What Does an Information Diffusion Model Tell about Social Network Structure?
Knowledge Acquisition: Approaches, Algorithms and Applications
A Study of Information Diffusion over a Realistic Social Network Model
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
Social Networks Analysis of the Knowledge Diffusion among University Students
KAM '09 Proceedings of the 2009 Second International Symposium on Knowledge Acquisition and Modeling - Volume 02
COMPENG '10 Proceedings of the 2010 Complexity in Engineering
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The Internet is radically changing the way from web 1.0, web 2.0 to web 3.0 in recent years and a new type of communications is on the rise, its call social network such as Facebook, Myspace, Skype and so on. There are many threats to an open Internet today. While the technical development of the Internet today has concentrated the awareness of several critical shortcomings in terms of performance, reliability, scalability, security and many other categories including societal, economical and business aspects. The rise of the Future Internet accelerates the creation of various large-scale social networks and considerable attention has been brought to social networks as an important medium for the information diffusion model, which could be used to describe the relationships and activities between human beings. The visualization of information diffusion model for Social Network in Future Internet is focused in this research. This research uses social network analysis (SNA) to analyze the key factors influencing information diffusion model about density, centrality and the cohesive subgroup, reveals useful insights which are the relationships and activities between human. The preprocessing with partitioning large-scale social networks is a clustering of the vertices in the network such that each vertex is assigned to exactly one cluster. The partitions store discrete characteristics of vertices. This research also presents each partitioning social network with visualization to show the information diffusion patterns of social network. They are applied as a guide to further investigation of social network behaviors to improve the security model and monitoring the risk for social networking in Future Internet.