Influence Maximization: How to Influence Supporters while Avoiding Detractors
COM1 Level 3
MR1, COM1-03-19
Abstract:
In social networks, diffusion is a process through which information propagates in the network. Each user of the network can exert influence on his/her neighbors via sending information. A classical problem is that of finding an initial seed set of users such that when the information originates at the seed set, it reaches the maximum number of users. This is known as the influence maximization problem. In constraint influence maximization, each node of the network is labeled either as supporter or detractor. The goal is to find a good seed set such that the information spread among supporters is maximized while the information spread among detractors is minimized. In this talk we will introduce the influence maximization problem, survey a few known results, and present hardness and algorithmic results for a version of the constraint influence maximization problem.
This is a joint work with Samik Basu, Madhavan Rajagopalan, and Naresh Somisetty.
Biodata:
Pavan Aduri is a faculty of Computer Science at Iowa State University. His research interests include complexity theory and algorithms. He received his PhD from University at Buffalo in 2001.