Locating the Leading Edge of Cultural Change
This research addresses the problem of measuring cultural change for social scientists and digital humanities researchers, but it is incremental as it compares existing methods without introducing new ones.
The study investigated which textual similarity measures best align with social evidence of cultural change across three corpora, finding that works by highly-cited and younger authors are consistently ahead of the curve, with the top quartile of passages showing the strongest alignment.
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.