# Quantitative Intertextuality from the Digital Humanities Perspective: A Survey

arXiv: https://arxiv.org/abs/2510.27045 · HTML: https://mlsanity.com/paper/2510.27045/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 70 references that are in the map.
- First posted on arXiv 30 Oct 2025.

## Builds on (most cited first, 9 of 9)

- [Billion-scale similarity search with GPUs](https://mlsanity.com/paper/1702.08734/) (2017)
- [Machine-assisted quantitizing designs: augmenting humanities and social sciences with artificial intelligence](https://mlsanity.com/paper/2309.14379/) (2023)
- [On the Feasibility of Automated Detection of Allusive Text Reuse](https://mlsanity.com/paper/1905.02973/) (2019)
- [Introducing Rhetorical Parallelism Detection: A New Task with Datasets, Metrics, and Baselines](https://mlsanity.com/paper/2312.00100/) (2023)
- [Identification of Parallel Passages Across a Large Hebrew/Aramaic Corpus](https://mlsanity.com/paper/1602.08715/) (2016)
- [Patterns of Text Reuse in a Scientific Corpus](https://mlsanity.com/paper/1412.2716/) (2014)
- [Investigating Expert-in-the-Loop LLM Discourse Patterns for Ancient Intertextual Analysis](https://mlsanity.com/paper/2409.01882/) (2024)
- [Automatic Detection of Reuses and Citations in Literary Texts](https://mlsanity.com/paper/1404.2997/) (2014)
- [The Cultural Evolution of National Constitutions](https://mlsanity.com/paper/1711.06899/) (2017)

## Built on by (most cited first, 2 of 2)

- [Extending AI for Research to the Humanities: A Multi-Agent Framework for Evidence-Grounded Scholarship](https://mlsanity.com/paper/2605.30947/) (2026)
- [Retrieving Biblical Intertextual References in Karen Blixen's Seven Gothic Tales](https://mlsanity.com/paper/2609.35765/) (2026)

## Abstract (arXiv)

The connection between texts is referred to as intertextuality in literary theory, which served as an important theoretical basis in many digital humanities studies. Over the past decade, advancements in natural language processing have ushered intertextuality studies into the quantitative age. Large-scale intertextuality research based on cutting-edge methods has continuously emerged. This paper provides a roadmap for quantitative intertextuality studies, summarizing their data, methods, and applications. Drawing on data from multiple languages and topics, this survey reviews methods from statistics to deep learning. It also summarizes their applications in humanities and social sciences research and the associated platform tools. Driven by advances in computer technology, more precise, diverse, and large-scale intertext studies can be anticipated. Intertextuality holds promise for broader application in interdisciplinary research bridging AI and the humanities.