Mean-reverting self-excitation drives evolution: phylogenetic analysis of a literary genre, waka, with a neural language model

Abstract To elucidate the evolutionary dynamics of culture, we must address fundamental questions such as whether we can interpolate and extrapolate cultural evolution, whether the time series of cultural evolution is distinguishable from its reverse, what factors determine the direction of change,...

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Main Author: Takuma Tanaka
Format: Article
Language:English
Published: Springer Nature 2025-03-01
Series:Humanities & Social Sciences Communications
Online Access:https://doi.org/10.1057/s41599-025-04714-1
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author Takuma Tanaka
author_facet Takuma Tanaka
author_sort Takuma Tanaka
collection DOAJ
description Abstract To elucidate the evolutionary dynamics of culture, we must address fundamental questions such as whether we can interpolate and extrapolate cultural evolution, whether the time series of cultural evolution is distinguishable from its reverse, what factors determine the direction of change, and how the cultural influence of a creative work from the viewpoint of an instant is correlated with that from the viewpoint of a later instant. To answer these questions, the evolution of classical Japanese poetry, waka, specifically tanka, was investigated. Phylogenetic networks were constructed on the basis of the vector representation obtained using a neural language model. The parent–child relationship in the phylogenetic networks exhibited significant agreement with a previously established honkadori (allusive variation) phrase-borrowing relationship. The real phylogenetic networks were distinguishable from the time-reversed and shuffled ones. Two anthologies could be interpolated but not extrapolated. The number of children of a poem in the phylogenetic networks, the proxy variable of its cultural influence, evaluated at an instant, was positively correlated with that evaluated later. A poem selected for an authoritative anthology tended to have 10–50% more children than a similar but nonselected poem, implying the existence of the Matthew effect. A model with mean-reverting self-excitation replicated these results.
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spelling doaj-art-c4ea4bbaad9440eba3557b571265cfa82025-08-20T02:51:27ZengSpringer NatureHumanities & Social Sciences Communications2662-99922025-03-0112111010.1057/s41599-025-04714-1Mean-reverting self-excitation drives evolution: phylogenetic analysis of a literary genre, waka, with a neural language modelTakuma Tanaka0Graduate School of Data Science, Shiga UniversityAbstract To elucidate the evolutionary dynamics of culture, we must address fundamental questions such as whether we can interpolate and extrapolate cultural evolution, whether the time series of cultural evolution is distinguishable from its reverse, what factors determine the direction of change, and how the cultural influence of a creative work from the viewpoint of an instant is correlated with that from the viewpoint of a later instant. To answer these questions, the evolution of classical Japanese poetry, waka, specifically tanka, was investigated. Phylogenetic networks were constructed on the basis of the vector representation obtained using a neural language model. The parent–child relationship in the phylogenetic networks exhibited significant agreement with a previously established honkadori (allusive variation) phrase-borrowing relationship. The real phylogenetic networks were distinguishable from the time-reversed and shuffled ones. Two anthologies could be interpolated but not extrapolated. The number of children of a poem in the phylogenetic networks, the proxy variable of its cultural influence, evaluated at an instant, was positively correlated with that evaluated later. A poem selected for an authoritative anthology tended to have 10–50% more children than a similar but nonselected poem, implying the existence of the Matthew effect. A model with mean-reverting self-excitation replicated these results.https://doi.org/10.1057/s41599-025-04714-1
spellingShingle Takuma Tanaka
Mean-reverting self-excitation drives evolution: phylogenetic analysis of a literary genre, waka, with a neural language model
Humanities & Social Sciences Communications
title Mean-reverting self-excitation drives evolution: phylogenetic analysis of a literary genre, waka, with a neural language model
title_full Mean-reverting self-excitation drives evolution: phylogenetic analysis of a literary genre, waka, with a neural language model
title_fullStr Mean-reverting self-excitation drives evolution: phylogenetic analysis of a literary genre, waka, with a neural language model
title_full_unstemmed Mean-reverting self-excitation drives evolution: phylogenetic analysis of a literary genre, waka, with a neural language model
title_short Mean-reverting self-excitation drives evolution: phylogenetic analysis of a literary genre, waka, with a neural language model
title_sort mean reverting self excitation drives evolution phylogenetic analysis of a literary genre waka with a neural language model
url https://doi.org/10.1057/s41599-025-04714-1
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