Locating the Leading Edge of Cultural Change

November 22, 2024 ยท Declared Dead ยท ๐Ÿ› Workshop on Computational Humanities Research

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Authors Sarah Griebel, Becca Cohen, Lucian Li, Jaihyun Park, Jiayu Liu, Jana Perkins, Ted Underwood arXiv ID 2411.15068 Category cs.CL: Computation & Language Citations 3 Venue Workshop on Computational Humanities Research Last Checked 5 months ago
Abstract
Measures of textual similarity and divergence are increasingly used to study cultural change. But which measures align, in practice, with social evidence about change? We apply three different representations of text (topic models, document embeddings, and word-level perplexity) to three different corpora (literary studies, economics, and fiction). In every case, works by highly-cited authors and younger authors are textually ahead of the curve. We don't find clear evidence that one representation of text is to be preferred over the others. But alignment with social evidence is strongest when texts are represented through the top quartile of passages, suggesting that a text's impact may depend more on its most forward-looking moments than on sustaining a high level of innovation throughout.
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