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.
Posts from 329 thematically distinct 'general' thread collections on 4chan's /pol/ board, November 2013 to May 2019, released by Emilija Jokubauskaitė and Stijn Peeters (Zenodo 3603292). 13,756,579 posts in 58,687 threads, one CSV per general plus an index file. Each row holds the thread ID, post ID, timestamp, body text, subject, poster name, image file name and MD5, and the poster's country code and name. Suitable for studying recurring political discussion threads, propaganda, hate speech and online subcultures.
A Bluesky Social dataset of approximately 1.8 million public posts, collected by Alpin Dale from the AT Protocol firehose API in 2024. Each record contains post text, author handle, timestamp, image presence flag, and reply-to URI for constructing directed reply-thread networks. multilingual corpus from a decentralized AT Protocol platform with English dominant alongside Spanish, Portuguese, Japanese, and other languages. Suitable for decentralized social media analysis, reply network structure, and multilingual content modeling.
A Fakeddit (multimodal fake news benchmark) dataset of 965,647 Reddit submissions with text, images and metadata, collected by Nakamura et al. via the Reddit API (2020). Each record holds the post title, text, image URL, comment count, score, timestamp and 2-, 3- and 6-way veracity labels (6-way: true, satire/parody, misleading content, imposter content, false connection, manipulated content). Suitable for fake news detection, multimodal learning and misinformation classification.
A Meme Descriptions (Cheezburger dataset) dataset of 252,284 meme descriptions and 117 images, collected by Wang and Wen via Cheezburger (2015). Each record contains meme image and text descriptions, popularity scores. The dataset is notable for its multimodal dataset for meme popularity prediction and generation. Intended for research into multimodal learning, meme generation, popularity prediction, and computational humor.
A ReCOVery (news credibility repository) dataset of 2,029 news articles with reliability labels and social media engagement, collected by Zhou, Mulay, Ferrara, and Zafarani via news websites and Twitter (2020). Each record contains news article title and body, reliability label (1=reliable, 0=unreliable), publisher, political bias, country, author, and social media engagement data. The dataset is notable for its multimodal repository combining news content with social media engagement, designed for COVID-19 news credibility research. Intended for research into fake news detection, credibility assessment, political bias analysis, and multimodal misinformation research.
A Reddit (cross-subreddit post collection) dataset of 31,725 posts across 91 subreddits, collected by EL-Amrany via Reddit API. Each record contains post title, subreddit, upvotes, score, upvote ratio, comment count, comment sentiment, title sentiment, image URL/format/dimensions, virality label (binary), and temporal features (hour, day, weekday, month, year). Reddit-V contains 31,725 Reddit posts labeled for virality (12.7% viral), with pre-computed engagement signals and sentiment scores designed for virality prediction benchmarking. Suitable for virality prediction, engagement modeling, multimodal analysis, sentiment analysis, content popularity research, social media classification benchmarks.
A Instagram (user engagement patterns) dataset of 1,000 posts with engagement metrics and multimedia, collected by Hanmante via Instagram API (2024). Each record contains post captions, hashtags, images, videos, likes, comments, user metadata, and tagged users. The dataset is notable for its dataset of Instagram political content from Uruguay, with rich multimodal data. Intended for research into social media engagement analysis, political communication, multimodal NLP, and user behavior modeling.
A Weibo (CHECKED dataset) dataset of 2,104 microblogs with engagement and expert analysis, collected by Yang, Zhou, and Zafarani via Weibo (2020-2021). Each record contains microblog text, images, videos, engagement metrics (comments, reposts, likes), and expert analysis for fake news. The dataset is notable for its first Chinese COVID-19 fake news dataset with expert analysis, anonymized user IDs, and rich social interaction data. Intended for research into fake news detection, misinformation analysis, Chinese NLP, social network analysis, and public health communication.
A Cross-platform meme corpus (4chan, Twitter, Weibo) dataset of 1,318 hate-speech labeled meme records from 3 platforms, collected by Mira AI Lab via cross-platform meme collection. Each record contains image filename, OCR-extracted image text, post caption text, hate speech label, category list (politics/race/religion/etc.), and human-readable annotation reason per record. M3-Hate is the hate-speech filtered subset of the M3 meme dataset, with 1,318 hateful memes across 4chan (1062), Twitter (132), and Weibo (124) — multimodal with both image OCR text and post captions. Suitable for hate speech detection, multimodal meme analysis, cross-platform content moderation, image-text classification, harmful content research. The package includes the 1,318 meme images (img/) alongside the JSON records.
Telegram
4chan
Bluesky
Reddit
Twitter (X)
Instagram
Weibo