The syntactic position of the “people” in the political discourse of left and right populism (NLP-based syntactic analysis experience)

Abstract

This paper attempts to measure populism in English-language speeches of politicians using computational linguistics methods. The relevance of this study is related not only to the rise of populism in the world and the importance of understanding the mechanisms of political discourse, but also to the lack of linguistic research in the context of corpus studies. Most of the methods proposed to date require significant resources or suffer from structural limitations, especially when they rely heavily on the human annotation process to analyze extensive corpus data. The material for the study was public speeches and interviews of right-wing populist politician and 45th President of the United States Donald Trump and political rhetoric of left-wing populist politician Senator Bernie Sanders. The corpus analysis was based on transcripts downloaded from The American Presidency Project and Miller Center websites. The syntactic position of key lexical units is determined using a comprehensive method based on dependency grammar combined with natural language processing (NLP) and van Leeuwen’s linguistic theory. The application of natural language processing methods confirms the assumption that the frequency of politicians’ reference to the people is not the only relevant indicator for measuring people-centrism in (populist) political discourse, as usually proposed in the political science literature. The results of the study indicate that there is no predominant role of the people in the discourse of Trump and Sanders. In most cases, the people appear in a complementary or adjunct position, indicating their secondary importance in their rhetoric. Given that populism implies proximity to the people and is positioned as “vox populi” – “the voice of the people”, it can be assumed that for both Trump and Sanders, addressing the people is only a way to achieve their political goals.