COVID-TAD

COVID-TAD是一个大规模的COVID-19错误信息数据集，覆盖了25个月的时间跨度。该数据集是首个包含多个数据流快照的大型错误信息数据集，规模远超相关数据集。数据集内容包括从社交媒体收集的大量与COVID-19相关的帖子，通过频繁更新关键词过滤器来确保数据的时效性和相关性。创建过程中，数据集采用了时间感知的方法，通过固定窗口和自适应窗口的划分，确保数据的时间敏感性。该数据集主要应用于检测和分析COVID-19相关的错误信息，旨在解决随着疫情发展而不断出现的新型错误信息问题。

COVID-TAD is a large-scale COVID-19 misinformation dataset spanning a 25-month timeframe. It is the first large-scale misinformation dataset encompassing multiple data stream snapshots, with a scale significantly exceeding that of existing relevant datasets. The dataset contains a large volume of COVID-19-related posts collected from social media, where frequently updated keyword filters were implemented to ensure data timeliness and relevance. During its development, a time-aware methodology was adopted, utilizing fixed-window and adaptive-window partitioning to guarantee the temporal sensitivity of the dataset. This dataset is primarily applied to the detection and analysis of COVID-19-related misinformation, aiming to address the continuously emerging novel misinformation issues alongside the progression of the COVID-19 pandemic.