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Data Descriptor

A Large-Scale COVID-19 Twitter Chatter Dataset for Open Scientific Research—An International Collaboration

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Department of Computer Science, Georgia State University, Atlanta, GA 30303, USA
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Missouri School of Journalism, University of Missouri, Columbia, MO 65201, USA
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Department of Social Psychology, Universitat Autònoma de Barcelona, 08035 Barcelona, Spain
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Department of Psychology, Carl von Ossietzky Universität Oldenburg, 26129 Oldenburg, Germany
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Language Technology Lab, Universität Duisburg-Essen, 47057 Duisburg, Germany
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Faculty of Computer Science, Higher School of Economics—National Research University, 101000 Moscow, Russia
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Faculty of Chemistry, Kazan Federal University, 420008 Kazan, Russia
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Department of Population Health Sciences, Georgia State University, Atlanta, GA 30303, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Nicola Luigi Bragazzi
Epidemiologia 2021, 2(3), 315-324; https://doi.org/10.3390/epidemiologia2030024
Received: 6 July 2021 / Revised: 28 July 2021 / Accepted: 29 July 2021 / Published: 5 August 2021
(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)
As the COVID-19 pandemic continues to spread worldwide, an unprecedented amount of open data is being generated for medical, genetics, and epidemiological research. The unparalleled rate at which many research groups around the world are releasing data and publications on the ongoing pandemic is allowing other scientists to learn from local experiences and data generated on the front lines of the COVID-19 pandemic. However, there is a need to integrate additional data sources that map and measure the role of social dynamics of such a unique worldwide event in biomedical, biological, and epidemiological analyses. For this purpose, we present a large-scale curated dataset of over 1.12 billion tweets, growing daily, related to COVID-19 chatter generated from 1 January 2020 to 27 June 2021 at the time of writing. This data source provides a freely available additional data source for researchers worldwide to conduct a wide and diverse number of research projects, such as epidemiological analyses, emotional and mental responses to social distancing measures, the identification of sources of misinformation, stratified measurement of sentiment towards the pandemic in near real time, among many others. View Full-Text
Keywords: public datasets; open science; COVID-19; social media; data sources public datasets; open science; COVID-19; social media; data sources
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MDPI and ACS Style

Banda, J.M.; Tekumalla, R.; Wang, G.; Yu, J.; Liu, T.; Ding, Y.; Artemova, E.; Tutubalina, E.; Chowell, G. A Large-Scale COVID-19 Twitter Chatter Dataset for Open Scientific Research—An International Collaboration. Epidemiologia 2021, 2, 315-324. https://doi.org/10.3390/epidemiologia2030024

AMA Style

Banda JM, Tekumalla R, Wang G, Yu J, Liu T, Ding Y, Artemova E, Tutubalina E, Chowell G. A Large-Scale COVID-19 Twitter Chatter Dataset for Open Scientific Research—An International Collaboration. Epidemiologia. 2021; 2(3):315-324. https://doi.org/10.3390/epidemiologia2030024

Chicago/Turabian Style

Banda, Juan M., Ramya Tekumalla, Guanyu Wang, Jingyuan Yu, Tuo Liu, Yuning Ding, Ekaterina Artemova, Elena Tutubalina, and Gerardo Chowell. 2021. "A Large-Scale COVID-19 Twitter Chatter Dataset for Open Scientific Research—An International Collaboration" Epidemiologia 2, no. 3: 315-324. https://doi.org/10.3390/epidemiologia2030024

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