Tipus de document: info:eu-repo/semantics/other
DOI: 10.5061/dryad.bzkh189cc
Publicacions relacionades: 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
Grup de recerca: Alephsys
Departament: Enginyeria Informàtica i Matemàtiques
Autor: Castioni, Piergiorgio
Data alta repositori: 2022-11-01
Acció del programa de finançament: Ministerio de Economía y Competitividad Ministerio de Ciencia, Innovación y Universidades, Agència de Gestió d’Ajuts Universitaris i de Recerca; Universitat Rovira i Virgili
Any de publicació de la dataset: 2022
Matèria: Enginyeria
Identificador del investigador: 0000-0001-5560-7094
DOI de la publicació relacionada: 10.1098/rsos.220716
Idioma: en
Publicat per (editora): Universitat Rovira i Virgili (URV)
Drets d'accés: info:eu-repo/semantics/openAccess
Resum: 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