Types of Astroturfing campaigns of disinformative and polarised content in times of pandemic in Spain

Abstract

The paper seeks to determine the application of Astroturfing strategies on Twitter, at the Spanish level, during the period of the pandemic caused by Covid-19 in the spring of 2020. Statistical analysis, network analysis and machine learning techniques, around 32,527 messages, published from the state of alarm decree in Spain (March 14, 2020) until the end of May of the same year, associated with eight tags that address issues related to disinformative content identified by two of the main fact-checking projects (Maldito Bulo and Newtral). Data allow us to observe, among other things, the participation of users (not bots) who exercise an influencing role despite having an average profile or far from being considered as a public personality. The application of Astroturfing appreciated as a communication strategy used to position issues in social networks, at the level of public opinion in Spain, through the distribution, amplification and flood of disinformative content. The scenario allows us to verify the presence of a digital communicative scenario that would favour a more difficult framework for detecting disinformative content, from strategies such as the one studied, aimed at breaking the bell effect and bubble filter of social networks like Twitter. Everything, in order to position issues at the level of public opinion.