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Political scientists have long asserted that populists use simpler language than their mainstream rivals to appeal to ordinary people and distance themselves from elites. However, there is little comparative evidence in support of that claim. In this study, we investigate the linguistic simplicity of four right-wing populists compared to their principal opponents in the United States, France, United Kingdom, and Italy. We do so by analysing a corpus of approximately one million words from leaders’ speeches, using a series of linguistics measures for evaluating simplicity. Contrary to expectations, we find that Donald Trump was only slightly simpler than Hillary Clinton, while Nigel Farage in the UK and Marine Le Pen in France were more complex than their main rivals, and Italy’s Matteo Salvini was simpler on some measures but not others. We conclude that the simple language claim is not borne out and that other aspects of the received wisdom about populism should be re-examined.

This paper describes a procedure to assess the acceptability of gender-inclusive linguistic structures. Informants were asked to provide an overall linguistic assessment of extracts from newspaper articles while unaware of the final objective of the survey, i.e. eliciting their opinions on the masculine and feminine forms of professions and titles. Although opinions varied, the results show an increase in the acceptability of feminine forms, probably strengthened by their frequent use in the media. Furthermore, those forms provide a solution to the morphological and syntactic inconsistencies considered by the informants as a violation of Italian grammar rules.

When analysing corpora with automatic and statistical means, one should remember that the raw material being treated is language and the specific nature thereof ought to be considered in all stages of research. Since language cannot be investigated per se, corpora can only reveal the characteristics of limited instances of linguistic behaviour: even exhaustive corpora only supply a finite set of texts which should be assessed in the light of a number of extra-linguistic factors impacting linguistic traits from different viewpoints: the sender’s and recipient’s region of origin, social and educational background and gender; the channel of communication; the topic under discussion and the formality of the situation, not to speak of the period in history when texts were produced. Such factors come into play in defining the linguistic properties of each single text (fragment) in the corpus, and their overall balance should be considered during the preliminary stages of corpus design and compilation. After having made decisions in terms of the selection of the texts to be included in the corpus, linguistic data need to be prepared for automatic processing. This stage too is far from intuitive and automatic: from the very identification of tokens of language to the extraction of lemmas, researchers should take into account qualitative aspects. Both corpus compilation and pre-processing cannot be considered neutral operations with a view to the results of automatic analysis and should be made explicit to enable the assessment of results and further exploitation of the same corpus.