Game Theoretical Study of Trend Diffusion and Community Formation in Social Networks
- Biying SHOU (Principal Investigator / Project Coordinator)Department of Management Sciences
- Chris CANNINGS (Co-Investigator)
- Jianwei HUANG (Co-Investigator)
DescriptionSocial networks are the mainstream medium through which trends spread across society. With the growth of massive online social networks such as Facebook, Twitter and LiveJournal, it is more important than ever to understand how the characteristics of social networks affect the diffusion of trends and the formation of communities. Much of the previous research focused upon Network Coordination Games, where individuals choose between two trends. However, real scenarios often include many more trends, with individuals adopting multiple trends simultaneously. By introducing many significant generalizations into the Network Coordination Game (such as the potential for individuals to adopt multiple trends simultaneously, and the potential for asymmetric influence relationships between individuals), we obtain a model applicable to a multitude of network diffusion scenarios. By exploiting relationships with Network Congestion Games and statistical mechanics, we identify conditions under which the diffusion dynamics eventually stabilize. We propose to develop efficient algorithms for planning trend dissemination. We also propose to conduct a rigorous mathematical investigation of the pure Nash equilibriums of our models, and relate these equilibriums to real community data. This could potentially lead to great advances in the understanding of trend diffusion and community formation.
|Effective start/end date||1/04/13 → 2/07/14|