Finding patterns in blog shapes and blog evolution
ICWSM(2007)
摘要
Can we cluster blogs into types by considering their typi- cal posting and linking behavior? How do blogs evolve over time? In this work we answer these questions, by providing several sets of blog and post features that can help distin- guish between blogs. The first two sets of features focus on the topology of the cascades that the blogs are involved in, and the last set of features focuses on the temporal evolu- tion, using chaotic and fractal ideas. We also propose to use PCA to reduce dimensionality, so that we can visualize the resulting clouds of points. We run all our proposed tools on the icwsm dataset. Our findings are that (a) topology features can help us distin- guish blogs, like 'humor' versus 'conservative' blogs (b) the temporal activity of blogs is very non-uniform and bursty but (c) surprisingly often, it is self-similar and thus can be com- pactly characterized by the so-called bias factor (the '80' in a recursive 80-20 distribution).
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关键词
principal component analysis,bursty behavior,social network analysis
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