NELA-GT-2018: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articles

Abstract

In this paper, we present a dataset of 713k articles collected between 02/2018-11/2018. These articles are collected directly from 194 news and media outlets including mainstream, hyper-partisan, and conspiracy sources. We incorporate ground truth ratings of the sources from 8 different assessment sites covering multiple dimensions of veracity, including reliability, bias, transparency, adherence to journalistic standards, and consumer trust. The NELA-GT-2018 dataset can be found at https://doi.org/10.7910/DVN/ULHLCB.

arXiv commentPublished at ICWSM 2019

References in corpus (4)

• Analysing How People Orient to and Spread Rumours in Social Media by Looking at Conversational Threads
• FakeNewsNet: A Data Repository with News Content, Social Context and Spatialtemporal Information for Studying Fake News on Social Media
• False Information on Web and Social Media: A Survey
• Some Like it Hoax: Automated Fake News Detection in Social Networks

Cited by in corpus (5)

• The Effects of Interactive AI Design on User Behavior: An Eye-tracking Study of Fact-checking COVID-19 Claims
• Do All Good Actors Look The Same? Exploring News Veracity Detection Across The U.S. and The U.K
• Self-Supervised Claim Identification for Automated Fact Checking
• PROVENANCE: An Intermediary-Free Solution for Digital Content Verification
• Characterizing the roles of bots during the COVID-19 infodemic on Twitter