Geo-Tagged COVID-19 Twitter Dataset

本数据集由田纳西大学诺克斯维尔分校的Yunhe Feng和Wenjun Zhou创建，包含了从2020年1月25日至5月10日在美国收集的650,563条带有地理位置标签的COVID-19相关推文。数据集通过Twitter的Streaming API收集，涵盖了美国50个州和华盛顿特区。该数据集用于研究公众对COVID-19的反应，包括推文的地理分布、情感分析和主题建模等。数据集的创建旨在通过社交媒体数据分析，理解疫情期间公众的行为和情感变化，以及政策对公众反应的影响。

This dataset was developed by Yunhe Feng and Wenjun Zhou from the University of Tennessee, Knoxville. It comprises 650,563 geotagged COVID-19-related tweets collected across the United States between January 25 and May 10, 2020. The dataset was gathered using Twitter's Streaming API and covers all 50 U.S. states as well as Washington, D.C. It is designed to support research on public responses to COVID-19, including analyses of tweet geographic distribution, sentiment analysis, and topic modeling. The dataset was created to enable understanding of shifts in public behavior and emotions during the pandemic, as well as the influence of policies on public reactions, through social media data analytics.

搜集汇总

背景与挑战

背景概述

该数据集包含2020年1月25日至5月10日在美国收集的65万余条带有地理位置标签的COVID-19相关推文，覆盖美国所有州和华盛顿特区，用于分析疫情期间公众的地理分布、情感反应和主题变化，旨在通过社交媒体数据研究公众行为与政策影响。