Astroturfing as a strategy for manipulating public opinion on Twitter during the pandemic in Spain

  1. Arce-García, Sergio 1
  2. Said-Hung, Elías 1
  3. Mottareale-Calvanese, Daría 1
  1. 1 Universidad Internacional de La Rioja
    info

    Universidad Internacional de La Rioja

    Logroño, España

    ROR https://ror.org/029gnnp81

Zeitschrift:
El profesional de la información

ISSN: 1386-6710,  1699-2407

Datum der Publikation: 2022

Titel der Ausgabe: Crisis en el espacio público

Ausgabe: 31

Nummer: 3

Art: Artikel

DOI: 10.3145/EPI.2022.MAY.10 DIALNET GOOGLE SCHOLAR lock_openOpen Access editor

Andere Publikationen in: El profesional de la información

Ziele für nachhaltige Entwicklung

Zusammenfassung

This work aims to establish whether astroturfing was used during the Covid-19 pandemic to manipulate Spanish public opinion through Twitter. This study analyzes tweets published in Spanish and geolocated in the Philippines, and its first objective is to determine the existence of an organized network that directs its messages mainly towards Spain. To determine the non-existence of a random network, a preliminary collection of 1,496,596 tweets was carried out. After determining its 14 main clusters, 280 users with a medium-low profile of participation and micro- and nano-influencer traits were randomly selected and followed for 103 days, for a total of 309,947 tweets. Network science, text mining, sentiment and emotion, and bot probability analyses were performed using Gephi and R. Their network structure suggests an ultra-small-world phenomenon, which would determine the existence of a possible organized network that tries not to be easily identifiable. The data analyzed confirm a digital communication scenario in which astroturfing is used as a strategy aimed at manipulating public opinion through non-influencers (cybertroops). These users create and disseminate content with proximity and closeness to different groups of public opinion, mixing topics of general interest with disinformation or polarized content.

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Fuente de los datos: Dialnet