Modeling Social Readers: Novel Tools for Addressing Reception from Online Book rsos.royalsocietypublishing.org Reviews Pavan Holur1;∗, Shadi Shahsavari1;∗, Research Ehsan Ebrahimzadeh, Timothy R. Tangherlini2;∗ and Vwani Roychowdhury1;∗ Article submitted to journal 1in order pholur,shadihpp,
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[email protected] mathematical modelling, ∗ Equal contribution computational social science, behaviour, pattern recognition, Readers’ responses to literature have received scant statistics, theory of computing attention in computational literary studies. The rise of social media offers an opportunity to capture a Keywords: segment of these responses while data-driven analysis natural language processing, of these responses can provide new critical insight into how people “read”. Posts discussing an individual narrative theory book on Goodreads, a social media platform that hosts user discussions of popular literature, are referred Author for correspondence: to as “reviews”, and consist of plot summaries, Pavan Holur opinions, quotes, or some mixture of these. Since e-mail:
[email protected] these reviews are written by readers, computationally modeling them allows one to discover the overall non-professional discussion space about a work, including an aggregated summary of the work’s plot, an implicit ranking of the importance of events, and the readers’ impressions of main characters. We develop a pipeline of interlocking computational tools to extract a representation of this reader- generated shared narrative model.