LiveJournal is a blogging and social networking service launched in 1999. Users keep journals, join communities and list friends; it was popular in the 2000s, especially in Russia, and its friendship network is a classic benchmark graph. Website ↗
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 LiveJournal (blogging and social network platform) dataset of 4,846,609 nodes and 68,475,391 edges, collected by J. Leskovec et al. via LiveJournal API. Each record contains directed: True, weighted: False, temporal: False. Large directed LiveJournal friendship network with 4.3M users and 69M edges — one of the largest social network datasets from the Web 2.0 era.. Suitable for large-scale social network analysis, community detection, information diffusion.
A LiveJournal social network of 106,577 users and 961,392 directed edges (793,948 follower links and 246,164 friendship links), from a crawl of the users within three hops of the seed user krazykitkat, pre-processed for the paper 'Emotions in Social Networks: Distributions, Patterns, and Models' (Jin and Zafarani): only users with 10 or more posts carrying a predefined LiveJournal mood were kept, and user ids are anonymized. This copy holds the two network files (Friendship.txt, Followers.txt) and the release README; the per-post mood file (Posts.txt) and community memberships (Community.txt) that the README describes are not included. Suitable for social network structure, follower and friendship analysis, community detection, social influence modeling.
