A Amazon (co-purchasing network) dataset of 334,863 nodes and 925,872 edges, collected by Yang & Leskovec from Amazon website (2012). Each record contains product-product co-purchasing edges and product-category communities. The dataset is notable for its product co-purchasing network with ground-truth communities from categories. Intended for research into community detection, recommendation systems, and product relationship analysis.
A DBLP (co-authorship network) dataset of 317,080 nodes and 1,049,866 edges, collected by Yang & Leskovec from DBLP bibliography (2012). Each record contains author-author co-authorship edges and publication-venue communities. The dataset is notable for its academic collaboration network with ground-truth communities from publication venues. Intended for research into community detection, network evolution, and scientific collaboration analysis.
A Facebook (ego-networks) dataset of 4,039 nodes and 88,234 edges, collected by McAuley & Leskovec via Facebook app survey (2012). Each record contains user-user friendship edges and ego-network circles. classic ego-network dataset with ground-truth social circles. Suitable for social network analysis, community detection, and circle prediction.
A Twitter (ego-networks) dataset of 81,306 nodes and 1,768,149 edges, collected by McAuley & Leskovec via Twitter public crawl (2012). Each record contains directed user-user follow edges and ego-network circles. The dataset is notable for its directed ego-network dataset with ground-truth social circles. Intended for research into social network analysis, influence propagation, and community detection.