# A Data-Oriented Model of Literary Language

arXiv: https://arxiv.org/abs/1701.03329 · HTML: https://mlsanity.com/paper/1701.03329/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Jan 2017.

## Built on by (most cited first, 1 of 1)

- [Good Books are Complex Matters: Gauging Complexity Profiles Across Diverse Categories of Perceived Literary Quality](https://mlsanity.com/paper/2404.04022/) (2024)

## Abstract (arXiv)

We consider the task of predicting how literary a text is, with a gold standard from human ratings. Aside from a standard bigram baseline, we apply rich syntactic tree fragments, mined from the training set, and a series of hand-picked features. Our model is the first to distinguish degrees of highly and less literary novels using a variety of lexical and syntactic features, and explains 76.0 % of the variation in literary ratings.