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ASUNAM
2011
IEEE

Content-based Modeling and Prediction of Information Dissemination

9 years 2 months ago
Content-based Modeling and Prediction of Information Dissemination
—Social and communication networks across the world generate vast amounts of graph-like data each day. The modeling and prediction of how these communication structures evolve can be highly useful for many applications. Previous research in this area has focused largely on using past graph structure to predict future links. However, a useful observation is that many graph datasets have additional information associated with them beyond just their graph structure. In particular, communication graphs (such as email, twitter, blog graphs, etc.) have information content associated with their graph edges. In this paper we examine the link between information content and graph structure, proposing a new graph modeling approach, GC-Model, which combines both. We then apply this model to multiple real world communication graphs, demonstrating that the built models can be used effectively to predict future graph structure and information flow. On average, GC-Model’s top predictions covered...
Kathy Macropol, Ambuj K. Singh
Added 12 Dec 2011
Updated 12 Dec 2011
Type Journal
Year 2011
Where ASUNAM
Authors Kathy Macropol, Ambuj K. Singh
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