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



Palabras clave:

Astroturfing, Disinformation, Hoaxes, Pandemics, Covid-19, Manipulation, Public opinion, Small-world, Thunderclap, Spain, Philippines, Nanoinfluencers, Geolocation


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.


Adhanom-Ghebreyesus, Tedros; Ng, Alex (2020). “Desinformación frente a medicina: hagamos frente a la ‘infodemia’”. El país, 18 febrero.

Aleixandre-Benavent, Rafael; Castelló-Cogollos, Lourdes; Valderrama-Zurián, Juan-Carlos (2020). “Información y comunicación durante los primeros meses de Covid-19. Infodemia, desinformación y papel de los profesionales de la información”. Profesional de la información, v. 29, n. 4, e290408.

Arce-García, Sergio; Menéndez-Menéndez, María-Isabel (2018). “Aplicaciones de la estadística al framing y la minería de texto en estudios de comunicación”. Información, cultura y sociedad, v. 39, pp. 61-70.

Barabasi, Albert-László (2016). Network science. Cambridge, United Kingdom: Cambridge university press. ISBN: 978 1 107 07626 6

Bastian, Mathieu; Heymann, Sebastien; Jacomy, Mathieu (2009). “Gephi: An open source software for exploring and manipulating networks”. Proceedings of the international AAAI conference on web and social media, v. 3, n. 1, pp. 361-362.

BBC (2020). “Philippines Troll Patrol: The woman taking on trolls on their own turf”. BBC news, 26 September.

Bengali, Shashank; Halper, Evan (2019). “Troll armies, a growth industry in the Philippines, may soon be coming to an election near you”. Los Angeles Times, 19 November.

Blanco-Alfonso, Ignacio; García-Galera, Carmen; Tejedor-Calvo, Santiago (2019). “El impacto de las fake news en la investigación en Ciencias Sociales. Revisión bibliográfica sistematizada”. Historia y comunicación social, v. 24, n. 2, pp. 449-469.

Blondel, Vicent D.; Guillaume, Jean-Lup; Lambiotte, Renaud; Lefebvre, Etienne (2008). “Fast unfolding of communities in large networks”. Journal of statistical mechanics: Theory and experiment, v. 10.

Bradshaw, Samantha; Bailey, Hannah; Howard, Phillip (2021). Industrialized disinformation. 2020 global inventory of organized media manipulation. Computational Propaganda Research Project. Oxford, United Kingdom: Internet Institute.

Bradshaw, Samantha; Howard, Philip N. (2018). Online supplement to working paper 2018.1. Challenging truth and trust: A global inventory of organized social media manipulation. Computational Propaganda Research Project. Oxford, United Kingdom: Oxford Internet Institute.

Campos-Domínguez, Eva; Calvo, Dafne (2017). “La campaña electoral en internet: planificación, repercusión, y viralización en Twitter durante las elecciones españolas de 2015”. Comunicación y sociedad, n. 29.

Cebrián, Manuel; Balsa-Barreiro, José (2021). “La enésima ola”. El país, 9 abril.

Chen, Jundong; Hossain, Shafaeat; Zhang, Huan (2020). “Analyzing the sentiment correlation between regular tweets and retweets”. Social network analysis and mining, v. 10, art. 13.

Collins, Ben; Zadrozny, Brandy (2020). “Troll farms from North Macedonia and the Philippines pushed coronavirus disinformation on Facebook”. NBC news, 29 May.

Davis, Richard G. (1991). “Operation ‘Thunderclap’: The US Army Air Forces and the bombing of Berlin”. Journal of strategic studies, v. 14, n. 1, pp. 90-111.

Diresta, Renee; Shaffer, Kris; Ruppel, Becky; Sullivan, David; Matney, Robert; Fox, Ryan; Albright, Jonathan; Johnson, Ben (2019). The tactics & tropes of the internet research agency. U.S. Senate documents. Congress of the United States.

Elmas, Tuğrulcan; Overdorf, Rebekah; Furkan-Özkalay, Ahmed; Aberer, Karl (2021). “Ephemeral astroturfing attacks: The case of fake Twitter trends”. In: IEEE European symposium on security and privacy 2021.

European Commission (2018). A multi-dimensional approach to disinformation. Luxembourg: Publications Office of the European Union. ISBN: 978 92 79 80419 9

Fitzgerald, Jonathan D. (2017). “Sentiment analysis of (you guessed it!) Donald Trump’s tweets”. Storybench, 17 December.

García-Marín, David (2020). “Infodemia global. Desórdenes informativos, narrativas fake y fact-checking en la crisis de la Covid-19”. Profesional de la información, v. 29, n. 4, e290411.

García-Orosa, Berta (2021). “Disinformation, social media, bots, and astroturfing: The fourth wave of digital democracy”. Profesional de la información, v. 30, n. 6, e300603.

Granovetter, Mark S. (1973). “The strength of weak ties”. American journal of sociology, v. 78, n. 6, pp. 1360-1380.

Guess, Andrew; Nyhan, Brendan; Reifler, Jason (2018). Selective exposure to misinformation: evidence from the consumption of fake news during the 2016 U.S. presidential campaign.

Higuchi, Koichi (2016). KH coder 3.

Himelboim, Itai; Smith, Marc A.; Rainie, Lee; Shneiderman, Ben; Espina, Camila (2017). “Classifying Twitter topic-net­works using social network analysis”. Social media + society, v. 3, n. 1.

Holbrook, Erik; Kaur, Gupreet; Bond, Jared; Imbriani, Josh; Nsoesie, Elaine; Grant, Christian (2016). “Tweet geolocation error estimation”. International conference on GIScience short paper proceedings, v. 1, n. 1, pp. 130-133.

Hrčková, Andrea; Srba, Ivan; Móro, Robert; Blaho, Radoslav; Šimko, Jakub; Návrat, Pavol; Bieliková, Mária (2019). “Unravelling the basic concepts and intents of misbehavior in post-truth society”. Bibliotecas. Anales de investigación, v. 15, n. 3, pp. 421-428.

Hu, Yifan (2006). “Efficient, high-quality force-directed graph drawing”. The mathematica journal, v. 10, n. 1, pp. 37-71.

Jack, Caroline (2017). Lexicon of lies: Terms for problematic information. New York, United States: Data & Society.

Jerit, Jennifer; Zhao, Yangzi (2020). “Political misinformation”. Annual review of political science, v. 23, pp. 77-94.

Jockers, Matthew (2017). Syuzhet, extracts sentiment and sentiment-derived plot arcs from text.

Kearney, Michael W. (2018). Tweetbotornot: An R package for classifying Twitter accounts as bot or not.

Keller, Franziska G.; Schoch, David; Stier, Sebastian; Yang, Junghwan (2020). “Political astroturfing on Twitter: how to coordinate a disinformation campaign”. Political communication, v. 37, n. 2, pp. 256-280.

Lantz, Brett (2019). Machine learning with R. Birmingham. United Kingdom: Packt publishing. ISBN: 978 1 78216 214 8

Lits, Brieuc (2020). “Exploring astroturf lobbying in the EU: The case of responsible energy citizen coalition”. European policy analysis, v. 7, n. 1, pp. 226-239.

López-García, Guillermo (2016). “‘New” vs. ‘old’ leaderships: the campaign of Spanish general elections 2015 on Twitter”. Comunicación y sociedad, v. 29, n. 3, pp. 149-167.

Lopreite, Milena; Panzarasa, Pietro; Puliga, Michelangelo; Riccaboni, Massimo (2021). “Early warnings of Covid-19 outbreaks across Europe from social media”. Scientific reports, v. 11, art. 2147.

Mahbub, Syed; Pardede, Eric; Kayes, A. S. M.; Rahayu, Wenny (2019). “Controlling astroturfing on the internet: a survey on detection techniques and research challenges”. International journal of web and grid services, v. 15, n. 2, pp. 139-158.

Mahtani, Shibani; Cabato, Regine (2019). “Why crafty internet trolls in the Philippines may be coming to a website near you”. The Washington Post, 26 July.

Martin, Shawn; Brown, W. Michael; Klavans, Richard; Boyack, Kevin W. (2011). “OpenOrd: An open-source toolbox for large graph layout”. In: Proceedings SPIE. Visualization and data analysis 2011, v. 7868.

Menczer, Filippo; Fortunato, Santo; Davis, Clayton A. (2020). A first course in network science. Cambridge, United Kingdom: Cambridge University Press. ISBN: 978 1 108 47113 8

Milgram, Stanley (1967). “The small world problem”. Psychology today, v. 1, n. 1, pp. 61-67.

Mohammad, Saif M. (2016). “Sentiment analysis: Detecting valence, emotions, and other affectual states from text”. In: Emotion measurement. Elsevier, pp. 201-237. ISBN: 978 0 08 100508 8

Mohammad, Saif M.; Turney, Peter D. (2010). “Emotions evoked by common words and phrases: Using mechanical Turk to create an emotion lexicon”. In: Proceedings of the NAACL-HLT 2010 workshop on computational approaches to analysis and generation of emotion in text, pp. 26-34.

Mohammad, Saif M.; Turney, Peter D. (2013). “Crowdsourcing a word-emotion association lexicon”. Computational intelligence, v. 29, n. 3, pp. 436-465.

Ong, Jonathan-Corpus; Cabañes, Jason-Vicent A. (2019). Politics and profit in the fake news factory. Four work models of political trolling in the Philippines. Riga, Latvia: NATO strategic communications, centre of excellence. ISBN: 978 9934 564 54 3

Ong, Jonathan-Corpus; Tapsell, Ross; Curato, Nicole (2019). Tracking digital disinformation in the 2019 Philippine Midterm Election. Camberra, Australia: New Mandala.

Ortega, Andrés (2020). “Infodemic and mediademic”. Real Instituto Elcano, 31 marzo.

Pérez-Colomé, Jordi (2020). “‘Yo fui un bot’: las confesiones de un agente dedicado al engaño en Twitter”. El país, 21 mayo.

Salaverría, Ramón; Buslón, Nataly; López-Pan, Fernando; León, Bienvenido; López-Goñi, Ignacio; Erviti, María-Carmen (2020). “Desinformación en tiempos de pandemia: Tipología de los bulos sobre la Covid-19”. Profesional de la información, v. 29, n. 3, e290315.

Sauter, Disa A.; Eisner, Frank; Ekman, Paul; Scott, Sophie K. (2010). “Cross-cultural recognition of basic emotions through nonverbal emotional vocalizations”. Proceedings of the National Academy of Sciences, v. 107, n. 6, pp. 2408-2412.

Schoch, David; Keller, Franzisca B.; Stier, Sebastian; Yang, Jung Hwan (2022). “Coordination patterns reveal online political astroturfing across the world”. Scientific reports, v. 12, art. 4572.

Sorensen, Anne; Andrews, Lynda; Drennan, Judy (2017). “Using social media posts as resources for engaging in value co-creation: The case for social media-based cause brand communities”. Journal of service theory and practice, v. 27, n. 4, pp. 898-922.

Tarjan, Robert (1972). “Depth-first search an linear graph algorithms”. Siam journal on computing, v. 1, n. 2, pp. 146-160.

Torabi, Fatemeh; Taboada, Maite (2019). “Big data and quality data for fake news and misinformation detection”. Big data & society, v. 6, n. 1.

Van-der-Veen, Han; Hiemstra, Djoerd; Van-den-Broek, Tijs; Ehrenhard, Michel; Need, Ariana (2015). “Determine the user country of a tweet”. Social and information networks.

Vidgen, Bertram (2019). Tweeting Islamophobia. Doctoral thesis, University of Oxford. British Library Ethos (E-theses online service).

Vila-Márquez, Fátima; Arce-García, Sergio (2019). “Fake news y difusión en Twitter: El caso de Curro, el perro ‘condenado’”. Historia y comunicación social, v. 24, n. 2, pp. 485-503.

Wardle, Claire; Derakhshan, Hossein (2017). Information disorder: Toward an interdisciplinary framework for research and policy making. Brussels, Belgium: Council of Europe.

Wason, Peter-Cathcart (1960). “On the failure to eliminate hypotheses in a conceptual task”. Quarterly journal of experimental psychology, v. 12, n. 3, pp. 129-140.

Williams, Matthew (2021). The science of hate. London, United Kingdom: Faber & Faber. ISBN: 978 0 571 35706 2

Wissman, Barrett (2018). “Micro-influencers: The marketing force of the future?”. Forbes, 2 March.

World Health Organization (2020). “Working together to tackle the ‘infodemic’”. World Health Organization. Regional Office for Europe, June 29.

Zhao, Zilong; Shao, Jichang; Sano, Yukie; Takayasu, Hideki; Takayasu, Misako; Li, Daquing; Wu, Junjie; Havlin, Shlomo (2020). “Fake news propagates differently from real news even at early stages of spreading”. EPJ data science, v. 9, n. 7.



Cómo citar

Arce-García, S., Said-Hung, E., & Mottareale-Calvanese, D. (2022). Astroturfing as a strategy for manipulating public opinion on Twitter during the pandemic in Spain. Profesional De La información, 31(3).



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