Discourse and bias: A corpus-assisted discourse analysis on Donald Trump in The Washington Post
2024 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE credits
Student thesis
Abstract [en]
This study explores the evolution of discourse surrounding Donald Trump as depicted in The Washington Post, and examines potential biases in the newspaper's articles across two distinct periods: 2015-2017, from when Trump announced his candidacy for the 2016 presidential election until his inauguration, and 2022-2024, from when he announced his candidacy for the 2024 election until the data collection date. Using corpus-assisted discourse analysis, the study investigates keywords and their collocating adjectival modifiers within the two corpora to reveal patterns in the discourse and potential bias around Trump. The results show that during the 2015-2017 period, the discourse predominantly centered on Trump's rivalry with Hillary Clinton, characterized by personal attacks and recurring themes of corruption, authoritarianism, and widespread protests against his presidency. In contrast, the 2022-2024 period's discourse focused more on Trump's legal challenges, particularly regarding the mishandling of classified information and doubts about electoral integrity, indicating a shift in discourse. The findings do not explicitly demonstrate bias towards Trump. However, the discussion highlights the potential for bias to subtly manifest itself through language choices, issue framing, and narrative selection.
Place, publisher, year, edition, pages
2024. , p. 29
Keywords [en]
corpus-assisted discourse analysis, Donald Trump, The Washington Post, 2024 US election, 2016 US election, keyword analysis, AntConc
National Category
Humanities and the Arts General Language Studies and Linguistics
Identifiers
URN: urn:nbn:se:mdh:diva-67734OAI: oai:DiVA.org:mdh-67734DiVA, id: diva2:1874671
Subject / course
English
Supervisors
Examiners
2024-06-262024-06-202025-10-10Bibliographically approved