arXiv Open Access 2024

Dynamic embedded topic models and change-point detection for exploring literary-historical hypotheses

Hale Sirin Tom Lippincott

Lihat Sumber

Abstrak

We present a novel combination of dynamic embedded topic models and change-point detection to explore diachronic change of lexical semantic modality in classical and early Christian Latin. We demonstrate several methods for finding and characterizing patterns in the output, and relating them to traditional scholarship in Comparative Literature and Classics. This simple approach to unsupervised models of semantic change can be applied to any suitable corpus, and we conclude with future directions and refinements aiming to allow noisier, less-curated materials to meet that threshold.

Topik & Kata Kunci

cs.CL

Penulis (2)

Hale Sirin

Tom Lippincott

Format Sitasi

APA MLA BibTeX

Sirin, H., Lippincott, T. (2024). Dynamic embedded topic models and change-point detection for exploring literary-historical hypotheses. https://arxiv.org/abs/2401.13905

Akses Cepat

Lihat di Sumber

Informasi Jurnal

Tahun Terbit: 2024
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓