mlsanityData to 14 Oct 2026

Critical biblical studies via word frequency analysis: unveiling text authorship

arXiv 2410.19883 ↗First posted 24 Oct 2024cs.CL cs.LGcited by 2

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Abstract (arXiv)

The Bible, a product of an extensive and intricate process of oral-written transmission spanning centuries, obscures the contours of its earlier recensions. Debate rages over determining the existing layers and identifying the date of composition and historical background of the biblical texts. Traditional manual methodologies have grappled with authorship challenges through scrupulous textual criticism, employing linguistic, stylistic, inner-biblical, and historical criteria. Despite recent progress in computer-assisted analysis, many patterns still need to be uncovered in Biblical Texts. In this study, we address the question of authorship of biblical texts by employing statistical analysis to the frequency of words using a method that is particularly sensitive to deviations in frequencies associated with a few words out of potentially many. We aim to differentiate between three distinct authors across numerous chapters spanning the first nine books of the Bible. In particular, we examine 50 chapters labeled according to biblical exegesis considerations into three corpora (D, DtrH, and P). Without prior assumptions about author identity, our approach leverages subtle differences in word frequencies to distinguish among the three corpora and identify author-dependent linguistic properties. Our analysis indicates that the first two authors (D and DtrH) are much more closely related compared to P, a fact that aligns with expert assessments. Additionally, we attain high accuracy in attributing authorship by evaluating the similarity of each chapter with the reference corpora. This study sheds new light on the authorship of biblical texts by providing interpretable, statistically significant evidence that there are different linguistic characteristics of biblical authors and that these differences can be identified.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 4 of its 86 references that are in the map. First posted on arXiv 24 Oct 2024.

Builds on

4 of 86 references.

References · 4

  1. 2019Universal Dependency Parsing from Scratchcited by 46
  2. 2019What's Wrong with Hebrew NLP? And How to Make it Rightcited by 16
  3. 2019Higher Criticism for Discriminating Word-Frequency Tables and Testing Authorshipcited by 3
  4. 2023A Statistical Exploration of Text Partition Into Constituents: The Case of the Priestly Source in the Books of Genesis and Exoduscited by 3

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Citing papers per year: 2024: 1; 2025: 1.

2 papers.