Materia: Enginyeria
Derechos de acceso: info:eu-repo/semantics/openAccess
Identificador del investigador: 0000-0001-5560-7094
Publicado por (editorial): Universitat Rovira i Virgili (URV)
Publicaciones relacionadas: Castioni, P., Andrighetto, G., Gallotti, R., Polizzi, E., & De Domenico, M. (2022). The voice of few, the opinions of many: Evidence of social biases in Twitter COVID-19 fake news sharing. Royal Society Open Science, 9(10), 220716. https://doi.org/10.1098/rsos.220716
Resumen: The datasets that we used in this work come from the COVID-19 Infodemics Observatory (https://covid19obs.fbk.eu/#/ (opens in new window)). Tweets associated with the COVID-19 pandemics (coronavirus, ncov, #Wuhan, covid19, COVID-19, SARSCoV2, COVID) have been automatically collected using the Twitter Filter API. It contains 7.7 million retweets in the case of USA, 300 thousand in the case of Italy and 900 thousand in the case of the UK. The time of the collection goes from the 22nd of January to the 22nd of May for the USA, while for Italy and the UK it goes from the 22nd of January to the 2nd of December. For each tweet we specified the ID code as well as the time at which it was created. In this dataset one can also find the tables necessary to reproduce exactly the figures in the paper.
Departamento: Enginyeria Informàtica i Matemàtiques
DOI: 10.5061/dryad.bzkh189cc
Tipo de documento: info:eu-repo/semantics/other
DOI de la publicación relacionada: 10.1098/rsos.220716
Fecha alta repositorio: 2022-11-01
Autor: Castioni, Piergiorgio
Palabras clave: Twitter, Other social sciences, COVID-19, Misinformation
Grupo de investigación: Alephsys
Año de publicación de la dataset: 2022
Acción del progama de financiación: Ministerio de Economía y Competitividad Ministerio de Ciencia, Innovación y Universidades, Agència de Gestió d’Ajuts Universitaris i de Recerca; Universitat Rovira i Virgili
Título del conjunto de datos: COVID-related tweets in the period between January and May 2020
Repositori URV