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Two fake news datasets covering seven different news domains.
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.
LIAR is a publicly available dataset for fake news detection. A decade-long of 12.8K manually labeled short statements were collected in various contexts from POLITIFACT.COM, which provides detailed analysis report and links to source documents for each case.
Fakeddit is a novel multimodal dataset for fake news detection 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.
Fakeddit is a novel multimodal dataset for fake news detection 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.
Fake News Corpus. This is an open source dataset composed of millions of news articles mostly scraped from a curated list of 1001 domains from http://www.opensources.co/.
Nov 5, 2021 · We surveyed 118 datasets related to fake news research on a large scale from three perspectives: (1) fake news detection, (2) fact verification, and (3) other tasks; for example, the analysis of fake news and satire detection.
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:
The "Fake and Real News Dataset" comprises two distinct collections of news articles: one containing 23,502 articles labeled as fake news and the other containing 21,417 articles labeled as true news.
This project aims to create the largest ground truth fake news analysis dataset for real and fake news content in relation to social media posts. Below illustrates the major contributions of the TruthSeeker dataset to the current fake news dataset landscape: One of the most extensive benchmark datasets with more than 180,000 labelled Tweets.
