Critical Discourse Analysis (CDA) is often criticised for not incorporating identifiable and accountable methods in its qualitative analyses (e.g. Rheindorf 2019), leading critics to comment that qualitative CDA methods lack transparency, replicability, and can lead to a high risk of researcher bias (Widdowson 2004: 109). This paper seeks to account for some of these limitations in the context of the press representation of protests. In doing so, it formulates the novel linguistic application of Tilly’s (2004) sociological ‘WUNC’ framework, which argues protests are successful when they display worthiness, unity, numbers and commitment (WUNC):
• Worthiness: protesters are credible
• Unity: protesters agree amongst themselves
• Numbers: there are numerous protesters
• Commitment: protesters will not give up
By drawing on prominent methods and theories established in CDA, the paper formulates transparent linguistic categorisations of WUNC — realised through referential strategies (worthiness), possessive pronouns and determiners (unity), aggregation (numbers) and modality and evaluation (commitment) — that contribute to an explicit qualitative framework that can be used to analyse the press representation of protests.
To demonstrate how this novel application of WUNC can be used in CDA, the paper uses the UK press reporting of the ‘People’s Vote’ anti-Brexit protests that took place between 2018 and 2019 as a case study. In doing so, it investigates how linguistic manifestations of WUNC can be manipulated by the press to convey support or opposition to the anti-Brexit protests, as a means to either legitimate (anti-Brexit press) or delegitimate (pro-Brexit press) the marches.
Charlotte-Rose Kennedy is an Arts and Humanities Research Council funded doctoral student in Linguistics and lecturer in Discourse Analysis at Nottingham Trent University. Grounded in critical discourse analysis and corpus linguistics, her research combines multidisciplinary methods in the critical analysis of media representations of protest.
