Abstract
Graphs resulting from human behavior (the web graph, friendship graphs, etc.) have hitherto been viewed as a monolithic class of graphs with similar characteristics; for instance, their degree distributions are markedly heavy tailed. In this paper we take our understanding of behavioral graphs a step further by showing that an intriguing empirical property of web graphs---their compressibility---cannot be exhibited by well-known graph models for the web and for social networks. We then develop a more nuanced model for web graphs and show that it does exhibit compressibility, in addition to previously modeled web graph properties.
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