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This document provides an introduction to analyzing social graphs using graph databases. It discusses using Neo4j to store social graph data and analyze centrality and clustering coefficients. Sample code is shown for inserting nodes and relationships in Neo4j and traversing the graph. Analyzing a sample social network dataset found centrality values ranged from 1 to over 900, with a median of 10,
Stanford Large Network Dataset Collection
Open research positions in SNAP group are available at undergraduate, graduate and postdoctoral levels. Social networks : online social networks, edges represent interactions between people Networks with ground-truth communities : ground-truth network communities in social and information networks Communication networks : email communication networks with edges representing communication Citation
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