Modelling social readers: novel tools for addressing reception from online book reviews.

ABSTRACT: Social reading sites offer an opportunity to capture a segment of readers' responses to literature, while data-driven analysis of these responses can provide new critical insight into how people 'read'. Posts discussing an individual book on the social reading site, Goodreads, are referred to as 'reviews', and consist of summaries, opinions, quotes or some mixture of these. Computationally modelling these reviews allows one to discover the non-professional discussion space about a work, including an aggregated summary of the work's plot, an implicit sequencing of various subplots and readers' impressions of main characters. We develop a pipeline of interlocking computational tools to extract a representation of this reader-generated shared narrative model. Using a corpus of reviews

SUBMITTER: Holur P 

PROVIDER: S-EPMC8692958 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature