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Massive Social Network Analysis: Mining Twitter for Social Good
2010
2010 39th International Conference on Parallel Processing
Social networks produce an enormous quantity of data. Facebook consists of over 400 million active users sharing over 5 billion pieces of information each month. Analyzing this vast quantity of unstructured data presents challenges for software and hardware. We present GraphCT, a Graph Characterization Toolkit for massive graphs representing social network data. On a 128processor Cray XMT, GraphCT estimates the betweenness centrality of an artificially generated (R-MAT) 537 million vertex, 8.6
doi:10.1109/icpp.2010.66
dblp:conf/icpp/EdigerJRBCFR10
fatcat:i6clwbmjuzetxgntubekzl3qxq