Cornell’s Computer Science department has published a multilingual coronavirus (COVID-19) Twitter dataset that they have been continuously collecting since January 22, 2020. We are making our dataset available to the research community. 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.
This dataset has been made available by arXiv, a a free distribution service and an open-access archive for 1,680,066 scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics
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