Aguilar-Gallegos, Norman
Romero-García, Leticia Elizabeth
Martínez-González, Enrique Genaro
García-Sánchez, Edgar Iván
Aguilar-Ávila, Jorge
2020-09-15T20:29:21Z
2020-09-15T20:29:21Z
2020
2352-3409
https://doi.org/10.1016/j.dib.2020.105684
http://hdl.handle.net/20.500.12010/13290
In this data article, we provide a dataset of 8,982,694 Twitter posts around the coronavirus health global crisis. The
data were collected through the Twitter REST API search. We
used the rtweet R package to download raw data. The term
searched was “Coronavirus” which included the word itself
and its hashtag version. We collected the data over 23 days,
from January 21 to February 12, 2020. The dataset is multilingual, prevailing English, Spanish, and Portuguese. We include a new variable created from other four variables; it
is called “type” of tweets, which is useful for showing the
diversity of tweets and the dynamics of users on Twitter.
The dataset comprises seven databases which can be analysed separately. On the other hand, they can be crossed to
set other researches, among them, trends and relevance of
different topics, types of tweets, the embeddedness of users
and their profiles, the retweets dynamics, hashtag analysis, as
well as to perform social network analysis. This dataset can
attract the attention of researchers related to different fields on knowledge, such as data science, social science, network
science, health informatics, tourism, infodemiology, and others
14 páginas
application/pdf
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Data in Brief
reponame:Expeditio Repositorio Institucional UJTL
instname:Universidad de Bogotá Jorge Tadeo Lozano
COVID-19
Pandemic
Infodemiology
Social media
Twitter
Retweets
Social Network Analysis
Hashtags
Dataset on dynamics of coronavirus on twitter
Artículo
Síndrome respiratorio agudo grave
COVID-19
SARS-CoV-2
Coronavirus
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/acceptedVersion
Abierto (Texto Completo)
https://doi.org/10.1016/j.dib.2020.105684
http://purl.org/coar/resource_type/c_2df8fbb1