A GitHub (stargazers network) dataset of 1,448,038 nodes and 2,985,781 edges across 12,725 graphs, collected by Rozemberczki et al. via GitHub API (2019). Each record contains graph ID, binary label (0=web development, 1=machine learning), developer-user follower edges. The dataset is notable for its graph classification dataset with 12,725 small graphs, each representing the social network of developers who starred a repository. Intended for research into graph classification, social network analysis, developer behavior modeling, and transfer learning.
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.
A Deezer (Romania) dataset of 54,573 users, 498,202 friendships, collected by Rozemberczki et al. via Deezer music streaming service (November 2017). Each record contains undirected edges between Deezer users representing mutual friendships, with node attributes including genre preferences (84 distinct genres). Friendship network from Deezer music streaming service in Romania, with rich genre preference metadata enabling music-based community detection and user behavior analysis. Suitable for community detection, graph embedding, music preference analysis, social network analysis, recommendation systems.
A Facebook dataset of 50,515 pages, 819,306 mutual likes, collected by Rozemberczki et al. via the Facebook Graph API (November 2017). Each record contains undirected edges between blue verified Facebook artist pages that mutually liked each other, with node attributes including page name and raw Facebook ID. Graph of blue verified Facebook artist pages, where edges represent mutual likes between pages, capturing how users discover and engage with artist content. Suitable for community detection in social networks, graph embedding, artist influence analysis, fanbase overlap studies.
A Twitch.tv (live streaming platform) dataset of 34,118 users and 214,556 undirected friendship edges across 6 language communities (DE, ENGB, ES, FR, PTBR, RU) merged into one cumulative graph, collected by Rozemberczki et al. via Twitch API, distributed via MUSAE/SNAP. Each record contains undirected friendship edges between Twitch streamers within each language community; node IDs namespaced by language to avoid collision across subgraphs. The dataset is notable for its multilingual streaming platform social network covering 6 distinct language communities, enabling cross-community structural comparison and multilingual graph embedding research. Intended for research into community detection, graph embedding, node classification, cross-platform social network analysis, and multilingual network comparison.
A Facebook dataset of 27,917 pages, 206,259 mutual likes, collected by Rozemberczki et al. via the Facebook Graph API (November 2017). Each record contains undirected edges between blue verified Facebook media pages that mutually liked each other, with node attributes including page name and raw Facebook ID. Graph of blue verified Facebook media pages, where edges represent mutual likes between pages, capturing how users discover and engage with media and news content. Suitable for community detection in social networks, graph embedding, media influence analysis, news consumption studies, journalism and media network analysis.
A Facebook dataset of company page mutual-like edges from November 2017, collected by Rozemberczki et al. via the Facebook Graph API. Each record contains undirected edges between company pages that mutually liked each other, with node attributes including page name and category. undirected structure capturing symmetric inter-company endorsement relationships across multiple industries. Suitable for corporate social media behavior, community detection, and undirected social network analysis.
A Facebook dataset of 13,866 pages, 86,858 mutual likes, collected by Rozemberczki et al. via the Facebook Graph API (November 2017). Each record contains undirected edges between blue verified Facebook sport pages that mutually liked each other, with node attributes including page name and raw Facebook ID. Graph of blue verified Facebook sport pages, where edges represent mutual likes between pages, capturing how fans engage with sports teams, athletes, and sporting content. Suitable for community detection in social networks, graph embedding, sports fan engagement analysis, team rivalry studies, sports media and fandom network analysis.
A Facebook dataset of 11,565 pages, 67,114 mutual likes, collected by Rozemberczki et al. via the Facebook Graph API (November 2017). Each record contains undirected edges between blue verified Facebook public figure pages that mutually liked each other, with node attributes including page name and raw Facebook ID. Graph of blue verified Facebook public figure pages, where edges represent mutual likes between pages, capturing how audiences engage with celebrities, influencers, and notable personalities. Suitable for community detection in social networks, graph embedding, celebrity influence analysis, public figure engagement studies, social media personality network analysis.
A Facebook dataset of 7,057 pages, 89,455 mutual likes, collected by Rozemberczki et al. via the Facebook Graph API (November 2017). Each record contains undirected edges between blue verified Facebook government pages that mutually liked each other, with node attributes including page name and raw Facebook ID. Graph of blue verified Facebook government pages, where edges represent mutual likes between pages, capturing how citizens engage with government content and official institutions. Suitable for community detection in social networks, graph embedding, government-citizen engagement studies, political communication analysis.
A Facebook dataset of 5,908 pages, 41,729 mutual likes, collected by Rozemberczki et al. via the Facebook Graph API (November 2017). Each record contains undirected edges between blue verified Facebook politician pages that mutually liked each other, with node attributes including page name and raw Facebook ID. Graph of blue verified Facebook politician pages, where edges represent mutual likes between pages, capturing how citizens engage with political figures and campaign content. Suitable for community detection in social networks, graph embedding, political communication analysis, politician influence studies, political polarization research.
A Facebook dataset of 3,892 pages, 17,262 mutual likes, collected by Rozemberczki et al. via the Facebook Graph API (November 2017). Each record contains undirected edges between blue verified Facebook TV show pages that mutually liked each other, with node attributes including page name and raw Facebook ID. Graph of blue verified Facebook TV show pages, where edges represent mutual likes between pages, capturing how viewers engage with television content, shows, and entertainment media. Suitable for community detection in social networks, graph embedding, TV viewership analysis, entertainment content engagement studies, media consumption network analysis, fan community detection.
A Facebook dataset of 620 pages, 2,102 mutual likes, collected by Rozemberczki et al. via the Facebook Graph API (November 2017). Each record contains undirected edges between blue verified Facebook food pages that mutually liked each other, with node attributes including page name and raw Facebook ID. Graph of blue verified Facebook food pages, where edges represent mutual likes between pages, capturing how users discover and engage with culinary content. Suitable for community detection in social networks, graph embedding, food influence analysis, culinary content engagement studies.