主 题：Influence Analysis towards Social Network
Zhipeng Cai received his PhD and MS degrees from the Department of Computing Science at University of Alberta, and BS degree from the Department of Computer Science and Engineering at Beijing Institute of Technology. He is currently an Assistant Professor in the Department of Computer Science at Georgia State University. Dr. Cai’s research areas focus on Networking and Big data. Dr. Cai is the recipient of an NSF CAREER Award. He actively participates in professional activities including several editor positions and chair positions for many prestigious journals and conferences, including associate editor for International Journal of Sensor Networks, guest editors for Algorithmca, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Theoretical Computer Science, and program chairs for COCOON 2014, WASA 2014, IPCCC 2013, and ISBRA 2013.
Online social networks have gained significant popularity recently. The problem of influence maximization in online social networks has been extensively studied. However, in prior works, influence propagation in the physical world, which is also an indispensable factor, is not considered. The Location- Based Social Networks (LBSNs) are a special kind of online social networks in which people can share location-embedded information. In this paper, we make use of mobile crowdsourced data obtained from location-based social network services to study influence maximization in LBSNs. A novel network model and an influence propagation model taking influence propagation in both online social networks and the physical world into consideration are proposed. An event activation position selection problem is formalized and a corresponding solution is provided. The experimental results indicate that the proposed influence propagation model is meaningful and the activation position selection algorithm has high performance.