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How to interpret large volumes of patient feedback: methods from computer-assisted linguistics

Research output: Contribution to Journal/MagazineJournal articlepeer-review

<mark>Journal publication date</mark>06/2017
<mark>Journal</mark>Social Research Practice
Issue number1
Number of pages12
Pages (from-to)2-13
Publication StatusPublished
<mark>Original language</mark>English


In this article, we demonstrate how methods from corpus linguistics can be used to interpret large
collections of patient feedback. Using a series of established corpus linguistic techniques, this study
examines the key areas of concern in 29 million words of online patient feedback about the National
Health Service (NHS) in England. Focusing on the theme of staff rudeness, our analysis shows how the
power of computer-assisted textual analysis can be fruitfully synthesised with fine grained, humanled
analyses to develop a more refined picture of the complex ways that patients evaluate healthcare
services in their comments. We argue that, by affording the opportunity to study large collections of
authentic language data, corpus linguistics methods can facilitate the types of objective and empirical
approaches to large datasets that are now commonplace in the domain of evidence-based health
communication research.