The wikilink network of the English Wikipedia, as distributed by KONECT (wikipedia_link_en), built from the Wikimedia dumps: 12,150,976 articles and 378,142,420 directed links between them, where a link from A to B means article A links to article B (article namespace only; 40,018 pages link to themselves). Counts are those of ECHO's copy of the KONECT archive; KONECT's current release lists 13,593,032 articles and 437,217,424 links, including articles without links. One of eight language editions on ECHO (English, German, French, Italian, Japanese, Polish, Portuguese, Russian); at this size the analytics are computed on disk (Kuzu), with assortativity and bridges sampled. Useful for knowledge-graph and hyperlink-structure analysis, link prediction, community detection and comparison across language editions.
A Friendster (social network) dataset of 5,689,498 users and 14,067,887 friendship edges, collected by Booher via Friendster crawl (Nov 2010). Each record contains user-user friendship edges. classic social network dataset with 14M edges, representing one of the early major social networking platforms. Suitable for social network analysis, community detection, and friendship prediction.
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 Pokec dataset of 1,632,803 users, 22,301,964 directed relationships, collected by Takac and Zabovsky via Pokec platform (2012). Each record contains directed edges between Pokec users representing user-to-user relationships in the Slovak social network. Pokec social network, the most popular social network in Slovakia, capturing user relationships in a regional online community. Suitable for social network analysis, community detection, graph mining, regional social network studies, link prediction.
A Google+ dataset of 211,187 users, 1,506,896 circle memberships, collected by Fire et al. via Google+ API (2013). Each record contains directed edges between Google+ users representing circle memberships (user → circle). Google+ social graph capturing directed circle relationships, where users add others to their circles, creating a directed social graph structure. Suitable for link prediction, social network analysis, community detection, circle-based social behavior analysis.
A Academia.edu dataset of 200,169 academics, 1,022,883 connections, collected by Fire et al. (2011) via Academia.edu platform. Each record contains undirected edges between academics, representing follows or connections between researchers on the platform. Academic social network capturing researcher connections on Academia.edu, a platform for sharing research papers and tracking scholarly impact. Suitable for link prediction, academic network analysis, scholarly collaboration studies, research impact analysis.
A Google+ (now defunct) dataset of 102,100 nodes and 13,548,655 directed edges across 132 ego networks with ground-truth circles, collected by McAuley and Leskovec (Stanford, 2012) from public Google+ profiles. Each record contains directed follow edges, ground-truth circle memberships (Google+ circles shared publicly), anonymized node feature vectors representing profile attributes. 133 Google+ ego networks with publicly shared ground-truth circles from users who voluntarily released their circle data, providing a uniquely clean community ground-truth from a directed social platform. Suitable for overlapping community detection, ego network analysis, directed social circle inference, link prediction.
A TheMarker Cafe dataset of 69,413 users and 1,644,849 undirected friendship links, collected by Fire et al. (2011) and distributed by Network Repository. TheMarker Cafe was an Israeli online community where most interaction was in Hebrew. Suitable for link prediction, social network analysis, community detection and regional online community studies.
A Brightkite (location-based social network) dataset of 58,228 users, 214,078 friendship edges, and 4.49M check-ins, collected by Cho et al. via Brightkite API (2008-2010). Each record contains undirected friendship edges, check-in records (timestamp, latitude, longitude, location_id). The dataset is notable for its location-based social network with rich spatiotemporal check-in data for mobility research. Intended for research into human mobility analysis, location-based social networks, friendship prediction, and urban computing.
A Anybeat dataset of 12,645 users, 49,132 connections, collected by Fire et al. (2012) via Anybeat platform. Each record contains undirected edges between Anybeat users representing social connections in the community platform. Anybeat social network capturing user connections in a public gathering place where people interact with others from around their neighborhood or across the world. Suitable for link prediction, social network analysis, community detection, online community behavior studies.
A Bitcoin OTC (peer-to-peer Bitcoin trading platform) dataset of 5,881 users and 35,592 directed weighted trust ratings (32,029 positive, 3,563 negative), collected by Kumar et al. via platform crawl, distributed by SNAP. Each record contains directed weighted signed edges between users: integer rating in [-10, +10] representing trust strength, plus binarized sign (+1/-1) for compatibility with signed network algorithms; Unix timestamps per rating. continuous integer trust weights rather than binary +1/-1 signs, enabling weighted signed network analysis and providing finer-grained trust signal than Epinions or Slashdot while operating in the high-stakes context of peer-to-peer Bitcoin trading. Suitable for weighted signed network analysis, edge weight prediction, trust propagation modeling, fraud detection, reputation system design, and signed graph embedding research.
Wikipedia
Friendster
Pokec
Google
Academia.edu
TheMarker
Brightkite