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Reading Dickens’s characters: Employing psycholinguistic methods to investigate the cognitive reality of patterns in texts

This article reports the findings of an empirical study that uses eye-tracking and follow-up interviews as methods to investigate how participants read body language clusters in novels by Charles Dickens. The study builds on previous corpus stylistic work that has identified patterns of body languag...

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Detalles Bibliográficos
Autores principales: Mahlberg, Michaela, Conklin, Kathy, Bisson, Marie-Josée
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5897890/
https://www.ncbi.nlm.nih.gov/pubmed/30262970
http://dx.doi.org/10.1177/0963947014543887
Descripción
Sumario:This article reports the findings of an empirical study that uses eye-tracking and follow-up interviews as methods to investigate how participants read body language clusters in novels by Charles Dickens. The study builds on previous corpus stylistic work that has identified patterns of body language presentation as techniques of characterisation in Dickens (Mahlberg, 2013). The article focuses on the reading of ‘clusters’, that is, repeated sequences of words. It is set in a research context that brings together observations from both corpus linguistics and psycholinguistics on the processing of repeated patterns. The results show that the body language clusters are read significantly faster than the overall sample extracts which suggests that the clusters are stored as units in the brain. This finding is complemented by the results of the follow-up questions which indicate that readers do not seem to refer to the clusters when talking about character information, although they are able to refer to clusters when biased prompts are used to elicit information. Beyond the specific results of the study, this article makes a contribution to the development of complementary methods in literary stylistics and it points to directions for further subclassifications of clusters that could not be achieved on the basis of corpus data alone.