COVID-19 Twitter chatter dataset

本数据集名为'COVID-19 Twitter chatter dataset'，由佐治亚州立大学计算机科学系创建，包含超过8亿条与COVID-19相关的推文，数据收集自2020年1月1日至11月8日。数据集内容丰富，涵盖多种语言，旨在通过社交媒体分析疫情相关的情感和心理反应，识别错误信息来源，并实时监测公众对疫情的态度。创建过程中，研究团队利用Python和Tweepy包，通过Twitter Stream API收集数据，并定期更新。该数据集广泛应用于公共卫生、社会学和心理学等领域，有助于科学家们从全球视角理解疫情的社会动态。

This dataset, titled 'COVID-19 Twitter chatter dataset', was developed by the Department of Computer Science at Georgia State University. It encompasses over 800 million COVID-19-related tweets, collected between January 1 and November 8, 2020. Boasting rich, multilingual content, this dataset is designed to analyze pandemic-associated emotional and psychological reactions via social media, identify sources of misinformation, and monitor public attitudes toward the pandemic in real time. During the development of this dataset, the research team collected data through the Twitter Stream API using Python and the Tweepy library, and conducted regular updates. This dataset has been widely applied across fields including public health, sociology, and psychology, assisting scientists in understanding the social dynamics of the pandemic from a global perspective.