Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set
arXiv(2020)
摘要
At the time of this writing, the novel coronavirus (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 conversation
about these phenomena now occurs online, e.g., on social media platforms like
Twitter. In this paper, we describe a multilingual coronavirus (COVID-19)
Twitter dataset that we have been continuously collecting since January 22,
2020. We are making our dataset available to the research community
(https://github.com/echen102/COVID-19-TweetIDs). 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 dataset could also help track scientific coronavirus
misinformation and unverified rumors, or enable the understanding of fear and
panic -- and undoubtedly more. Ultimately, this dataset may contribute towards
enabling informed solutions and prescribing targeted policy interventions to
fight this global crisis.
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