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NELA-GT-2019: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articles
arXiv - CS - Computers and Society Pub Date : 2020-03-18 , DOI: arxiv-2003.08444
Maur\'icio Gruppi and Benjamin D. Horne and Sibel Adal{\i}

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

中文翻译:

NELA-GT-2019:用于研究新闻文章中的错误信息的大型多标签新闻数据集

在本文中,我们展示了 NELA-GT-2018 数据集(N{\o}rregaard、Horne 和 Adal{\i} 2019)的更新版本,名为 NELA-GT-2019。NELA-GT-2019 包含来自 2019 年 1 月 1 日至 2019 年 12 月 31 日期间收集的 260 个来源的 112 万篇新闻文章。与 NELA-GT-2018 一样,这些来源来自广泛的主流新闻来源和替代新闻来源。数据集包含来自 7 个不同评估站点的源级真实标签,涵盖多个维度的真实性。NELA-GT-2019 数据集可在以下位置找到:https://doi.org/10.7910/DVN/O7FWPO
更新日期:2020-03-30
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