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A Mixed Approach for Aggressive Political Discourse Analysis on Twitter

Torregrosa, Javier; D’Antonio-Maceiras, Sergio; Villar-Rodríguez, Guillermo; Hussain, Amir; Cambria, Erik; Camacho, David

Authors

Javier Torregrosa

Sergio D’Antonio-Maceiras

Guillermo Villar-Rodríguez

Erik Cambria

David Camacho



Abstract

Political tensions have grown throughout Europe since the beginning of the new century. The consecutive crises led to the rise of different social movements in several countries, in which the political status quo changed. These changes included an increment of the different tensions underlying politics, as has been reported after many other political and economical crises during the twentieth century. This article proposes the study of the political discourse, and its underlying tension, during Madrid’s elections (Spain) in May 2021 by using a mixed approach. To demonstrate if an aggressive tone is used during the campaign, a mixed methodology approach is applied: quantitative computational techniques, related to natural language processing, are used to conduct a first general analysis of the information screened; then, these methods are used for detecting specific trends that can be later filtered and analyzed using a qualitative approach (content analysis), which is also conducted to extract insights about the information found. The main outcomes of this study show that the electoral campaign is not as negative as perceived by the citizens and that there was no relationship between the tone of the discourse and its dissemination. The analysis confirms that the most ideologically extreme parties tend to have a more aggressive language than the moderate ones. The content analysis carried out using our methodology showed that Twitter is used as a sentiment thermometer more than as a way of communicating concrete politics.

Journal Article Type Article
Acceptance Date Jul 19, 2022
Online Publication Date Aug 17, 2022
Publication Date 2023
Deposit Date Oct 7, 2022
Publicly Available Date Aug 18, 2023
Journal Cognitive Computation
Print ISSN 1866-9956
Electronic ISSN 1866-9964
Publisher Springer
Peer Reviewed Peer Reviewed
Volume 15
Pages 440-465
DOI https://doi.org/10.1007/s12559-022-10048-w
Keywords Natural language processing, Sentiment analysis, Content analysis, Aggressive discourse, Mixed methods, Twitter
Public URL http://researchrepository.napier.ac.uk/Output/2911133

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