Measuring the Candidates’ Emotions in Political Debates Based on Facial Expression Recognition Techniques
Identificadores
URI: http://hdl.handle.net/20.500.12020/1244DOI: https://doi.org/10.3389/fpsyg.2022.785453
Fecha
2022-05-09Tipo de documento
articleÁrea/s de conocimiento
Ciencias Sociales, Políticas y del ComportamientoResumen
This article presents the analysis of the main Spanish political candidates for the elections
to be held on April 2019. The analysis focuses on the Facial Expression Analysis (FEA),
a technique widely used in neuromarketing research. It allows to identify the microexpressions
that are very brief, involuntary. They are signals of hidden emotions that
cannot be controlled voluntarily. The video with the final interventions of every candidate
has been post-processed using the classification algorithms given by the iMotions’s
AFFDEX platform. We have then analyzed these data. Firstly, we have identified and
compare the basic emotions showed by each politician. Second, we have associated
the basic emotions with specific moments of the candidate’s speech, identifying the
topics they address and relating them directly to the expressed emotion. Third, we
have analyzed whether the differences shown by each candidate in every emotion are
statistically significant. In this sense, we have applied the non-parametric chi-squared
goodness-of-fit test. We have also considered the ANOVA analysis in order to test
whether, on average, there are differences between the candidates. Finally, we have
checked if there is consistency between the results provided by different surveys from
the main media in Spain regarding the evaluation of the debate and those obtained in
our empirical analysis. A predominance of negative emotions has been observed. Some
inconsistencies were found between the emotion expressed in the facial expression and
the verbal content of the message. Also, evidences got from statistical analysis confirm
that the differences observed between the various candidates with respect to the basic
emotions, on average, are statistically significant. In this sense, this article provides a
methodological contribution to the analysis of the public figures’ communication, which
could help politicians to improve the effectiveness of their messages identifying and
evaluating the intensity of the expressed emotions.