This paper applies a new approach to the identification of discourses, based on Multiple Correspondence Analysis (MCA), to the study of discourse variation over time. The MCA approach to keywords deals with a major issue with the use of keywords to identify discourses: the allocation of individual keywords to multiple discourses. Yet, as this paper demonstrates, the approach also allows us to observe variation in the prevalence of discourses over time. The MCA approach to keywords allows the allocation of individual texts to multiple discourses based on patterns of keyword co-occurrence. Metadata in the corpus data analysed (here, UK newspaper articles about Islam) can then be used to map those discourses over time, resulting in a clear view of how the discourses vary relative to one another as time progresses. The paper argues that the drivers for these fluctuations are language external; the real-world events reported on in the newspapers.
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This list is based on CrossRef data as of 6 january 2025. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers.
Any errors therein should be reported to them.
