--- license: apache-2.0 annotations_creators: - expert-generated language_creators: - found task_categories: - text-classification language: - en multilinguality: - monolingual source_datasets: - Opensources https://github.com/BigMcLargeHuge/opensources - FakeNews Corpus https://github.com/several27/FakeNewsCorpus tags: - fake-news-detection - fake news - english - nlp task_ids: - topic-classification - fact-checking pretty_name: Fake News Opensources size_categories: - 1M - **Homepage:** [https://github.com/AndyTheFactory/FakeNewsDataset](https://github.com/AndyTheFactory/FakeNewsDataset) - **Repository:** [https://github.com/AndyTheFactory/FakeNewsDataset](https://github.com/AndyTheFactory/FakeNewsDataset) - **Point of Contact:** [Andrei Paraschiv](https://github.com/AndyTheFactory) - ### Dataset Summary a consolidated and cleaned up version of the opensources Fake News dataset Fake News Corpus comprises 8,529,090 individual articles, classified into 12 classes: reliable, unreliable, political, bias, fake, conspiracy, rumor clickbait, junk science, satire, hate and unknown. The articles were scraped between the end of 2017 and the beginning of 2018 from various news websites, totaling 647 distinct sources, collecting articles dating from various years leading to the 2016 US elections and the year after. Documents were classified based on their source, based on the curated website list provided by opensources.co using a leading to a high imbalanced class distribution. Their proposed source classification method, was based on six criteria: - Title and Domain name analysis, - “About Us” analysis, - source or study mentioning, - writing style analysis, - aesthetic analysis and social media analysis. After extensive data cleaning and duplicate removal we retain **5,915,569** records ### Languages English ## Dataset Structure ### Data Instances An example record looks as follows. ``` { 'id': 4059480, 'type': 'political', 'domain': 'dailycaller.com', 'scraped_at': '2017-11-27', 'url': 'http://dailycaller.com/buzz/massachusettsunited-states/page/2/', 'authors': 'Jeff Winkler, Jonathan Strong, Ken Blackwell, Pat Mcmahon, Julia Mcclatchy, Admin, Matt Purple', 'title': 'The Daily Caller', 'content':'New Hampshire is the state with the highest median income in the nation, according to the U.S. Census Bureau’s report on income, poverty and health insurance', } ``` ### Data Fields - `id`: The unique article ID - `type`: the label of the record (one of: reliable, unreliable, political, bias, fake, conspiracy, rumor clickbait, junk science, satire, hate) - 'scraped_at': date of the original scrape run - 'url': original article url - 'authors': comma separated list of scraped authors - 'title': original scraped article title - `content`: full article text ### Data Splits Label | Nr Records :---| :---: reliable | 1807323 political | 968205 bias | 769874 fake | 762178 conspiracy | 494184 rumor | 375963 unknown | 230532 clickbait | 174176 unreliable | 104537 satire | 84735 junksci | 79099 hate | 64763 | total | 5915569 ## Dataset Creation ### Source Data News Articles from various sites #### Who are the source language producers? News Articles, Blogs ### Annotations #### Who are the annotators? Journalists ### Other Known Limitations The dataset was not manually filtered, therefore some of the labels might not be correct and some of the URLs might not point to the actual articles but other pages on the website. However, because the corpus is intended for use in training machine learning algorithms, those problems should not pose a practical issue. Additionally, when the dataset will be finalised (as for now only about 80% was cleaned and published), I do not intend to update it, therefore it might quickly become outdated for other purposes than content-based algorithms. However, any contributions are welcome! ### Licensing Information This data is available and distributed under Apache-2.0 license ### Citation Information ``` tbd ```