COVID-19 Fake News Dataset

COVID-19 Fake News Dataset是由印度理工学院德里分校的研究团队创建的一个包含10,700条真实和虚假COVID-19新闻的数据集。该数据集主要收集自社交媒体和事实核查网站，旨在通过机器学习方法识别和区分真实与虚假新闻。数据集中的真实新闻来自经过验证的Twitter账户，而虚假新闻则从多个事实核查网站收集。此数据集的创建是为了帮助研究人员开发自动检测虚假新闻的算法，特别是在COVID-19疫情期间，以应对信息泛滥的问题。

The COVID-19 Fake News Dataset is a dataset containing 10,700 real and fake COVID-19 news items, created by a research team from the Indian Institute of Technology Delhi. This dataset is primarily collected from social media platforms and fact-checking websites, with the goal of identifying and differentiating real and fake news via machine learning approaches. Real news entries in this dataset are sourced from verified Twitter accounts, whereas fake news is collected from multiple fact-checking websites. This dataset was developed to assist researchers in developing algorithms for automatic fake news detection, particularly during the COVID-19 pandemic to tackle the issue of information overload.

搜集汇总

背景与挑战

背景概述

COVID-19 Fake News Dataset是一个用于检测COVID-19相关假新闻的数据集，包含训练集、验证集和测试集，是AAAI21会议中CONSTRAINT workshop共享任务的一部分。数据集的相关资源包括论文、共享任务网站和Codalab竞赛页面。