When negativity is the fuel. Bots and Political Polarization in the COVID-19 debate

Robles, José-Manuel, Guevara, Juan-Antonio, Casas-Mas, Belén and Gómez, Daniel When negativity is the fuel. Bots and Political Polarization in the COVID-19 debate. Comunicar, 2022, vol. 30, n. 71, pp. 63-75. [Journal article (Paginated)]

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English abstract

The contexts of social and political polarization are generating new forms of communication that affect the digital public sphere. In these environments, different social and political actors contribute to extreme their positions, using bots to create spaces for social distancing where hate speech and incivility have a place, a phenomenon that worries scientists and experts. The main objective of this research is to analyze the role that these automated agents played in the debate on social networks about the Spanish Government’s management of the global COVID-19 pandemic. For this, “Social Big Data Analysis” techniques were applied: “machine learning algorithms to know the positioning of users; bot detection algorithms; “topic modeling” techniques to learn about the topics of the debate on the web, and sentiment analysis. We used a database comprised of Twitter messages published during the confinement, as a result of the Spanish state of alarm. The main conclusion is that the bots could have served to design a political propaganda campaign initiated by traditional actors with the aim of increasing tension in an environment of social emergency. It is argued that, although these agents are not the only actors that increase polarization, they do contribute to deepening the debate on certain key issues, increasing negativity.

Spanish abstract

Los contextos de polarización social y política están generando nuevas formas de comunicar que inciden en la esfera pública digital. En estos entornos, distintos actores sociales y políticos estarían contribuyendo a extremar sus posicionamientos, utilizando «bots» para crear espacios de distanciamiento social en los que tienen cabida el discurso del odio y la «incivility», un fenómeno que preocupa a científicos y expertos. El objetivo principal de esta investigación es analizar el rol que desempeñaron estos agentes automatizados en el debate en redes sociales sobre la gestión del Gobierno de España durante la pandemia global de COVID-19. Para ello, se han aplicado técnicas de «Social Big Data Analysis»: algoritmos de «machine learning» para conocer el posicionamiento de los usuarios; algoritmos de detección de «bots»; técnicas de «topic modeling» para conocer los temas del debate en la red, y análisis de sentimiento. Se ha utilizado una base de datos compuesta por mensajes de Twitter publicados durante el confinamiento iniciado a raíz del estado de alarma español. La principal conclusión es que los «bots» podrían haber servido para diseñar una campaña de propaganda política iniciada por actores tradicionales con el objetivo de aumentar la crispación en un ambiente de emergencia social. Se sostiene que, aunque dichos agentes no son los únicos actores que aumentan la polarización, sí coadyuvan a extremar el debate sobre determinados temas clave, incrementando la negatividad.

Item type: Journal article (Paginated)
Keywords: COVID-19; political bots; political polarization; digital propaganda; public opinion; social networks analysis; COVID-19; bots políticos; polarización política; propaganda digital; opinión pública; análisis de redes sociales
Subjects: B. Information use and sociology of information > BJ. Communication
G. Industry, profession and education.
G. Industry, profession and education. > GH. Education.
Depositing user: Alex Ruiz
Date deposited: 21 Mar 2022 07:14
Last modified: 21 Mar 2022 07:14
URI: http://hdl.handle.net/10760/42973

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