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Generative Model To Construct Blog and Post Networks In Blogosphere

Generative Model To Construct Blog and Post Networks In Blogosphere. Amit Karandikar, Akshay Java, Anupam Joshi, Tim Finin. AIM To simulate the graph structures that look like the “real” Blogosphere. http://prefuse.org/gallery/. Graphs are everywhere.

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Generative Model To Construct Blog and Post Networks In Blogosphere

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  1. Generative Model To Construct Blog andPost Networks In Blogosphere Amit Karandikar, Akshay Java, Anupam Joshi, Tim Finin AIMTo simulate the graph structures that look like the “real” Blogosphere http://prefuse.org/gallery/ Graphs are everywhere .. Ok, but why?To test the new algorithmsfor blogosphere, To save time and effortin gathering and preprocessing the "real" data, To extrapolate the properties by varying parameters .. and so are Power Laws! 20% of the population owns 80% of the wealthReal networks often tend to show the “rich get richer” phenomenon. Already popular website is bound to get more inlinks. • Blogger characteristics • Blog writers are enthusiastic blog readers • Most bloggers post infrequently • Active bloggers follow popular blogs, friends blogs and interact online. Scale-free networks The likelihood of linking to a popular website is higher • Ok, power laws: • So what’s the big deal? • Makes ranking of web content possible • (e.g. Google ranking) • Shows that only a few things are more important than others Preferential Attachment • Approach • Model bloggers with Read, Write, Idle states • Select blog writers preferentially based on the outdegree of the blog node • Perform preferential random walk in the blog neighborhood based on the indegree of the neighbor • With a small probability perform totally random reading and writer selection Conclusion We were able to simulate the blogosphere propertiessuch as degree distributions, average shortest path, diameter, degree correlations, reciprocity, size of connected components

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