Fake news
The dataset contains two types of articles fake and real News. This dataset was collected from realworld sources; the truthful articles were obtained by crawling articles from Reuters.com (News website). As for the fake news articles, they were collected from different sources. The fake news articles were collected from unreliable websites that were flagged by Politifact (a fact-checking organization in the USA) and Wikipedia. The dataset contains different types of articles on different topics, however, the majority of articles focus on political and World news topics.
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COVIFN is a CoVID-19-specific dataset that consists of fact-checked fake news scraped from Poynter and true news from news publishers' verified portals. The dataset was pre-processed, the removal of special characters and non-vital information is performed.
The file contains columns such as:
Date: publish date of news article
country: country the article is about
text: the news article content
label: fake or real news label
URL: the fact-checked site
source: original news source site
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The CoVID19-FNIR dataset contains news stories related to CoVID-19 pandemic fact-checked by expert fact-checkers. CoVID19-FNIR is a CoVID-19-specific dataset consisting of fact-checked fake news scraped from Poynter and true news from the verified Twitter handles of news publishers. The data samples were collected from India, The United States of America, and European regions and consist of online posts from social media platforms between February 2020 to June 2020. The dataset went through prepossessing steps that include removing special characters and non-vital information.
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This database is provided for the Fake News Detection task. In addition to being used in other tasks of detecting fake news, it can be specifically used to detect fake news using the Natural Language Inference (NLI).
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This dataset provides a labeled fake news data, which can be used to have a deep study of fake news.
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