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.
Impact & Fiction
Measuring the impact of fiction on readers
image credit: Shutterstock
Participating organisations
Output
- 1.Author(s): Marijn Koolen, Joris van Zundert, Eva Viviani, Carsten Schnober, Willem van Hage, Katja TereshkoPublished by Universitäts- und Landesbibliothek Darmstadt in 202410.48694/jcls.3927
- 2.Author(s): Eva Viviani, Michael Ramscar, Elizabeth WonnacottPublished in Cognitive Science by Wiley in 202410.1111/cogs.13445
Team
Contact person
Willem van Hage
eScience Research Engineer / Technology Lead
Netherlands eScience Center
0000-0002-6478-3003
Mail WillemPB
Peter Boot
MK
Marijn Koolen
Willem van Hage
Ole Mussmann
Carsten Schnober
Angel Daza