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Impact & Fiction

Measuring the impact of fiction on readers

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In this project we ask which properties of fictional texts have impact on readers. The impact types we look at include affective responses to narrative and style as well as reflection. We distinguish different groups of readers and require the textual properties to be meaningful to literary researchers and readers. Earlier research often handled all readers as essentially similar and targeted a single measure of success (popularity or sales). It also tried to predict success based on features that are hard to interpret from a literary point of view (such as word frequencies). We will use a large corpus of recent Dutch novels (10921 texts), a large corpus of online book reviews (> 472000) and a large collection of book lists (> 37400) created by users on book-oriented social media sites. In the reviews, we measure different types of impact. Based on the book lists, we cluster readers by their preferred type of reading. For the texts, we define new metrics for key textual properties that (we hypothesize) are partly responsible for the impact a book has on its readers. These metrics will include parameters referring to the novel's narrative, writing style and mood.

Participating organisations

Social Sciences & Humanities
Huygens Instituut
KNAW Humanities Cluster
Koninklijke Bibliotheek
Netherlands eScience Center




Peter Boot
Lead Applicant
Huygens Institute for the History of the Netherlands
Marijn Koolen
Humanities Cluster, KNAW
Willem van Hage
eScience Research Engineer / Technology Lead
Netherlands eScience Center
Ole Mussmann
Ole Mussmann
eScience Research Engineer
Netherlands eScience Center
Jisk Attema
Jisk Attema
Programme Manager
Netherlands eScience Center
Carsten Schnober
eScience Research Engineer
Netherlands eScience Center