Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set.
Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set.
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DOI：
10.2196/19273
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发表时间：
2020-05-29
影响因子：
8.5
通讯作者：
Ferrara, Emilio
中科院分区：
文献类型：
--
作者：
Chen, Emily;Lerman, Kristina;Ferrara, Emilio
背景技术背景：在撰写本文时，冠状病毒病（COVID-19）大流行疫情已经给全球许多国家的公民、资源和经济带来了巨大压力。社交距离措施、旅行禁令、自我约束和企业关闭正在改变世界各地社会的结构。随着人们被迫离开公共场所，关于这些现象的大部分对话现在都发生在Twitter等社交媒体平台上。目的：在本文中，我们描述了一个多语言的COVID-19 Twitter数据集，我们通过我们的COVID-19-TweetID GitHub存储库向研究社区提供。方法：我们于2020年1月28日开始进行这项持续的数据收集，利用Twitter的流媒体应用程序编程接口（API）和Twitter跟踪数据收集开始时流行的某些关键字和帐户。我们使用Twitter的搜索API来查询过去的推文，结果是我们收集的最早的推文可以追溯到2020年1月21日。结果：自我们的收集开始以来，我们每周都积极维护和更新我们的GitHub存储库。我们已经发布了超过1.23亿条推文，其中超过60%的推文是英文的。本文还提供了基本的统计数据，显示Twitter活动对COVID-19相关事件的反应和反应。结论：我们希望我们的贡献将能够在前所未有的规模和影响的全球流行病爆发的背景下研究在线对话动态。这一数据集还可以帮助追踪与COVID-19相关的错误信息和未经证实的谣言，或者使人们能够理解恐惧和恐慌--毫无疑问还有更多。
BACKGROUND: At the time of this writing, the coronavirus disease (COVID-19) pandemic outbreak has already put tremendous strain on many countries' citizens, resources, and economies around the world. Social distancing measures, travel bans, self-quarantines, and business closures are changing the very fabric of societies worldwide. With people forced out of public spaces, much of the conversation about these phenomena now occurs online on social media platforms like Twitter.OBJECTIVE: In this paper, we describe a multilingual COVID-19 Twitter data set that we are making available to the research community via our COVID-19-TweetIDs GitHub repository.METHODS: We started this ongoing data collection on January 28, 2020, leveraging Twitter's streaming application programming interface (API) and Tweepy to follow certain keywords and accounts that were trending at the time data collection began. We used Twitter's search API to query for past tweets, resulting in the earliest tweets in our collection dating back to January 21, 2020.RESULTS: Since the inception of our collection, we have actively maintained and updated our GitHub repository on a weekly basis. We have published over 123 million tweets, with over 60% of the tweets in English. This paper also presents basic statistics that show that Twitter activity responds and reacts to COVID-19-related events.CONCLUSIONS: It is our hope that our contribution will enable the study of online conversation dynamics in the context of a planetary-scale epidemic outbreak of unprecedented proportions and implications. This data set could also help track COVID-19-related misinformation and unverified rumors or enable the understanding of fear and panic-and undoubtedly more.