Discursive news values analysis: the case of Liz Truss’ representation in the British press
-
Ester Di Silvestro
and
Marco Venuti
Abstract
This paper focuses on the news representation of Liz Truss by the British press, starting from the identification of news values. In addition, our analysis investigates the portrayal of Truss as a gendered social actor. The data were retrieved online through the resource LexisNexis – using the keyword “Truss” in headlines and lead paragraphs in both British broadsheets and tabloids – during three crucial days: 10 July 2022, the day Truss announced her candidacy for the leadership of the Conservative Party and as Prime Minister, 5 September 2022, when she became leader of the Conservative Party and consequently the new Prime Minister, and 20 October 2022, the day she announced her resignation as leader of the Conservative Party and Prime Minister. These data were analysed combining Bednarek’s and Caple’s Discursive News Values Analysis (DNVA) and Multimodal Critical Discourse Analysis (MCDA). Our findings identify the most frequent news values employed by British national newspapers in Truss’ portrayal during the selected timespans and highlight the connection between those values and her gendered representation.
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Articles in the same Issue
- Frontmatter
- Editorial
- Introduction to the Special Issue: Pragmatics, digital content and opinions
- Research Articles
- Discursive news values analysis: the case of Liz Truss’ representation in the British press
- The case of romantic relationships: analysis of the use of metaphorical frames with ‘traditional family’ and related terms in political Telegram posts in three countries and three languages
- Expressing anger on Mexican X/Twitter: the case of Uber customer complaints
- Expressing negative opinions through metaphor and simile in popular music reviews
- Slur reclamation, irony, and resilience
- What is the authentic internet register before & after the Russian invasion in Ukraine? Polish and Czech YouTube comments from 2021–2023
- Application of natural language processing for the recognition of obesity-related topics in the discourses of Argentine Twitter users
- Opinion events and stance types: advances in LLM performance with ChatGPT and Gemini
- Classifying offensive language in Arabic: a novel taxonomy and dataset
- Implicit offensive language taxonomy
