Abstract
Analysing complex natural phenomena often requires synthesized data that matches observed characteristics. Graph models are widely used in analyzing the Web in general, but are less suitable for modeling the Blogosphere. While blog networks resemble many properties of Web graphs, the dynamic nature of the Blogosphere, its unique structure and the evolution of the link structure due to blog readership and social interactions are not captured by the existing models. We describe an agent-based simulation model to construct blog graphs that exhibit properties similar to the real world blog networks in their degree distributions, degree correlation, clustering coefficient and reciprocity. The model can help researchers analyze the Blogosphere and facilitates the development and testing of new algorithms.
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