, and then show how to extend these models to cover more complex influence diffusion dynamics, such as emergence and propagation of negative opinions, competing influence diffusion, and diffusion on networks with distrust relationships, and how to achieve efficient influence maximization in these models.
    Wei Chen is a Lead Researcher in the Theory Group of Microsoft Research Asia, in Beijing China, and an Adjunct Professor at Tsinghua University. His research interests include computational and game theoretic aspects of social networks, algorithmic game theory, distributed computing, and fault tolerance. For more information, you are welcome to visit his home page at http://research.microsoft.com/en-us/people/weic/.

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