Papers › NELA-GT-2019: A Large Multi-Labelled News Dataset for The Study of Misinformation in...
NELA-GT-2019: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articles
Maurício Gruppi, Benjamin D. Horne, Sibel Adalı
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In this paper, we present an updated version of the NELA-GT-2018 dataset (N{\o}rregaard, Horne, and Adal{\i} 2019), entitled NELA-GT-2019. NELA-GT-2019 contains 1.12M news articles from 260 sources collected between January 1st 2019 and December 31st 2019. Just as with NELA-GT-2018, these sources come from a wide range of mainstream news sources and alternative news sources. Included with the dataset are source-level ground truth labels from 7 different assessment sites covering multiple dimensions of veracity. The NELA-GT-2019 dataset can be found at: https://doi.org/10.7910/DVN/O7FWPO
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