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 News Articles (multiple sources) dataset of 85,917 articles (43,610 fake, 34,941 true, 7,366 russian propaganda), collected by Steven Peutz via Kaggle (2022); Russian propaganda subset sourced from the EUvsDisinfo Project (2015-present). Each record contains full article text and veracity label (fake, true, or russian_propaganda). combination of general fake/true news articles with a dedicated Russian propaganda subset from the EUvsDisinfo database, enabling comparative analysis across disinformation types. Suitable for fake news detection, misinformation topic modeling, propaganda characterization, and classification benchmarking.
A ISOT (fake news dataset) dataset of 44,898 news articles labeled fake/real, collected by ISOT via Reuters and various sources (2017). Each record contains news article text (title + content) and binary label (is_fake: 1=fake, 0=real). The dataset is notable for its well-balanced dataset of fake and real news articles for misinformation research. Intended for research into fake news detection, text classification, and misinformation analysis.
A FakeNewsNet (fake news with social context) dataset of 23,196 news articles labeled fake/real with social media context, collected by Shu et al. via Politifact and GossipCop (2019). Each record contains news title, article text, binary label (0=real, 1=fake), source (politifact/gossipcop), publish date, and URL. The dataset is notable for its dataset with social context and spatiotemporal information for studying fake news propagation. Intended for research into fake news detection, social media analysis, misinformation propagation, and multimodal research.
A LIAR (fact-checking benchmark) dataset of 12,789 labeled claim statements from Politifact, collected by Wang via Politifact fact-checking (2017). Each record contains claim text, 6-class veracity label, speaker metadata (party, state, job title), credit history counts (barely_true/false/half_true/mostly_true/pants_fire), and context. The dataset is notable for its benchmark dataset for fake news detection with fine-grained 6-class labels, rich speaker metadata, and credit history. Intended for research into fake news detection, fact-checking, political discourse analysis, and misinformation research.
A News Articles (multiple sources) dataset of 9,900 news articles (5,000 fake, 4,900 real), collected by Vishakh Dapat via Kaggle (2023). Each record contains full article text and binary veracity label (Fake or Real). The dataset is notable for its balanced binary-labeled news corpus with approximately equal proportions of fake and real articles, making it well-suited as a classification benchmark. Intended for research into fake news detection, text classification benchmarking, misinformation topic modeling, and NLP feature engineering.
A HOT Speech (hate/offensive/toxic speech dataset) dataset of 3,481 social media comments with multi-dimensional annotations, collected by SOMAR / ICPSR via Twitter, YouTube, and Reddit APIs (August 2021). Each record contains comment text, hard and soft labels (hateful, offensive, toxic), composite scores, and 21 researcher codes. multi-platform dataset with rich annotations including both MTurk worker labels and researcher codes. Suitable for hate speech detection, offensive language identification, toxicity classification, and political discourse analysis.
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.
Reddit
Twitter (X)
YouTube
Weibo