A Stack Exchange (askubuntu.com) dataset of 255,799 users, 434,011 answer-collaboration edges, 414,451 questions, 523,728 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 askubuntu.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 Stack Exchange (unix.stackexchange.com) dataset of 124,093 users, 280,381 answer-collaboration edges, 238,249 questions, 351,325 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 unix.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 StackExchange Ask Ubuntu (Linux/Ubuntu Q&A community) dataset of 137,517 users and 280,102 directed interaction edges, collected by Paranjape, Benson & Leskovec via SNAP (2017). Each record contains source user ID, target user ID, Unix timestamp of interaction. Temporal directed network of answer-to-question interactions on Ask Ubuntu — edges connect answering users to question-asking users with Unix timestamps, capturing the flow of technical knowledge.. Suitable for Q&A network analysis, temporal interaction patterns, community detection, knowledge flow in technical communities.
A Stack Exchange (elementaryos.stackexchange.com) dataset of 6,245 users, 7,967 answer-collaboration edges, 8,252 questions, 10,051 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 elementaryos.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 Linux kernel source code (function call graph) dataset of 30,837 nodes and 213,954 edges, collected by KONECT via static analysis of Linux kernel. Each record contains directed: True, weighted: False. Directed call graph of the Linux kernel — nodes are functions, edges are function calls.. Suitable for software network analysis, dependency network research, community detection.
A Voat (Reddit alternative, 2013–2020) dataset of 4,796 submissions, 18,175 comments, 4,559 users, 10,627 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/Linux, covering its full lifetime on the platform (2013–2020). Includes all 4,796 submissions and 18,175 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.