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Articles

Mediating Knowledge through Expressing Surprises: A Frame-based Analysis of Surprise Markers in Research Articles across Disciplines and Research Paradigms

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ABSTRACT

Taking a cognitive approach to genre-specific language, this corpus-based study investigated the disciplinary and paradigmatic effect on the use of a specific type of attitude markers—surprise markers—with an analytical framework informed by frame semantics. A Surprise frame was generated and then used to analyze the use of surprise markers in a 2,000,000-word corpus consisting of 320 full-length empirical research articles collected from two social sciences (applied linguistics vs. clinical psychology) cutting across two research paradigms (qualitative vs. quantitative). Results from multiple binary logistic regression analyses show that the research paradigm can reliably predict the absence or presence of five categories across four frame elements of the Surprise frame. This study not only extends the application of frame semantics to discourse analysis but also has the potential to create a new direction for research in English for academic purpose.

Acknowledgement

This work was based on one of the pilot studies carried out by the first author for his doctorial thesis and was supported by NTU Research Scholarship (August 2017-August 2021) awarded to him by Nanyang Technological University.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. FN is an ongoing project to build a lexical database of English that is both human and machine readable. This project is created by Charles Fillmore and his colleagues based on the theory of frame semantics and has been in operation at the International Computer Science Institute in Berkeley, California since 1977. It is now an important tool for lexical research with a semantic orientation (Ruppenhofer et al., Citation2016).

2. The annotation convention adopted in FN is used for examples 1 to 3 for the sake of discussion because these examples are taken from FN. The rest of the examples, which are from our corpus, are presented in a simpler format, with focus only on the FE under discussion.

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