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10th International Conference on Computational Data and Social Networks, CSoNet 2021 ; 13116 LNCS:267-278, 2021.
Article in English | Scopus | ID: covidwho-1597625

ABSTRACT

A graph analysis on the tweets and users networks from a set of curated news was done to study the existing difference in communication patterns between legitimate and misinformation news. Our findings suggest there is no difference in the influence of misinformation and legitimate news but misinformation news tend to be more shared and present than legitimate news, meaning that while misinformation tweets do not have more influence, their authors are more prolific. Misinformation reach wider audience even if the tweets, individually, are not more influential. A subsequent qualitative analysis on the users reveal that there is also influence of misinformation spreading in Spain from other Spanish speaking countries. © 2021, Springer Nature Switzerland AG.

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