Interim seminar: multidimensional analysis


In order to investigate what linguistic features distinguish between monodisciplinary and interdisciplinary journal discourses, we employed Biber’s (1988) multidimensional (MD) analysis. This well-known technique in corpus linguistics investigates quantitative correlations between language features in texts and discloses functional similarities and differences between corpora. The corpus used for this study consists of all the research papers published in 11 journals over 10 years, which were provided by our partners, Elsevier publishers.

In short, multidimensional (MD) analysis is a methodological approach that identifies co-occurrence patterns of linguistic features based on the factor analysis and characterises a text or a group of texts in terms of those patterns that are functionally interpreted. For example, some of the linguistic features used in the analysis include measuring average word length in texts, that deletions (e.g. The results showed that high concentrations of CO2 can affect…), the use of present or past tense, the use of passives, use of nominalisations (nouns derived from words, such as contamination, development, production and sampling), etc.

So far, we have identified six factors that between distinguish co-occurring linguistic features. Each factor represents a specific ʻstylisticʼ characteristic that makes one text different from another. We have tentatively interpreted these factors and proposed dimension descriptions, but as this is a work in progress further analyses and interpretations will be conducted. You can find out more from the attached presentation.

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