An Analysis of Reader Engagement in Literary Fiction through Eye Tracking and Linguistic Features
This incremental work addresses the challenge of understanding reader engagement for improving narrative generation and writing tools.
The study tackled the problem of capturing reader engagement in fiction by analyzing eye tracking, annotations, and survey data from 23 readers on 2 short stories, finding that text qualities predict engagement while accounting for individual differences.
Capturing readers' engagement in fiction is a challenging but important aspect of narrative understanding. In this study, we collected 23 readers' reactions to 2 short stories through eye tracking, sentence-level annotations, and an overall engagement scale survey. We analyzed the significance of various qualities of the text in predicting how engaging a reader is likely to find it. As enjoyment of fiction is highly contextual, we also investigated individual differences in our data. Furthering our understanding of what captivates readers in fiction will help better inform models used in creative narrative generation and collaborative writing tools.