Social network analysis algorithm on a many-core GPU

Proliferation of social network service permeates lives of people on internet, and its social, political and cultural significance prompts the need to understand and to analyze the contents and structures of such services. The sheer volume of such social network is enormous, and it necessitates development and implementation of efficient social network analysis algorithms. Among these, Influence Maximization is one example of such algorithm. The objective of the influence maximization algorithm is to find a small subset of nodes, so-called seed-nodes, that result in maximization of the spread of influence through the edges in the graph which represents connections in social network.