Online social networks have become an increasingly important medium for people to create and share information such as latest news headlines and personal status updates. In light of the significant role online social networks have played in recent events and crisis, it becomes urgent and necessary to understand the diffusion process of information over large scale online social networks. However, due to the intricacy of human dynamics and social interactions, the vast scale of online social networks, the heterogeneity and diversity of social networks and medias, understanding information diffusion in social networks remains a significant challenge. This project proposes dynamic mathematical modeling approach to characterize and predict the temporal and spatial dynamics of information diffusion in online social networks. The goal of this research is to increase the understanding on how information cascades along friendship hops or shared interest in social networks, and to use the improved knowledge to develop new techniques and algorithms for maximizing the diffusion of positive information or influence over social networks.
|Effective start/end date||9/1/12 → 8/31/16|
- National Science Foundation (NSF): $250,000.00