NELA-GT-2022: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articles
Maur\'icio Gruppi, Benjamin D. Horne, Sibel Adal{\i}
TL;DR
NELA-GT-2022 is a comprehensive, multi-label news dataset with over 1.7 million articles from 361 outlets, designed to facilitate research on misinformation and bias in news media.
Contribution
This paper introduces the fifth version of the NELA-GT dataset, expanding the dataset size and scope for studying misinformation in news articles.
Findings
Contains 1,778,361 articles from 361 outlets
Includes outlet-level veracity labels from Media Bias/Fact Check
Features embedded tweets within news articles
Abstract
In this paper, we present the fifth installment of the NELA-GT datasets, NELA-GT-2022. The dataset contains 1,778,361 articles from 361 outlets between January 1st, 2022 and December 31st, 2022. Just as in past releases of the dataset, NELA-GT-2022 includes outlet-level veracity labels from Media Bias/Fact Check and tweets embedded in collected news articles. The NELA-GT-2022 dataset can be found at: https://doi.org/10.7910/DVN/AMCV2H
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