Influence Maximization & Misinformation Countermeasures

Online social networks (OSNs) like Facebook, Twitter, etc. are excellent media for viral marketing. One of the fundamental problems for viral marketing in OSNs is the influence maximization (IM) problem, where the company aims at reaching a widespread product adoption via word-of-mouth effect by providing free samples of a product to a set of influential individuals. In a graph G, IM can be restate as finding at most k seed nodes (influential individuals) that can influence the maximum number of nodes, either directly or indirectly. A variation of IM, the threshold activation problem (TAP), does not restrict the number of seed nodes. Instead, it aims at using minimum number of seed nodes to influence at least fraction of all nodes. As the graph is usually gigantic and also probabilistic, exact solutions to neither IM or TAP are accessible with reasonable computational resources. Thus, the solutions rely on sampling methods and the main objective of research is to design approaches to use less samples while maintaining solution quality.

Objectives:

  • Design efficient sampling methods for estimating influence spread in large-scale OSNs
  • Study variations of IM, TAP (for example: by considering external influence or different diffusion models)

Publications:

  • Xiang Li, J David Smith, Thang Dinh, and My T. Thai. “Why approximate when you can get the exact? Optimal Targeted Viral Marketing at Scale.,” in Proceedings of the IEEE Int Conference on Computer Communications (INFOCOM), 2017 [arXiv]
  • H. Zhang, H. Zhang, A. Kuhnle, and and M. T. Thai. “Profit Maximization for Multiple Products in Online Social Networks,” in Proceedings of the IEEE Int Conference on Computer Communications (INFOCOM), 2016
  • H. T. Nguyen, M. T. Thai, and T. N. Dinh. “Stop-and-Stare: Optimal Sampling Algorithms for Viral Marketing in Billion-scale Networks,” in Proceedings of ACM SIGMOD/POSD Conference (SIGMOD), 2016
  • H. Zhang, M. Alim, X. Li, M. T. Thai, and H. Nguyen. “Misinformation in Online Social Networks: Catch Them All with Limited Budget,” in ACM Transactions on Information Systems, 2016
  • H. Zhang, D. T. Nguyen, S. Das, H. Zhang, and M. T. Thai. “Least Cost Influence Maximization Across Multiple Social Networks,” in IEEE Transactions on Networking (ToN), 2015
  • H. Zhang, H. Zhang, X. Li, and M. T. Thai. “Limiting the Spread of Misinformation while Effectively Raising Awareness in Social Networks,” in Proceedings of the 4th International Conference on Computational Social Networks (CSoNet), 2015
  • H Zhang, M. Alim, M. T. Thai, and H. Nguyen. “Monitor Placement to Timely Detect Misinformation in Online Social Networks,” in Proceedings of the 2015 IEEE International Conference on Communications (ICC), 2015
  • H. Zhang, D. T. Nguyen, S. Das, H. Zhang, and M. T. Thai. “Least Cost Influence Maximization Across Multiple Social Networks,” in IEEE Transactions on Networking, 2015