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A dataset of fake news articles from various sources and languages, labeled by human annotators. The dataset is available for download and can be used for training and testing machine learning models for fake news detection.
LIAR is a publicly available dataset for fake news detection with 12.8K manually labeled short statements from POLITIFACT.COM. It can be used for fact-checking research and has various benchmarks, papers, and code related to this task.
Browse 25 datasets for fake news detection from various sources and contexts, such as POLITIFACT, Common Crawl, Weibo, and COVID-19. Compare papers, benchmarks, and metrics for each dataset.
Feb 24, 2022 · 📖 A curated list of resources dedicated to Fake News Detection. natural-language-processing fake-news fake-news-software fake-news-dataset. Updated on Feb 24, 2022. hritik5102 / Fake-news-classification-model. Star 34. Code. Issues. Pull requests. Discussions.
Fakeddit is a large-scale dataset of over 1 million samples from various categories of fake news, labeled with different classification schemes. It is introduced by Nakamura et al. in a paper and can be accessed through a web app.
Nov 10, 2019 · We present Fakeddit, a novel multimodal dataset consisting of over 1 million samples from multiple categories of fake news. After being processed through several stages of review, the samples are labeled according to 2-way, 3-way, and 6-way classification categories through distant supervision.
The aim of Fakeddit is to provide a fine-grained multimodal fake news detection dataset and advance efforts to combat the spread of misinformation in multiple modalities. As such, we require those using our dataset to adhere to these guidelines:
