document: On compressing social networks Motivated by structural properties of the Web graph that support efficient data structures for in memory adjacency queries , we study the extent to which a large network can be compressed . Boldi and Vigna ( WWW 2004 ) , showed that Web graphs can be compressed down to three bits of storage per edge ; we study the compressibility of social networks where again adjacency queries are a fundamental primitive . To this end , we propose simple combinatorial formulations that encapsulate efficient compressibility of graphs . We show that some of the problems are NP-hard yet admit effective heuristics , some of which can exploit properties of social networks such as link reciprocity . Our extensive experiments show that social networks and the Web graph exhibit vastly different compressibility characteristics .
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