A Facebook (USC35, September 2005) dataset of 17,444 users and 801,853 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (50% male, 50% female), graduation year, major (133 unique), dorm (130 unique), student/faculty status; undirected friendship edges. One of 100 university Facebook networks from Sept 2005, each with rich demographic node attributes enabling homophily and community structure analysis. Gender homophily: 0.0861, major homophily: 0.0797.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (USF51, September 2005) dataset of 13,377 users and 321,214 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (58% male, 42% female), graduation year, major (89 unique), dorm (79 unique), student/faculty status; undirected friendship edges. One of 100 university Facebook networks from Sept 2005, each with rich demographic node attributes enabling homophily and community structure analysis. Gender homophily: -0.0755, major homophily: 0.0286.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (USFCA72, September 2005) dataset of 2,682 users and 65,252 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (68% male, 32% female), graduation year, major (41 unique), dorm (22 unique), student/faculty status; undirected friendship edges. One of 100 university Facebook networks from Sept 2005, each with rich demographic node attributes enabling homophily and community structure analysis. Gender homophily: 0.024, major homophily: 0.067.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (UVA16, September 2005) dataset of 17,196 users and 789,321 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (54% male, 46% female), graduation year, major (98 unique), dorm (137 unique), student/faculty status; undirected friendship edges. One of 100 university Facebook networks from Sept 2005, each with rich demographic node attributes enabling homophily and community structure analysis. Gender homophily: 0.0967, major homophily: 0.0521.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (Vanderbilt48, September 2005) dataset of 8,069 users and 427,832 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (52% male, 48% female), graduation year, major (76 unique), dorm (66 unique), student/faculty status; undirected friendship edges. One of 100 university Facebook networks from Sept 2005, each with rich demographic node attributes enabling homophily and community structure analysis. Gender homophily: 0.1591, major homophily: 0.0515.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (Vassar85, September 2005) dataset of 3,068 users and 119,161 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (61% male, 39% female), graduation year, major (50 unique), dorm (13 unique), student/faculty status; undirected friendship edges. One of 100 university Facebook networks from Sept 2005, each with rich demographic node attributes enabling homophily and community structure analysis. Gender homophily: 0.002, major homophily: 0.0566.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (Vermont70, September 2005) dataset of 7,324 users and 191,221 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (59% male, 41% female), graduation year, major (95 unique), dorm (44 unique), student/faculty status; undirected friendship edges. One of 100 university Facebook networks from Sept 2005, each with rich demographic node attributes enabling homophily and community structure analysis. Gender homophily: 0.0037, major homophily: 0.0497.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (Villanova62, September 2005) dataset of 7,772 users and 314,989 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (53% male, 47% female), graduation year, major (83 unique), dorm (49 unique), student/faculty status; undirected friendship edges. One of 100 university Facebook networks from Sept 2005, each with rich demographic node attributes enabling homophily and community structure analysis. Gender homophily: 0.1007, major homophily: 0.0525.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (Virginia63, September 2005) dataset of 21,325 users and 698,178 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (44% male, 56% female), graduation year, major (72 unique), dorm (90 unique), student/faculty status; undirected friendship edges. One of 100 university Facebook networks from Sept 2005, each with rich demographic node attributes enabling homophily and community structure analysis. Gender homophily: 0.0671, major homophily: 0.052.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (Wake73, September 2005) dataset of 5,372 users and 279,191 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (51% male, 49% female), graduation year, major (53 unique), dorm (48 unique), student/faculty status; undirected friendship edges. One of 100 university Facebook networks from Sept 2005, each with rich demographic node attributes enabling homophily and community structure analysis. Gender homophily: 0.1309, major homophily: 0.0439.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (WashU32, September 2005) dataset of 7,755 users and 367,541 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (51% male, 49% female), graduation year, major (140 unique), dorm (52 unique), student/faculty status; undirected friendship edges. One of 100 university Facebook networks from Sept 2005, each with rich demographic node attributes enabling homophily and community structure analysis. Gender homophily: 0.0939, major homophily: 0.0395.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (Wellesley22, September 2005) dataset of 2,970 users and 94,899 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (99% male, 1% female), graduation year, major (63 unique), dorm (24 unique), student/faculty status; undirected friendship edges. One of 100 university Facebook networks from Sept 2005, each with rich demographic node attributes enabling homophily and community structure analysis. Gender homophily: 0.2461, major homophily: 0.0401.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (Wesleyan43, September 2005) dataset of 3,593 users and 138,035 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (53% male, 47% female), graduation year, major (47 unique), dorm (155 unique), student/faculty status; undirected friendship edges. One of 100 university Facebook networks from Sept 2005, each with rich demographic node attributes enabling homophily and community structure analysis. Gender homophily: 0.0353, major homophily: 0.0526.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (William77, September 2005) dataset of 6,472 users and 266,378 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (56% male, 44% female), graduation year, major (56 unique), dorm (70 unique), student/faculty status; undirected friendship edges. One of 100 university Facebook networks from Sept 2005, each with rich demographic node attributes enabling homophily and community structure analysis. Gender homophily: 0.1173, major homophily: 0.0417.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (Williams40, September 2005) dataset of 2,790 users and 112,986 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (52% male, 48% female), graduation year, major (49 unique), dorm (32 unique), student/faculty status; undirected friendship edges. One of 100 university Facebook networks from Sept 2005, each with rich demographic node attributes enabling homophily and community structure analysis. Gender homophily: 0.0706, major homophily: 0.0435.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (Wisconsin87, September 2005) dataset of 23,842 users and 835,952 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (55% male, 45% female), graduation year, major (265 unique), dorm (75 unique), student/faculty status; undirected friendship edges. One of 100 university Facebook networks from Sept 2005, each with rich demographic node attributes enabling homophily and community structure analysis. Gender homophily: 0.0467, major homophily: 0.0371.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (Yale4, September 2005) dataset of 8,578 users and 405,450 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (48% male, 52% female), graduation year, major (77 unique), dorm (21 unique), student/faculty status; undirected friendship edges. One of 100 university Facebook networks from Sept 2005, each with rich demographic node attributes enabling homophily and community structure analysis. Gender homophily: 0.0367, major homophily: 0.0521.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Fediverse (bookwyrm, federation graph) dataset of 151 nodes, 4,966 edges (62 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains undirected edges between instances that have ever communicated, with instances.csv providing node metadata. The dataset is notable for its communication backbone graph where nodes are instances and edges represent any past interaction (undirected), showing how servers in the Fediverse are connected at the infrastructure level. Intended for research into decentralized network topology analysis, infrastructure resilience, cross-instance communication patterns, and federation policy impact studies.
A Fediverse (friendica, federation graph) dataset of 594 nodes, 70,812 edges (59 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains undirected edges between instances that have ever communicated, with instances.csv providing node metadata. The dataset is notable for its communication backbone graph where nodes are instances and edges represent any past interaction (undirected), showing how servers in the Fediverse are connected at the infrastructure level. Intended for research into decentralized network topology analysis, infrastructure resilience, cross-instance communication patterns, and federation policy impact studies.
A Fediverse (lemmy, cross_instance graph) dataset of 557 nodes, 4,701 edges (24 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains undirected edges between instances that communicate across different software platforms. The dataset is notable for its undirected graph of communication between instances, specifically capturing how different servers interact across the broader Fediverse. Intended for research into cross-platform communication analysis, inter-server community detection, and federated network structure studies.
A Fediverse (lemmy, federation graph) dataset of 779 nodes, 166,096 edges (62 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains undirected edges between instances that have ever communicated, with instances.csv providing node metadata. The dataset is notable for its communication backbone graph where nodes are instances and edges represent any past interaction (undirected), showing how servers in the Fediverse are connected at the infrastructure level. Intended for research into decentralized network topology analysis, infrastructure resilience, cross-instance communication patterns, and federation policy impact studies.
A Fediverse (lemmy, federation_with_blocks graph) dataset of 779 nodes, 289,473 edges (62 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains directed edges with signs (+ for federation, - for blocks) between instances. The dataset is notable for its directed graph with both positive (federation) and negative (block) edges, showing communication relationships alongside active blocking between instances. Intended for research into defederation studies, conflict resolution, trust and distrust analysis in decentralized networks.
A Fediverse (lemmy, intra_instance graph) dataset of 557 nodes, 2,398 edges (24 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains directed edges representing internal interactions within a single instance. The dataset is notable for its directed sparse graph capturing internal, within-instance communication patterns that are not visible in cross-instance graphs. Intended for research into internal community structure, local user interaction patterns, and instance-level activity analysis.
A Fediverse (mastodon, active_user graph) dataset of 8,135 nodes, 647,823 edges (24 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains directed, weighted edges based on user follow activity across instances, aggregated over time. The dataset is notable for its influence-weighted graph where nodes are instances and directed edges represent user following behavior (weighted by count), showing which servers generate content consumed by users on other servers. Intended for research into information flow analysis, influence measurement, content source tracking, and cross-instance user attention studies.
A Fediverse (mastodon, federation graph) dataset of 8,953 nodes, 16,135,522 edges (24 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains undirected edges between instances that have ever communicated, with instances.csv providing node metadata. The dataset is notable for its communication backbone graph where nodes are instances and edges represent any past interaction (undirected), showing how servers in the Fediverse are connected at the infrastructure level. Intended for research into decentralized network topology analysis, infrastructure resilience, cross-instance communication patterns, and federation policy impact studies.
A Fediverse (misskey, active_user graph) dataset of 1,274 nodes, 19,491 edges (24 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains directed, weighted edges based on user follow activity across instances, aggregated over time. The dataset is notable for its influence-weighted graph where nodes are instances and directed edges represent user following behavior (weighted by count), showing which servers generate content consumed by users on other servers. Intended for research into information flow analysis, influence measurement, content source tracking, and cross-instance user attention studies.
A Fediverse (misskey, federation graph) dataset of 1,765 nodes, 360,281 edges (60 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains undirected edges between instances that have ever communicated, with instances.csv providing node metadata. The dataset is notable for its communication backbone graph where nodes are instances and edges represent any past interaction (undirected), showing how servers in the Fediverse are connected at the infrastructure level. Intended for research into decentralized network topology analysis, infrastructure resilience, cross-instance communication patterns, and federation policy impact studies.
A Fediverse (peertube, follow graph) dataset of 2,356 nodes, 88,587 edges (62 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains directed edges representing following relationships between Peertube instances. The dataset is notable for its directed graph showing follower relationships between instances, specifically for the Peertube platform's follow network. Intended for research into video content discovery, creator-audience relationships, and media sharing network analysis.
A Fediverse (pleroma, active_user graph) dataset of 821 nodes, 1,801 edges (24 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains directed, weighted edges based on user follow activity across instances, aggregated over time. The dataset is notable for its influence-weighted graph where nodes are instances and directed edges represent user following behavior (weighted by count), showing which servers generate content consumed by users on other servers. Intended for research into information flow analysis, influence measurement, content source tracking, and cross-instance user attention studies.
A Fediverse (pleroma, federation graph) dataset of 1,170 nodes, 185,908 edges (61 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains undirected edges between instances that have ever communicated, with instances.csv providing node metadata. The dataset is notable for its communication backbone graph where nodes are instances and edges represent any past interaction (undirected), showing how servers in the Fediverse are connected at the infrastructure level. Intended for research into decentralized network topology analysis, infrastructure resilience, cross-instance communication patterns, and federation policy impact studies.
A Flickr (photo-sharing) dataset of 80,513 users and 5,899,882 friendship edges, collected by Tang & Liu via Flickr crawl (2009). Each record contains user-user friendship edges, group memberships (195 groups), and user IDs. The dataset is notable for its classic photo-sharing social network with explicit group memberships, used as a benchmark for latent social dimensions. Intended for research into social network analysis, community detection, group membership prediction, and photo-sharing platform structure studies.
A Flixster (social movie network) dataset of 2,523,386 users and 7,918,801 friendship edges, collected by Javier Parra via Flixster crawl (December 2010). Each record contains user-user friendship edges and user IDs. The dataset is notable for its friendship network from Flixster, a social movie site where users shared ratings, discovered films, and found others with similar tastes. Intended for research into social network analysis, community detection, movie recommendation systems, and taste-based social network studies.
A Free On-line Dictionary of Computing (FOLDOC) dataset of 13,356 nodes and 120,238 edges, collected by Denis Howe. Each record contains directed: True, weighted: True. Directed network of computing terms linked by cross-references in the FOLDOC dictionary.. Suitable for knowledge network analysis, dictionary network structure, NLP.
A Florida Bay ecosystem (dry season) dataset of 128 nodes and 2,137 edges, collected by R.E. Ulanowicz et al.. Each record contains directed: True, weighted: True, signed: False. Directed weighted ecological food web of the Florida Bay in dry season — complement to the wet season network.. Suitable for ecological network analysis, seasonal network comparison, food web topology.
A Florida Bay ecosystem (wet season) dataset of 128 nodes and 2,106 edges, collected by R.E. Ulanowicz et al.. Each record contains directed: True, weighted: True, signed: False. Directed weighted ecological food web of the Florida Bay in wet season — edges represent biomass flow between species.. Suitable for ecological network analysis, food web topology, trophic structure.
A Twitter dataset of 6,184 tweets from Fortune 100 companies, collected by Kevin McElwee via Twitter API. Each record contains tweet text, corporation name, sector, timestamp, hashtags, racial justice label, BLM mention, Juneteenth mention, donation mention. A manually annotated dataset of tweets from Fortune 100 companies during the 2020 Black Lives Matter protests, capturing corporate responses to a major social movement. Suitable for corporate activism, social movement response, political communication, crisis communication, public relations, brand activism.
A Foursquare (location-based social network) dataset of 639,014 users and 3,214,986 friendship edges, collected by Fred Morstatter via Foursquare crawl (December 2010). Each record contains user-user friendship edges and user IDs. The dataset is notable for its friendship network from Foursquare, a pioneering location-based social network where users checked in at venues and shared locations with friends. Intended for research into social network analysis, community detection, location-based social network studies, and geographic mobility research.
A Foursquare dataset of 22,809,624 check-ins, 114,324 users, 3,820,891 venues, collected by Yang et al. via Foursquare API (2012–2014). Each record contains check-in timestamps, venue IDs, GPS coordinates, venue categories, friendship edges. One of the largest public Foursquare datasets with both check-in histories and social networks. Suitable for location-based social network analysis, user mobility, POI recommendation, community detection.
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 Gab (alt-right social network) dataset of 22,112,812 Gab posts from January 2018 (13,871,421 original posts, 8,241,391 reposts), collected by Zannettou et al. via Gab API (2018). Each record contains post body text, username, verified flag, published_at, post type (post/repost), topic category, language, likes/reposts/replies counts, sentiment score, isPopular. 22,112,812 Gab posts from January 2018 — one of the earliest large-scale Gab datasets, capturing the platform during its growth phase as an alt-right Twitter alternative. Suitable for alt-right discourse analysis, fringe platform research, meme propagation, hate speech detection, cross-platform information flow, deplatforming research.
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 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 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.
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 WebKB cornell dataset of 195 web pages, 286 hyperlinks, collected by Yang et al. (ICML 2016). Each record contains web page features, hyperlink edges, class labels. WebKB cornell university web page classification dataset. Suitable for node classification, web page categorization, graph neural networks.
A WebKB texas dataset of 187 web pages, 298 hyperlinks, collected by Yang et al. (ICML 2016). Each record contains web page features, hyperlink edges, class labels. WebKB texas university web page classification dataset. Suitable for node classification, web page categorization, graph neural networks.
A WebKB washington dataset of 230 web pages, 417 hyperlinks, collected by Yang et al. (ICML 2016). Each record contains web page features, hyperlink edges, class labels. WebKB washington university web page classification dataset. Suitable for node classification, web page categorization, graph neural networks.
A WebKB wisconsin dataset of 265 web pages, 479 hyperlinks, collected by Yang et al. (ICML 2016). Each record contains web page features, hyperlink edges, class labels. WebKB wisconsin university web page classification dataset. Suitable for node classification, web page categorization, graph neural networks.
A Facebook (social media platform) dataset of 134,833 Facebook pages and 1,379,403 undirected mutual-like edges across 8 page categories (company, politician, tvshow, government, artist, new_sites, public_figure, athletes), collected by Rozemberczki et al. via Facebook Graph API, distributed via GEMSEC/SNAP. Each record contains undirected edges between Facebook pages representing mutual likes; pages categorized as company, politician, TV show, government, artist, news site, public figure, or athlete; node IDs namespaced by category. The dataset is notable for its multi-category Facebook page network with known ground-truth category labels per node, enabling direct evaluation of community detection and node classification algorithms across heterogeneous page types. Intended for research into community detection, node classification, graph embedding, cross-category network comparison, and social media page recommendation research.