Investigating Appraisal and the language of evaluation in fake news corpora

Corpus Pragmatics. 2024. Vol. 8. No. 2. P. 107–130.

Trnavac R., Poldvere N.

Abstract
The present corpus study, which is grounded in Appraisal Theory, investigates evaluative
language use in fake news in English. The primary aim is to find out how and
why, if at all, evaluative meanings are construed differently in fake news compared
to genuine news. The secondary aim is to explore potential differences between
types of fake news based on contextual factors. The data are from two carefullydesigned
corpora containing both fake and genuine news: a single-authored corpus
and a multi-authored corpus. Both corpora contain false information that is meant
to deceive, but they also differ from each other in terms of register, genre and the
motivational goals of the authors. Through qualitative and quantitative analyses, we
show that there are systematic differences in the occurrence of Appraisal expressions
across fake and genuine news, with Appraisal being more common in the former.
However, the exact nature of the affective, dialogic and modal expression of
fake news is influenced by contextual factors that, so far, have largely been ignored
in fake news research. Therefore, the study has important implications for the development
of fake news detection systems based on data sources of different kinds, a
task which is in grave need of the input of corpus linguists.

Keywords: disinformation, manual annotation, Appraisal Theory, inter-rater reliability

Publication based on the results of: Language in Real-world and Digital Environments (2024)