Multi-dimensional register classification using bigrams
Scott Crossley | Mississippi State University
Max M. Louwerse | University of Memphis
A corpus linguistic analysis investigated register classification using frequency of bigrams in nine spoken and two written corpora. Four dimensions emerged from a factor analysis using bigram frequencies shared across corpora: (1) Scripted vs. Unscripted Discourse, (2) Deliberate vs. Unplanned Discourse, (3) Spatial vs. Non-Spatial Discourse, and (4) Directional vs. Non-Directional Discourse. These findings were replicated in a second analysis. Both analyses demonstrate the strength of bigrams for classifying spoken and written registers, especially in locating distinct collocations among spoken corpora, as well as revealing syntactic and discourse features through a data-driven approach.
Keywords: register variation, multi-dimensional analysis, bigrams, collocations
Published online: 20 December 2007
https://doi.org/10.1075/ijcl.12.4.02cro
https://doi.org/10.1075/ijcl.12.4.02cro
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