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Bibliographic Details
Main Author: Xing, Yi
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2509.06637
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author Xing, Yi
author_facet Xing, Yi
contents Intertextuality is a central tenet in literary studies. It refers to the intricate links between literary texts that are created by various types of references. This paper proposes a new quantitative model of intertextuality to enable scalable analysis and network-based insights: perform pairwise comparisons of the embeddings of n-grams from two texts and average their results as the overall intertextuality. Validation on four texts with known degrees of intertextuality, alongside a scalability test on 267 diverse texts, demonstrates the method's effectiveness and efficiency. Network analysis further reveals centrality and community structures, affirming the approach's success in capturing and quantifying intertextual relationships.
format Preprint
id arxiv_https___arxiv_org_abs_2509_06637
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Modelling Intertextuality with N-gram Embeddings
Xing, Yi
Computation and Language
Intertextuality is a central tenet in literary studies. It refers to the intricate links between literary texts that are created by various types of references. This paper proposes a new quantitative model of intertextuality to enable scalable analysis and network-based insights: perform pairwise comparisons of the embeddings of n-grams from two texts and average their results as the overall intertextuality. Validation on four texts with known degrees of intertextuality, alongside a scalability test on 267 diverse texts, demonstrates the method's effectiveness and efficiency. Network analysis further reveals centrality and community structures, affirming the approach's success in capturing and quantifying intertextual relationships.
title Modelling Intertextuality with N-gram Embeddings
topic Computation and Language
url https://arxiv.org/abs/2509.06637