Tipo de documento: info:eu-repo/semantics/other
DOI: 10.5061/dryad.bzkh189cc
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
Grupo de investigación: Alephsys
Departamento: Enginyeria Informàtica i Matemàtiques
Autor: Castioni, Piergiorgio
Fecha alta repositorio: 2022-11-01
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
Año de publicación de la dataset: 2022
Materia: Enginyeria
Identificador del investigador: 0000-0001-5560-7094
DOI de la publicación relacionada: 10.1098/rsos.220716
Idioma: en
Publicado por (editorial): Universitat Rovira i Virgili (URV)
Derechos de acceso: info:eu-repo/semantics/openAccess
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.
Repositori URV