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 US Western States power grid infrastructure dataset of 4,941 nodes and 6,594 edges, collected by D.J. Watts & S.H. Strogatz. Each record contains directed: False, weighted: False, signed: False. Classic small-world network of the US western power grid — nodes are generators/transformers, edges are transmission lines.. Suitable for infrastructure network analysis, small-world networks, robustness analysis.
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 Wikispeedia (Wikipedia-based online navigation game) dataset of 4,586 Wikipedia article nodes, 119,767 hyperlinks, and 76,193 human navigation paths, collected by West & Leskovec via the Wikispeedia online game (2008–2012). Each record contains article hyperlink graph (source → target), navigation path sequences, path duration in seconds, path length in clicks, back-click count, and optional difficulty rating (1=easy to 5=brutal). Unique dataset combining a Wikipedia hyperlink graph with 76,193 human navigation paths from an online game where players navigate from a random start article to a target article using only hyperlinks — 67.4% of paths were successfully completed.. Suitable for semantic distance estimation, human wayfinding behavior, hyperlink graph analysis, information foraging, Wikipedia structure research.
A Facebook (Rochester38, September 2005) dataset of 4,563 users and 161,404 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (48% male, 52% female), graduation year, major (86 unique), dorm (38 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: 0.0758, major homophily: 0.0642.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Stack Exchange (moderators.stackexchange.com) dataset of 540 users, 1,030 answer-collaboration edges, 582 questions, 1,296 answers, collected by Stack Exchange, Inc. via the annual Stack Exchange Data Dump. Each record contains user nodes (reputation, badge counts, vote history), directed weighted edges (answerer→asker, weight=answer score, count=interactions, accepted=bool), post text, tag distribution. User collaboration network from moderators.stackexchange.com — directed weighted graph where edges represent knowledge-sharing relationships (A answered B's question), with edge weight reflecting answer quality. Enables prestige hierarchy, community detection, and expertise flow analysis.. Suitable for expertise network analysis, reputation systems, community detection, knowledge flow, PageRank-based authority ranking, Q&A platform dynamics..
Twitter conversations around the Germanwings plane crash in the French Alps (March 2015), from the PHEME rumour dataset (Zubiaga, Liakata, Procter, Kochkina and colleagues; the complete release for rumour detection and veracity classification, figshare 6392078): 469 threads, each a source tweet and its replies, of which 238 were judged rumours by journalists and 231 not. Every rumour also carries its veracity as later established: 94 true, 111 false and 33 unverified. 4,489 tweets in all, with full tweet JSON. ECHO builds the reply network (4,020 reply links, each reply pointing to the tweet it answers) and labels each tweet with its thread's rumour status and, for source tweets, the veracity. Useful for rumour detection, rumour verification and modelling how conversations unfold. Annotations CC BY 4.0; Twitter retains the rights to tweet content. The archive PHEME_veracity.tar.bz2 is gzip-compressed despite its name (the name is the authors' own, kept so the checksum matches figshare): extract it with `tar xzf`.
A Twitter dataset of 4,465 labeled Twitter accounts (991 bots, 3474 genuine), collected by Ashu273k — curated subset of Cresci et al. (2017). Each record contains user profile features (followers, friends, statuses, favourites, listed count), binary bot/genuine label, user bio text. Small, clean subset of the Cresci-2017 dataset curated for rapid prototyping and benchmarking of bot detection models, with pre-extracted user-level features and binary labels. Suitable for bot detection, social spambot classification, feature selection for account authenticity, rapid prototyping of detection algorithms.
A TextDetox 2024 shared task (Hindglish) dataset of 4,363 Hindglish posts (2,200 toxic, 2,163 non-toxic), collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic). TextDetox Hindglish provides 4,363 balanced binary toxicity annotations — part of a 15-language multilingual benchmark for cross-lingual toxicity detection research. Suitable for toxicity detection, multilingual content moderation, cross-lingual NLP, hate speech classification, text detoxification.
A Facebook (Rice31, September 2005) dataset of 4,087 users and 184,828 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (47% male, 53% female), graduation year, major (46 unique), dorm (9 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: 0.0301, major homophily: 0.0486.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (Howard90, September 2005) dataset of 4,047 users and 204,850 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (66% male, 34% female), graduation year, major (62 unique), dorm (29 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: -0.0922, major homophily: 0.0427.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (ego-networks) dataset of 4,039 nodes and 88,234 edges, collected by McAuley & Leskovec via Facebook app survey (2012). Each record contains user-user friendship edges and ego-network circles. classic ego-network dataset with ground-truth social circles. Suitable for social network analysis, community detection, and circle prediction.
A Twitter dataset of 4,021 tweets referencing 3,611 images by URL, collected by Alam et al. for the Hurricane Irma 2017 crisis. Each record contains tweet text, engagement metrics (retweets, favorites, replies, quotes), user metadata, media attachments, crisis code. The dataset is notable for its multimodal dataset from the Hurricane Irma 2017 crisis, collected from Twitter during the event with full Twitter API metadata. Intended for research into crisis informatics, multimodal learning, disaster response, image classification, tweet filtering, engagement analysis. This copy (the SocialED redistribution) holds the tweet objects only: the images are referenced by URL and the image files are not included, and neither are CrisisMMD's human annotations (informativeness, humanitarian category, damage severity).
A Twitter dataset of 3,995 tweets referencing 4,691 images by URL, collected by Alam et al. for the Hurricane Maria 2017 crisis. Each record contains tweet text, engagement metrics (retweets, favorites, replies, quotes), user metadata, media attachments, crisis code. The dataset is notable for its multimodal dataset from the Hurricane Maria 2017 crisis, collected from Twitter during the event with full Twitter API metadata. Intended for research into crisis informatics, multimodal learning, disaster response, image classification, tweet filtering, engagement analysis. This copy (the SocialED redistribution) holds the tweet objects only: the images are referenced by URL and the image files are not included, and neither are CrisisMMD's human annotations (informativeness, humanitarian category, damage severity).
A Twitter dataset of 3,992 tweets referencing 4,569 images by URL, collected by Alam et al. for the Hurricane Harvey 2017 crisis. Each record contains tweet text, engagement metrics (retweets, favorites, replies, quotes), user metadata, media attachments, crisis code. The dataset is notable for its multimodal dataset from the Hurricane Harvey 2017 crisis, collected from Twitter during the event with full Twitter API metadata. Intended for research into crisis informatics, multimodal learning, disaster response, image classification, tweet filtering, engagement analysis. This copy (the SocialED redistribution) holds the tweet objects only: the images are referenced by URL and the image files are not included, and neither are CrisisMMD's human annotations (informativeness, humanitarian category, damage severity).
A Twitter dataset of 3,933 tweets from cyclone_idai_2019, collected by Alam et al. for cyclone_idai_2019 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the cyclone_idai_2019 event. Suitable for crisis informatics, humanitarian response, text classification.
A Facebook (Brandeis99, September 2005) dataset of 3,898 users and 137,567 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (57% male, 43% female), graduation year, major (57 unique), dorm (11 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: 0.0194, major homophily: 0.042.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
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 Twitter (OffensEval 2020 — English) dataset of 3,887 English tweets (1,080 offensive, 2,807 non-offensive), collected by Zampieri et al. for SemEval-2020 Task 12. Each record contains tweet text, binary offensive label (OFF/NOT), split (train/test). OffensEval 2020 English — part of the most popular SemEval task of all time (528 teams), enabling multilingual offensive language research. Suitable for offensive language detection, multilingual NLP, cross-lingual transfer learning, content moderation benchmarking.
A Voat (Reddit alternative, 2013–2020) dataset of 3,366 submissions, 595 comments, 174 users, 218 collaboration edges, collected by Mekacher & Papasavva (ICWSM 2022) via full platform crawl. Each record contains user nodes (registration date, moderation status), directed weighted edges (commenter→submitter, weight=upvotes+1), submission titles and bodies, comment text, upvotes, downvotes, depth. Complete dataset for the Voat subverse v/Dreamworlds, covering its full lifetime on the platform (2013–2020). Includes all 3,366 submissions and 595 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.
A Facebook (Bucknell39, September 2005) dataset of 3,826 users and 158,864 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (54% male, 46% female), graduation year, major (74 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: 0.1168, major homophily: 0.0509.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Voat (Reddit alternative, 2013–2020) dataset of 1,516 submissions, 2,089 comments, 376 users, 439 collaboration edges, collected by Mekacher & Papasavva (ICWSM 2022) via full platform crawl. Each record contains user nodes (registration date, moderation status), directed weighted edges (commenter→submitter, weight=upvotes+1), submission titles and bodies, comment text, upvotes, downvotes, depth. Complete dataset for the Voat subverse v/Contact, covering its full lifetime on the platform (2013–2020). Includes all 1,516 submissions and 2,089 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.
A Bitcoin Alpha (peer-to-peer Bitcoin trading platform) dataset of 3,783 users and 24,186 directed weighted trust ratings (22,650 positive, 1,536 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.
A Stack Exchange (bioacoustics.stackexchange.com) dataset of 305 users, 798 answer-collaboration edges, 480 questions, 1,074 answers, collected by Stack Exchange, Inc. via the annual Stack Exchange Data Dump. Each record contains user nodes (reputation, badge counts, vote history), directed weighted edges (answerer→asker, weight=answer score, count=interactions, accepted=bool), post text, tag distribution. User collaboration network from bioacoustics.stackexchange.com — directed weighted graph where edges represent knowledge-sharing relationships (A answered B's question), with edge weight reflecting answer quality. Enables prestige hierarchy, community detection, and expertise flow analysis.. Suitable for expertise network analysis, reputation systems, community detection, knowledge flow, PageRank-based authority ranking, Q&A platform dynamics..
A Facebook (Mich67, September 2005) dataset of 3,748 users and 81,903 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (27% male, 73% female), graduation year, major (79 unique), dorm (28 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: 0.0576, major homophily: 0.075.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A MADOC (Voat, MensRights) dataset of 992 users and 1,628 reply edges from 3,735 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.
A LinkedIn dataset of 3,600 profiles: 1,800 legitimate, 600 fake and 1,200 generated by ChatGPT (600 from legitimate profiles' statistics, 600 from fake ones'), released by Ayoobi, Shahriar and Mukherjee (ACM Hypertext 2023). Each record holds the profile sections visible before connecting: intro, about, experience, education, skills, languages, interests, licences and more, with counts per section. Suitable for fake and LLM-generated profile detection.
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 Voat (Reddit alternative, 2013–2020) dataset of 3,465 submissions, 117 comments, 73 users, 66 collaboration edges, collected by Mekacher & Papasavva (ICWSM 2022) via full platform crawl. Each record contains user nodes (registration date, moderation status), directed weighted edges (commenter→submitter, weight=upvotes+1), submission titles and bodies, comment text, upvotes, downvotes, depth. Complete dataset for the Voat subverse v/newsandpolitics, covering its full lifetime on the platform (2013–2020). Includes all 3,465 submissions and 117 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.
A Facebook (Santa74, September 2005) dataset of 3,578 users and 151,747 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (56% male, 44% female), graduation year, major (44 unique), dorm (72 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: 0.0456.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A Facebook (Colgate88, September 2005) dataset of 3,482 users and 155,043 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (53% male, 47% female), graduation year, major (50 unique), dorm (37 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: 0.09, major homophily: 0.0559.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A HOT Speech (hate/offensive/toxic speech dataset) dataset of 3,481 social media comments with multi-dimensional annotations, collected by SOMAR / ICPSR via Twitter, YouTube, and Reddit APIs (August 2021). Each record contains comment text, hard and soft labels (hateful, offensive, toxic), composite scores, and 21 researcher codes. multi-platform dataset with rich annotations including both MTurk worker labels and researcher codes. Suitable for hate speech detection, offensive language identification, toxicity classification, and political discourse analysis.
A Facebook (Pepperdine86, September 2005) dataset of 3,445 users and 152,007 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (58% male, 42% female), graduation year, major (84 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: 0.0593, major homophily: 0.0343.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
A OpenFlights.org airport route database dataset of 3,425 nodes and 37,595 edges, collected by OpenFlights.org. Each record contains directed: True, weighted: True. Directed network of airports connected by flight routes — nodes are airports, edges are direct routes.. Suitable for transportation network analysis, network robustness, hub detection.
A #petpeeve (annoying behaviors) dataset of 3,375 tweets labeled with annoying behavior categories, collected by Wang and Yang via Twitter API (2015). Each record contains tweet text and annoying behavior category label. The dataset is notable for its dataset for automatic categorization of annoying behaviors using lexical and frame-semantic embeddings. Intended for research into social media analysis, text classification, and behavioral categorization.
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.
Meta's Social Connectedness Index (SCI): the relative probability that two Facebook users in two places are friends, scaled so that the most connected pair is 1,000,000,000. This package is the release distributed on HDX, at several resolutions: country to country, GADM level 1 and 2 regions, geoBoundaries ADM1 and ADM2, EU NUTS 1 to 3 (2024), US counties and US ZIP code tabulation areas, with region-to-country lookups and the methodology paper. Suitable for research on social ties, migration, trade and economic spillovers between regions.
A Human protein interaction network (Vidal lab) dataset of 3,133 nodes and 6,726 edges, collected by M. Vidal et al.. Each record contains directed: False, weighted: False. Human protein-protein interaction network from the Vidal lab — classic biological network benchmark.. Suitable for biological network analysis, protein interaction research.
A Facebook (Middlebury45, September 2005) dataset of 3,075 users and 124,610 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (53% male, 47% female), graduation year, major (42 unique), dorm (10 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: 0.0395, major homophily: 0.046.. 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 MADOC (Voat, CringeAnarchy) dataset of 876 users and 1,740 reply edges from 3,030 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.
A Facebook (Smith60, September 2005) dataset of 2,970 users and 97,133 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (99% male, 1% female), graduation year, major (48 unique), dorm (39 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: 0.0252, major homophily: 0.0516.. 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 (Oberlin44, September 2005) dataset of 2,920 users and 89,912 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (56% male, 44% female), graduation year, major (69 unique), dorm (25 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: 0.0203, major homophily: 0.0939.. 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 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 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 (Trinity100, September 2005) dataset of 2,613 users and 111,996 friendship edges, collected by Traud, Mucha & Porter via Facebook network snapshots. Each record contains node attributes: gender (52% male, 48% female), graduation year, major (52 unique), dorm (25 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: 0.052, major homophily: 0.0707.. Suitable for community detection with node attributes, homophily analysis, demographic network structure, university social dynamics.
An adolescent friendship network from the Add Health study (2,539 students, 12,969 edges), compiled by James Moody. Each record contains directed edges: True, weighted: True, signed: False. This directed network was created from a survey that took place in 1994/1995. Each student was asked to list his 5 best female and his 5 male friends. A node represents a student and an edge between two students shows that the left student chose the right student as a friend. Higher edge weights ind. Suitable for social network analysis, community detection.
A 4chan, Twitter, and Weibo (cross-platform) dataset of 2,455 multimodal posts (1,318 hate, 1,137 non-hate), collected by Mira AI Lab (2024). Each record contains image filename, image OCR text, post text, hate/non-hate binary label, hate category (gender/race/religion/politics/violence/health/etc), and human-annotated reason for classification. Multimodal cross-platform collection hate speech dataset combining image OCR text and post text with fine-grained category labels across 8 hate dimensions — 54% of posts are hate speech with human-annotated reasoning. Suitable for multimodal hate speech detection, cross-platform analysis, hate category classification, image-text hate speech, content moderation research. The package includes the 2,455 meme images (img/) that the records name.
Twitter (X)
Wikipedia
Facebook
Stack Exchange
Voat
LinkedIn
Reddit
YouTube
4chan
Weibo