Old Testament, New Tricks: Using Biblical Translation to Examine Word Sense and Popular Belief

This project presents a novel framework and empirical technique using digital tools and a small but highly-structured dataset--namely, 14 translations of the Old Testament--to analyze latent beliefs regarding beautiful objects across three broadly-defined populations: 16th century Great Britain, 20th century Germany, and the contemporary United States.

Abstract: One strand of recent research in digital humanities and computational linguistics uses digital tools to process the natural language of large available corpora like Google Ngram and Twitter. However, sample selection bias in the construction of those corpora frustrates inference about the societies and populations represented by each corpus. I present a novel framework and empirical technique using digital tools and a small but highly-structured dataset--namely, 14 translations of the Old Testament--that plausibly avoids these sample selection issues, and then presents a working example using this framework to analyze differences in latent beliefs regarding beautiful objects across three broadly-defined populations: 16th century Great Britain, 20th century Germany, and the contemporary United States. Biblical translations' substantial within- and between-translation word choice variation suggest that this corpus is capable of identifying multi-dimensional latent beliefs. I present evidence that these latent beliefs are well-defined across at least one population--the contemporary United States--with disparate groups having produced dissimilar text that is nevertheless shown to manifest highly similar latent aesthetic categories. I also present evidence of measured differences in latent aesthetic categories between the three studied populations. Future research will develop unsupervised latent models (e.g. topic models) to characterize the content of these similarities and differences across populations.

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