{"url":"/dataset/nela-gt-2018","name":"NELA-GT-2018","full_name":null,"description_markdown":"**NELA-GT-2018** is a dataset for the study of misinformation that consists of 713k articles collected between 02/2018-11/2018. These articles are collected directly from 194 news and media outlets including mainstream, hyper-partisan, and conspiracy sources. It includes ground truth ratings of the sources from 8 different assessment sites covering multiple dimensions of veracity, including reliability, bias, transparency, adherence to journalistic standards, and consumer trust.","description_withheld":null,"homepage":"https://doi.org/10.7910/DVN/ULHLCB","introduced_date":"2019-04-02","introduced_date_note":null,"introduced_by":{"paper":null,"title":"NELA-GT-2018: 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-2018"],"data_loaders":[],"num_papers_in_archive":9,"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."}