A LiveJournal (blogging social network) dataset of 12,404,868 emotion-labeled posts from 115,444 users with 106,577 nodes and 961,392 friendship/follower edges, collected by Jin & Zafarani via LiveJournal API, distributed by Data Lab SU. Each record contains user ID, emotion label (-1=negative/0=neutral/1=positive), timestamp, friendship edges, follower edges, community membership. 12,404,868 LiveJournal posts labeled with trichotomous emotion scores across 115,444 users — uniquely combines social network structure (friendship + follower graphs) with per-post emotion labels and community membership for studying emotion propagation in networks. Suitable for emotion propagation in social networks, community emotion analysis, sentiment diffusion, social influence on emotion, network-based mood modeling.
A MySpace dataset of 854,498 users, 6,489,736 directed follower edges, collected by Zhang and Tang via AMiner. Each record contains directed follower edges (source -> target means source follows target). Large-scale MySpace follower graph from AMiner, capturing social connections among 854K users. Suitable for social network analysis, community detection, influence propagation, graph embedding.
A Twitter (following network sample) dataset of 465,017 nodes and 834,797 edges, collected by Munmun De Choudhury et al. via Twitter API. Each record contains directed: True, weighted: False, signed: False, temporal: False. Large directed Twitter following network of 465k users and 835k edges, collected via API sampling. Unweighted directed graph suitable for large-scale social network analysis.. Suitable for Twitter network analysis, community detection, influence propagation.
A Twitter (hateful user network) dataset of 100,386 users (544 hateful, 4,427 normal, 0 suspended) with 2,286,592 follower edges, collected by Ribeiro et al. via Twitter API (2018). Each record contains user ID, hate label (hateful/normal/suspended), follower/followee/statuses counts, network centrality metrics, 200+ Empath emotional category scores, 300-dim GloVe embeddings, sentiment, subjectivity, tweet engagement statistics. One of the most feature-rich hateful user datasets, with 100,386 Twitter users labeled for hatefulness and supplemented with full network topology, Empath psychological features, and GloVe embeddings. Suitable for hate speech detection, hateful user classification, network-based toxicity analysis, suspended account detection, social influence of hate, graph-based hate propagation.
LiveJournal
Myspace
Twitter (X)