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Given a large graph with millions or billions of nodes and edges, like a who-follows-whom Twitter graph, how do we scalably compute its statistics, summarize its patterns, spot anomalies, visualize and make sense of it? We present OPAvion, a graph mining system that provides a scalable, interactive workflow to accomplish these analysis tasks. OPAvion consists of three modules: (1) The Summarization module (Pegasus) operates off-line on massive, diskresident graphs and computes graph statistics,doi:10.1145/2213836.2213941 dblp:conf/sigmod/AkogluCKKF12 fatcat:oj7arrwbvzf33ivfphz2llib4e