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Riddle of Literary Quality
(Englisch)
A Computational Approach
Karina Dalen-Oskam

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Produktbeschreibung

Prof. Dr. Karina van Dalen-Oskam is head of the research group Computational Literary Studies at Huygens Institute and professor in Computational Literary Studies at the University of Amsterdam. In 2021 she published a longer Dutch version of this book with AUP, Het raadsel literatuur: is literaire kwaliteit meetbaar?


What is literature? Can we measure `literariness´ in texts themselves? The innovative Computational Humanities project The Riddle of Literary Quality asked thousands of Dutch readers for their opinion about contemporary Dutch and translated novels. The public shared which novels they had read, what they really thought of them, and how they judged their quality. Their judgments of the same novels were compared with the results of computational analysis of the books.

Using evidence from almost 14,000 readers and building on more textual data than ever before, Van Dalen-Oskam and her team uncovered unconscious biases that shed new light on prejudices many people assumed no longer existed. This monograph explains in an accessible way how the project unfolded, which methods were used, and how the results may change the future of Literary Studies.


1 The Riddle 2 The National Reader Survey 3 Romance, Suspense, and Translations 4 Literary Novels Written by Women 5 Literary Novels Written by Men 6 Style, Gender, and Genre 7 The Riddle of Literary Quality Solved? Appendix 1: The Survey Appendix 2: The Books Appendix 3: The Website, Bibliography, Tables, Figures, Acknowledgements, Index.
The innovative Computational Humanities project The Riddle of Literary Quality collected opinions from thousands of Dutch readers about contemporary Dutch and translated novels, comparing their quality judgments with computational analysis of the same books to explore what constitutes literariness in texts. Using evidence from almost 14,000 readers and extensive textual data, Van Dalen-Oskam and her team uncovered unconscious biases that reveal persistent prejudices, presenting their accessible methodology and results that may transform the future of Literary Studies.


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