A YouTube (friendship network) dataset of 1,138,499 users and 2,990,443 friendship edges, collected by Tang & Liu via YouTube crawl (2009). Each record contains user-user friendship edges, group memberships (47 groups), and user IDs. The dataset is notable for its classic social network dataset with explicit group memberships, used as a benchmark for latent social dimensions and collective behavior learning. Intended for research into social network analysis, community detection, group membership prediction, and relational learning in social media.
A Twitter dataset of 1,600,000 tweets with binary sentiment labels (positive/negative) assigned via emoticon distant supervision, collected by Go, Bhayani and Huang at Stanford University via Twitter streaming API in 2009. Each record contains tweet text with polarity label (0=negative, 4=positive), tweet ID, timestamp, search query used for collection, and username. The dataset is notable for its one of the largest and most widely used Twitter sentiment benchmarks, notable for using emoticons as a noisy but scalable distant supervision signal rather than manual annotation, enabling 1.6M labeled examples. Intended for research into sentiment analysis, opinion mining, distant supervision research, text classification benchmarking, and social media language modeling.
A Web (news sites and blogs, Aug 2008–Apr 2009) dataset of 71,568 phrase clusters, 310,457 unique phrase nodes, 238,889 directed root→variant edges, 71,568 phrases in text corpus, collected by Leskovec et al. via web crawl of 1.5M articles/day, August 2008 to April 2009, distributed by SNAP. Each record contains phrase cluster graph where nodes are natural language phrases extracted from news articles and blogs; directed edges from root phrase to variant phrases within each cluster; edge weight = variant phrase frequency; covers the 2008 US election, financial crisis, and other major news events. The dataset is notable for its foundational information diffusion dataset capturing how phrases mutate and propagate across mainstream media and blogs; the cluster graph encodes phrase similarity and co-occurrence structure, enabling study of linguistic variation in news cycles. Intended for research into information diffusion modeling, meme propagation analysis, phrase clustering, linguistic variation in news media, temporal network analysis, and graph-based NLP research.
A BlogCatalog (v2) dataset of 97,884 bloggers and 1,668,698 friendship edges, collected by Agarwal et al. / Tang & Liu via BlogCatalog crawl. Each record contains blogger-blogger friendship edges, user IDs. The dataset is notable for its blogosphere friendship network from BlogCatalog, used for familiar stranger detection and latent social dimensions research. Intended for research into social network analysis, community detection, group membership prediction, and blogosphere structure studies.
A BlogCatalog (blogging social network) dataset of 88,784 bloggers and 2,093,195 friendship edges, collected by Agarwal et al. via BlogCatalog crawl (July 2009). Each record contains blogger-blogger friendship edges and user IDs. The dataset is notable for its classic blogosphere friendship network used for familiar stranger detection and social identity research. Intended for research into social network analysis, community detection, familiar stranger identification, and blogosphere structure 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 multi-dimensional YouTube network crawled in December 2008 at Arizona State University (Tang & Liu), from the ASU Social Computing Data Repository: 15,088 active users and five weighted, undirected interaction layers with 13,628,895 edges in all. The layers are contacts (76,765), shared friends (1,940,806), shared subscriptions (5,574,249), shared subscribers (2,239,440) and shared favourite videos (3,797,635); each pair is listed once. Suitable for multi-layer network analysis and community detection.
A BlogCatalog (v3) dataset of 10,312 bloggers and 333,983 friendship edges, collected by Agarwal et al. / Tang & Liu via BlogCatalog crawl. Each record contains blogger-blogger friendship edges, user IDs and group memberships. The dataset is notable for its blogosphere friendship network from BlogCatalog, used for familiar stranger detection and latent social dimensions research. Intended for research into social network analysis, community detection, group membership prediction, and blogosphere structure studies.
A Advogato dataset of 6,551 users, 51,317 trust relationships, collected by Massa et al. (2009) via Advogato platform. Each record contains directed, weighted trust edges between users, representing explicit trust relationships expressed by users. Advogato trust network where users express weighted trust relationships, enabling research on trust propagation and social influence in online communities. Suitable for trust network analysis, influence propagation, social influence studies, trust-based recommendation systems.
YouTube
Twitter (X)
BlogCatalog
Flickr
Advogato