Pushing Everyone’s Buttons: Cognitive Methods in Political Discourse Analysis

Laura A. Janda and Tore Nesset

Political discourse has become increasingly toxic in a media environment driven by whatever attracts the most attention – namely negative attitudes and distortions. This is particularly evident in times of conflict resulting from greed, aggression, climate change, and scarcity of resources. Given the overwhelming quantity of messages, a great challenge today is to sort through them in a meaningful way. As cognitive linguists we have an obligation to engage this challenge, and we also have a lot to offer. 

This theme session represents and compares various methods that investigate political messages in public discourse such as news media, social media, and political speeches. Methods are illustrated by case studies from a variety of languages. Some methods are part of the traditional canon of cognitive linguistic inquiry, others are of more recent origin, but all are compatible with a data-driven usage-based approach to linguistic analysis. 

Metaphor (Lakoff 2002), Metonymy (Panther 2005) are proven methods of analysis for political discourse, an arena where messaging is often multimodal. Blending and Compression (Fauconnier and Turner 2002) provide mental shortcuts that can be used and abused to political ends. Construction Grammar (Goldberg 1995, 2006) has become a major direction within Cognitive Linguistics, making it possible to analyze a whole language in terms of constructions, and to reveal the relationships among constructions. Frame Semantics (Fillmore et al. 2012) empowers us to analyze meanings of constructions, while Constructicography (collection and classification of grammatical constructions; Lyngfelt 2018) yields constructicons (interconnected inventories of constructions; Janda et al. Forthcoming). All of these are relevant to unraveling the underlying patterns in political discourse.

Computational and corpus methods present opportunities for cognitive linguists to compare the distribution of features observed in a political message (target text) with distribution in a reference corpus (Baker 2006, Baker et al. 2008, Groom 2019). Keyword Analysis (Scott & Tribble 2006, Fidler and Cvrček 2015) compares the distribution of words, and for inflected languages this approach can be extended as Keymorph Analysis (Fidler and Cvrček 2017) to probe the distribution of grammatical morphemes (such as those marking case on nouns), disclosing patterns at an even more systematic level. Market Basket Analysis, originally developed to encourage consumers to make additional purchases (“customers who bought X also bought Y”), is another innovative approach linguists can use to discover associative links among words and grammatical features in target texts (Cvrček and Fidler 2019).


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