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.
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Notes
- 1.
- 2.
This project is financed by the BBVA Foundation in its 2019 call for Ayudas a Equipos de Investigación Científica en el área de Economía y Sociedad Digital. https://www.rrssalud.org.
- 3.
Sources: EFE Verifica, Maldita and Newtral.
- 4.
The figure shows a big clique of 45 nodes, those tweets are the same tweets being posted by the same user and this user liking its own tweets.
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Saby, D. et al. (2021). Twitter Analysis of Covid-19 Misinformation in Spain. In: Mohaisen, D., Jin, R. (eds) Computational Data and Social Networks. CSoNet 2021. Lecture Notes in Computer Science(), vol 13116. Springer, Cham. https://doi.org/10.1007/978-3-030-91434-9_24
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