Coverage of the 2021 Madrid regional election campaign by the main Spanish newspapers on Twitter: natural language processing and machine learning algorithms

Abstract

The aim of this work is to study the news coverage by the main Spanish generalist newspapers on Twitter during the campaign for the Community of Madrid elections in 2021 (n = 2,709). Natural language processing techniques and machine learning algorithms are applied to identify the predominant topic related to the elections and the mentions of candidates and political parties by each media, and to calibrate the emotional value of the messages published by El país, El mundo, Eldiario.es, and El confidencial. Among other findings, the results reveal how the media coverage focused mainly on campaign events and electoral debates. Despite the detection of minor differences between the newspapers, a general pattern emerges through this content, with a notable dominance of Isabel Díaz Ayuso but little influence of Rocío Monasterio as the lead candidates for their party. The sentiment analysis reveals the political alignment of each newspaper, using mainly negative messages with the aim of reducing the importance of a candidate or political party. While El país and Eldiario.es focused their criticism on Vox and the Partido Popular, El mundo and El confidencial criticized the actions of the national government, the PSOE’s proposal to join forces with Unidas Podemos, and Vox’s position, as well as emphasizing the disaster faced by Ciudadanos. It can be deduced that the media contributed to Ayuso’s success and to the consolidation of her image as an individual distinct from her own party.