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Article published In:
Journal of Language Aggression and Conflict
Vol. 11:1 (2023) ► pp.1–24

“We were cocked & loaded to retaliate”

An appraisal-based study of dichotomies in Trump’s tweets about Iran

ORCID logo | University of New South Wales, Australia
ORCID logo | University of Sydney, Australia
The diplomatic relationship between the USA and Iran has long been fraught and is characterised by various conflicts and the implementation of economic sanctions. It can be argued that the relationship became even more hostile after Donald Trump was elected president of the US. Trump’s sentiments towards Iran were made public through his behavior on Twitter, both before and after he took over the Presidency. These sentiments have been a mix of negative and sometimes positive views and opinions. This study uses a corpus of Trump’s tweets that explicitly mention ‘Iran’ as the basis of a linguistic analysis and applies to it the analytical framework of appraisal from Systemic Functional Linguistics. More specifically, this study focuses on how he established an Us vs. Them dichotomy. While the analysis shows that Iran has been generally portrayed negatively by Trump, there were several tweets where the Iranian government was appraised positively, too. More interestingly, in those tweets, he seemed to target Obama and democrats and represent them negatively while Iran was assessed in positive terms.
Keywords: appraisal , Trump, Iran, discourse analysis, representation, ingroups, outgroups, democrats
Article outline
  • 1.Introduction
    • 1.1Background on Iran and US relations
    • 1.2Twitter and political communication
    • 1.3Aims and objectives
  • 2. appraisal: An overview
  • 3.Trump and Twitter
  • 4.Methodology
  • 5.Results and discussion
    • 5.1Iranian government vs. the US government
    • 5.2Obama administration vs. Trump (administration)
      • 5.2.1Trump and Iran vs. Obama
    • 5.3Iranian government vs. Iranian people
    • 5.4Media vs. Trump administration
  • 6.Conclusions
  • Notes
  • References
Published online: 30 August 2021
DOI logo
https://doi.org/10.1075/jlac.00069.mak
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