数据链接：
官方服务：
资源简介：
Data for HKS Misinformation Review publication
应用场景：
创建时间：
2025-09-18
相关数据集
AMMEBA
AMMEBA数据集是由谷歌等机构创建的一个大规模的媒体基础错误信息调查数据集，专注于自然环境中的图像基础错误信息。该数据集包含135,838条经过事实检查的错误信息声明，主要关注图像在错误信息声明中的作用。数据集的创建旨在评估现实环境中错误信息缓解方法的有效性，并作为在线错误信息类型和模式的首次普查。AMMEBA数据集的应用领域包括错误信息研究、媒体分析和在线内容的真实性验证，旨在解决媒体错误信息
arXiv2024-05-21 更新120
Supplemental_Material – Supplemental material for Mapping Recent Development in Scholarship on Fake News and Misinformation, 2008 to 2017: Disciplinary Contribution, Topics, and Impact
Supplemental material, Supplemental_Material for Mapping Recent Development in Scholarship on Fake News and Misinformation, 2008 to 2017: Disciplinary Contribution, Topics, and Impact by Louisa Ha, Lo
Mendeley Data2024-06-27 更新100
Replication Data for: Right and left, partisanship predicts vulnerability to misinformation
The dataset consists of two files: 1. anonymized_shares.json: A collection of sharing actions, each corresponding to a tweet posted in June 2017 in which one or more URLs were shared. The format is as
DataONE2021-08-12 更新60
Source Credibility Effects in Misinformation Research: A Review and Primer - Supplementary Materials
The supplementary material for the paper titled "Source Credibility Effects in Misinformation Research: a Review and Primer" can be accessed here.
osf.io2024-10-04 更新110
Classifications of research articles published in Misinformation Review by theory (administrative or institution-level); methodology (con-tent analysis, media effects experiment, or surveys); and geography (Global North or Global South)
This file contains the list of all 31 peer-reviewed research articles published in Misinformation Review during 2020 (excluding the article types “commentary” and “research note”), along with their cl
DataONE2021-03-20 更新80
