Quantifying Systemic Coupling and Syndrome Using Multivariate Statistical Methods
An SFL Corpus Example
Keywords:appraisal; coupling; syndrome; quantitative analysis; multiple correspondence analysis; log-linear model
One of the fundamental underpinnings of systemic functional linguistics (SFL) is that the relationship between language-as-system and language-as-text is modelled probabilistically in relation to the cline of instantiation. This offers a spectrum of new ways to approach several SFL concepts quantitatively. This paper falls within that spectrum as it proposes that the relatively recent concepts of coupling and syndrome can be redefined quantitatively in relation to instantiation through two statistical methods – namely log-linear analysis and multiple correspondence analysis (MCA) The application of these two methods is illustrated through an analysis of a corpus of twelve online voting-based online debate texts (ODTs) The results and discussion sections of this paper show that the methods can identify and quantify significant couplings and syndromes from both probabilistic and statistical perspectives. Both methods illustratively highlight eleven couplings and four syndromes associated with the more persuasive and less persuasive ODTs writers.
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