A Wikipedia (English edition, 2013 snapshot) dataset of 4,203,323 article nodes and 101,311,614 directed hyperlink edges, collected by Leskovec et al. via Wikipedia XML dump (SNAP, 2013). Each record contains source article ID, destination article ID (directed hyperlink). Complete English Wikipedia hyperlink graph from a 2013 snapshot — one of the largest hyperlink networks publicly available, capturing the full link structure of 4.2M Wikipedia articles.. Suitable for hyperlink network analysis, graph evolution studies, link prediction, Wikipedia structure research, large-scale directed graph algorithms.
A US Patent and Trademark Office (1963–1999) dataset of 3,774,768 nodes and 16,518,947 edges, collected by B.H. Hall et al.. Each record contains directed: True, weighted: False. Massive directed citation network of 3.7M US patents spanning 1963–1999 — one of the largest citation networks available.. Suitable for citation network analysis, technology diffusion, innovation research.
The citation network of the arXiv High Energy Physics – Phenomenology (hep-ph) section, from SNAP (the KDD Cup 2003 data), as distributed by KONECT (cit-HepPh): 421,578 citations among 34,546 papers posted between January 1993 and April 2003. An edge points from a citing paper to the paper it cites. Useful for citation analysis, scientific impact and the growth of networks over time.
A CiteSeer digital library dataset of 384,413 nodes and 1,751,463 edges, collected by KONECT via CiteSeer database. Each record contains directed: True, weighted: False. Large directed citation network from the CiteSeer digital library — widely used in graph learning research.. Suitable for citation network analysis, graph neural networks benchmark, community detection.
A Google Scholar dataset of 82,937 papers, 148,116 citations, collected by Google Scholar via academic citation data. Each record contains citation edges between papers, node IDs, node names (titles), node types (paper, author, etc.), edge types (cites, etc.). Academic citation network from Google Scholar, capturing the flow of scientific knowledge through citation relationships. Suitable for citation analysis, academic network analysis, research impact, knowledge flow studies, scholarly communication.
The co-authorship network of the arXiv High Energy Physics – Phenomenology (hep-ph) section, as distributed by KONECT (ca-cit-HepPh), from SNAP's arXiv data: 28,093 authors linked by 4,596,803 collaboration records, one for each pair of authors on a paper, published between March 1992 and March 2002. The records form 3,148,447 distinct co-author pairs, each timestamped with its paper's date. Useful for studying scientific collaboration, the growth and densification of networks over time, and community structure.
A arXiv High Energy Physics — Theory (1991–2003) dataset of 27,770 nodes and 352,807 edges, collected by J. Leskovec et al. via arXiv. Each record contains directed: True, weighted: False. Citation network of HEP-TH papers on arXiv — directed, covers theoretical physics literature.. Suitable for citation network analysis, academic influence, graph mining.
A Cora machine learning paper database dataset of 23,166 nodes and 91,500 edges, collected by McCallum et al.. Each record contains directed: True, weighted: False. Classic citation network of machine learning papers — one of the most used benchmarks for graph neural network node classification.. Suitable for graph neural networks, node classification, citation network analysis.
A PubMed dataset of 19,717 nodes, 44,327 edges, 3 classes, collected by Yang et al. (ICML 2016). Each record contains node features, citation edges, class labels. PubMed network with bag-of-words features. Suitable for node classification, semi-supervised learning, graph neural networks.
A DBLP Computer Science Bibliography dataset of 12,591 nodes and 49,743 edges, collected by KONECT via DBLP database. Each record contains directed: True, weighted: False. Directed citation network of computer science papers in the DBLP bibliography.. Suitable for citation network analysis, academic influence, community detection.
A CiteSeer dataset of 3,327 nodes, 4,676 edges, 6 classes, collected by Yang et al. (ICML 2016). Each record contains node features, citation edges, class labels. CiteSeer network with bag-of-words features. Suitable for node classification, semi-supervised learning, graph neural networks.
A Cora dataset of 2,708 nodes, 5,278 edges, 7 classes, collected by Yang et al. (ICML 2016). Each record contains node features, citation edges, class labels. Cora network with bag-of-words features. Suitable for node classification, semi-supervised learning, graph neural networks.
A Terrorist Relations dataset of 881 nodes, 8,592 edges, 4 classes, collected by Yang et al. (ICML 2016). Each record contains node features, citation edges, class labels. Terrorist Relations network with bag-of-words features. Suitable for node classification, semi-supervised learning, graph neural networks.
A Terrorist Attacks dataset of 645 nodes, 3,172 edges, 6 classes, collected by Yang et al. (ICML 2016). Each record contains node features, citation edges, class labels. Terrorist Attacks network with bag-of-words features. Suitable for node classification, semi-supervised learning, graph neural networks.
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