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 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 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 FakeNewsNet (fake news with social context) dataset of 23,196 news articles labeled fake/real with social media context, collected by Shu et al. via Politifact and GossipCop (2019). Each record contains news title, article text, binary label (0=real, 1=fake), source (politifact/gossipcop), publish date, and URL. The dataset is notable for its dataset with social context and spatiotemporal information for studying fake news propagation. Intended for research into fake news detection, social media analysis, misinformation propagation, and multimodal research.
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 MOOC online learning platform dataset of 7,047 students, 97 course content items, and 411,749 student actions, collected by Kumar, Zhang & Leskovec via SNAP (2019). Each record contains action ID, student user ID, course content item ID, relative timestamp, dropout label (0/1), and 4 pre-computed action feature dimensions. Bipartite temporal network of student interactions with MOOC course content — 1.0% dropout rate across 396,633 actions. Includes pre-computed embedding features per action, enabling direct use in temporal graph learning without feature engineering.. Suitable for student dropout prediction, temporal interaction networks, dynamic graph embedding, online learning behavior analysis.
A Reddit (state-sponsored troll comments) dataset of 7,097 Reddit comments from verified Russian state-sponsored troll accounts, collected by Zannettou et al. via Reddit API (2019). Each record contains comment body, subreddit, author, score, controversiality, created_utc, gilded, parent_id. 7,097 Reddit comments from verified Russian IRA troll accounts across 649 subreddits — enabling study of coordinated influence operations on Reddit. Suitable for information operations detection, coordinated inauthentic behavior, Reddit manipulation analysis, troll comment classification, cross-platform influence campaign research.
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 Twitter dataset of 4,952 tweets (1,238 rumour, 3,714 non-rumour) from the 2013 Boston Marathon bombings, collected by Zubiaga, Liakata, and Procter — Augmented PHEME (Zenodo, 2019). Each record contains tweet text, binary rumour/non-rumour label, timestamp, reaction thread structure linking source tweets to replies. Augmented extension of PHEME covering the Boston Marathon bombings event with both rumour threads and non-rumour threads, providing a balanced benchmark for rumour detection with reaction graph structure. Suitable for rumour detection, misinformation classification, crisis communication analysis, stance detection, conversational thread modelling.
A Twitter (state-sponsored IO accounts) dataset of 3,836 Russian IRA and 770 Iranian state-sponsored troll accounts with profile metadata, collected by Zannettou et al. via Twitter API (2019). Each record contains hashed user ID, display name, screen name, reported location, profile description, follower/following counts, account creation date, account language. Hashed and anonymized profiles of 4,606 verified state-sponsored troll accounts from Russian IRA and Iranian IO campaigns, enabling detection and characterization of coordinated inauthentic behavior. Suitable for information operations detection, state-sponsored troll identification, coordinated inauthentic behavior, influence campaign analysis, social media manipulation 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.
Foursquare
Facebook
Deezer
Reddit
Twitter (X)