Influence maximization is the problem of finding k most influential nodes in a social network. Many works has been done in two different categories, greedy approach and heuristic approach. The first one has better influence spread, but lower scalability on large networks. Second category is scalable and fast but not dependable on different networks, so working to improve scalability of greedy approach is still in progress. We work on both categories, first improving the speed of greedy algorithms and second extracting structural features to be used as the building blocks to design more dependable heuristic methods.
email: heidari_mehdi [at] ut.ac.ir
email: asadpour [AT] ut.ac.ir