# Computational Analysis of Semantic Connections Between Herman Melville Reading and Writing

arXiv: https://arxiv.org/abs/2603.14674 · HTML: https://mlsanity.com/paper/2603.14674/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 26 references that are in the map.
- First posted on arXiv 15 Mar 2026.

## Builds on (most cited first, 3 of 3)

- [BERTScore: Evaluating Text Generation with BERT](https://mlsanity.com/paper/1904.09675/) (2019)
- [GLaM: Fine-Tuning Large Language Models for Domain Knowledge Graph Alignment via Neighborhood Partitioning and Generative Subgraph Encoding](https://mlsanity.com/paper/2402.06764/) (2024)
- [BERTScoreVisualizer: A Web Tool for Understanding Simplified Text Evaluation with BERTScore](https://mlsanity.com/paper/2409.17160/) (2024)

## Abstract (arXiv)

This study investigates the potential influence of Herman Melville reading on his own writings through computational semantic similarity analysis. Using documented records of books known to have been owned or read by Melville, we compare selected passages from his works with texts from his library. The methodology involves segmenting texts at both sentence level and non-overlapping 5-gram level, followed by similarity computation using BERTScore. Rather than applying fixed thresholds to determine reuse, we interpret precision, recall, and F1 scores as indicators of possible semantic alignment that may suggest literary influence. Experimental results demonstrate that the approach successfully captures expert-identified instances of similarity and highlights additional passages warranting further qualitative examination. The findings suggest that semantic similarity methods provide a useful computational framework for supporting source and influence studies in literary scholarship.