NELA-GT-2020：一个用于研究新闻文章中错误信息的大型多标签新闻数据集
NELA-GT-2020: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articles
摘要：
在本文中，我们提出了NELA-GT-2019数据集的更新版本，名为NELA-GT-2020。NELA-GT-2020包含2020年1月1日至2020年12月31日期间收集的来自519个来源的近180万篇新闻文章。与NELA-GT-2018和NELA-GT-2019一样，这些来源来自广泛的主流新闻来源和替代新闻来源。数据集中包括来自媒体偏差/事实检查（MBFC）的源代码级基础事实标签，涵盖准确性的多个维度。此外，2020年数据集中的新内容是嵌入在收集的新闻文章中的推文，为数据添加了额外的信息层。NELA-GT-2020数据集可以在https://doi.org/10.7910/DVN/CHMUYZ上找到。
英文摘要：
In this paper, we present an updated version of the NELA-GT-2019 dataset, entitled NELA-GT-2020. NELA-GT-2020 contains nearly 1.8M news articles from 519 sources collected between January 1st, 2020 and December 31st, 2020. Just as with NELA-GT-2018 and NELA-GT-2019, these sources come from a wide range of mainstream news sources and alternative news sources. Included in the dataset are source-level ground truth labels from Media Bias/Fact Check (MBFC) covering multiple dimensions of veracity. Additionally, new in the 2020 dataset are the Tweets embedded in the collected news articles, adding an extra layer of information to the data. The NELA-GT-2020 dataset can be found at https://doi.org/10.7910/DVN/CHMUYZ.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
