{"url":"/dataset/nela-gt-2020","name":"NELA-GT-2020","full_name":null,"description_markdown":"**NELA-GT-2020** is an updated version of the [NELA-GT-2019](nela-gt-2019) dataset. NELA-GT-2020 contains nearly 1.8M news articles from 519 sources collected between January 1st, 2020 and December 31st, 2020. Just as with NELA-GT-2018 and NELA-GT-2019, these sources come from a wide range of mainstream news sources and alternative news sources. Included in the dataset are source-level ground truth labels from Media Bias/Fact Check (MBFC) covering multiple dimensions of veracity. Additionally, new in the 2020 dataset are the Tweets embedded in the collected news articles, adding an extra layer of information to the data.","description_withheld":null,"homepage":"https://github.com/MELALab/nela-gt","introduced_date":"2021-02-08","introduced_date_note":null,"introduced_by":{"paper":"/paper/nela-gt-2020-a-large-multi-labelled-news","title":"NELA-GT-2020: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articles","first_author":null,"url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Fake News Detection","url":"/task/fake-news-detection","datasets_with_task":"/datasets/task/fake-news-detection"},{"name":"Misinformation","url":"/task/misinformation","datasets_with_task":"/datasets/task/misinformation"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["NELA-GT-2020"],"data_loaders":[{"repo":"https://github.com/MELALab/nela-gt","url":"https://github.com/MELALab/nela-gt","frameworks":[]}],"num_papers_in_archive":4,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}