Key points are not available for this paper at this time.
Despite all the elasticity and even ambiguity surrounding the concept of populism, the existing paradigms converge in the recognition of a populist rhetoric. By using Natural Language Processing (NLP) tools we propose a set of linguistic and discursive markers to identify populist markers in Presidential speeches. The performance of these markers is subsequently tested against the Global Populism Database (GPD). We set-up a multinomial regression model to study the predictive power of these markers on the GPD populist score, focusing on left-wing populist leaders in Spanish-speaking countries in Latin America. We are thus able to characterize (left-wing) populism as a style of communication, as well as to understand what is behind this rhetoric. Our results show that ingroup and emotional content are more present in populist speeches. We also find a positive relation between populism and the use future tense and conditional connectors, which suggest an intention to manipulate the audience. These results have implications both for the current understanding of (left-wing) populist rhetoric and for the conceptualization of populism itself.
Raveau et al. (Thu,) studied this question.