A Telegram (German-language conspiracy channels) dataset of 63,908,365 messages from 4,404 unique channels, collected by Hagen, Wiencierz, and Freudenthaler via Telegram API. Each record contains message UUID, channel name, author, reply structure, conspiracy label, language, media type (photo/video/voice), audio/video duration, forwarding metadata, duplicate flag. Schwurbelarchiv is a large-scale German Telegram corpus with 3.1% of messages labeled as conspiracy content, 23.8% reply edges enabling thread analysis, and rich media metadata across 4,404 channels. Suitable for conspiracy theory detection, German NLP, social network analysis, Telegram platform research, misinformation propagation, reply network analysis, media sharing patterns.
The wikilink network of the Russian Wikipedia, as distributed by KONECT (wikipedia_link_ru), built from the Wikimedia dumps: 2,853,118 articles and 82,056,101 directed links between them, where a link from A to B means article A links to article B (article namespace only; 20,493 pages link to themselves). Counts are those of ECHO's copy of the KONECT archive; KONECT's current release lists 3,370,462 articles and 93,373,056 links, including articles without links. One of eight language editions on ECHO (English, German, French, Italian, Japanese, Polish, Portuguese, Russian). Useful for knowledge-graph and hyperlink-structure analysis, link prediction, community detection and comparison across language editions.
A TextDetox 2024/2025 shared task (15 languages) dataset of 71,374 posts across 15 languages with binary toxicity labels, collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic), language. Combined multilingual toxicity benchmark covering 15 languages including low-resource languages (Amharic, Tatar, Hindglish) — 71,374 balanced samples total. Suitable for multilingual toxicity detection, cross-lingual transfer learning, low-resource NLP, content moderation benchmarking.
A Stack Exchange (russian.stackexchange.com) dataset of 3,171 users, 8,366 answer-collaboration edges, 4,705 questions, 11,992 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 russian.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 Twitch.tv (live streaming platform) dataset of 34,118 users and 214,556 undirected friendship edges across 6 language communities (DE, ENGB, ES, FR, PTBR, RU) merged into one cumulative graph, collected by Rozemberczki et al. via Twitch API, distributed via MUSAE/SNAP. Each record contains undirected friendship edges between Twitch streamers within each language community; node IDs namespaced by language to avoid collision across subgraphs. The dataset is notable for its multilingual streaming platform social network covering 6 distinct language communities, enabling cross-community structural comparison and multilingual graph embedding research. Intended for research into community detection, graph embedding, node classification, cross-platform social network analysis, and multilingual network comparison.
A TextDetox 2024 shared task (Russian) dataset of 5,000 Russian posts (2,500 toxic, 2,500 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 Russian provides 5,000 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 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.
Telegram
Wikipedia
Stack Exchange
Twitch
Twitter (X)