We aim to develop computational tools for quality assessment and automated narrative analysis of fiction literature. We combine fractal analysis, sentiment analysis, and advanced language models with deep neural networks and machine learning to gain a deeper understanding of literary data structures. We combine that with studies of data on literary preferences and biases in valuation. The research group, which is funded 2021-25, is based at Aarhus University, Denmark.

Project Team

Associate Professor Kristoffer L. Nielbo, Center for Humanities Computing
Professor Mads Rosendahl Thomsen, Comparative Literature
Post.doc. Yuri Bizzoni, Comparative Literature
PhD research fellow Ida Marie S. Lassen, Information Science
Systems manager Peter Bjerregaard Vahlstrup, Center for Humanities Computing