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NELA-GT-2019: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articles

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arxiv 2003.08444 v2 pith:AMWDXEDJ submitted 2020-03-18 cs.CY

Maurício Gruppi , Benjamin D. Horne , Sibel Adal{i} This is my paper · ORCID
classification cs.CY
keywords newsdatasetnela-gt-2019sourcesarticlesnela-gt-2018adalalternative
verification ladder T0 review T1 audit T2 compute T3 formal
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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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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. On the Effectiveness of Fact Checking Information from Politically Congruent and Incongruent Large Language Models

    cs.CY 2026-07 conditional novelty 6.0 of 10

    LLM fact-checkers shift trust in political headlines across partisan lines, with perceived chatbot politics mattering only for politically distant true headlines.

  2. The 2021 Tokyo Olympics Multilingual News Article Dataset

    cs.IR 2025-02 conditional novelty 6.0 of 10

    A new multilingual news benchmark, OG2021, contains 10,940 Olympic articles in nine languages grouped into 1,350 manually checked event clusters.

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