“I Am Too Old For This Style!” A Stylometric Benchmark of Age Effecton Authorship Attribution

Can age act as a significant factor in determining authorship? While writers’ styles are known to measurably evolve over time, most computational pipelines still treat them as time-invariant. Building on recent work that tracks idiolectal change in several literary traditions, we introduce the first controlled benchmark that quantifies how both the magnitude and the direction of temporal distance affect attribution. A diachronic corpus of French novelists is sampled at bidirectional gaps of ±1, ±5, ±10, and ±15 years. Verification is then tested with a generative Bootstrap Distance Impostors (BDI) model and a discriminative linear Support Vector Machine (SVM). Results reveal a near-linear loss of confidence as the gap widens, but –critically– also show a systematic directional asymmetry: late-career texts remain recognisable when compared with early-career references, whereas early texts are markedly harder to verify against late ones, suggesting a cumulative rather than a substitutive evolution. The pattern persists under random-pair controls, confirming that it is not a sampling artefact. All code, data, and evaluation scripts are released to encourage further research on temporally robust authorship analysis and to quantify both the dynamics and amplitude of idiolectal change over time.

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Publication Details

Published
2025-11-17
DOI
https://doi.org/10.63744/by09x5zx3ywx
Citations
1
Primary Topic
Authorship Attribution and Profiling
Type
article
Field-Weighted Citation Impact
4.74
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article

“I Am Too Old For This Style!” A Stylometric Benchmark of Age Effecton Authorship Attribution

Florian Cafiero, Thibault Clérice, Simon Gabay, Lucence Ing
1 citations
Authorship Attribution and Profiling
4.74
article

“I Am Too Old For This Style!” A Stylometric Benchmark of Age Effecton Authorship Attribution

Florian Cafiero, Thibault Clérice, Simon Gabay, Lucence Ing
article en
1 citations

Abstract

Can age act as a significant factor in determining authorship? While writers’ styles are known to measurably evolve over time, most computational pipelines still treat them as time-invariant. Building on recent work that tracks idiolectal change in several literary traditions, we introduce the first controlled benchmark that quantifies how both the magnitude and the direction of temporal distance affect attribution. A diachronic corpus of French novelists is sampled at bidirectional gaps of ±1, ±5, ±10, and ±15 years. Verification is then tested with a generative Bootstrap Distance Impostors (BDI) model and a discriminative linear Support Vector Machine (SVM). Results reveal a near-linear loss of confidence as the gap widens, but –critically– also show a systematic directional asymmetry: late-career texts remain recognisable when compared with early-career references, whereas early texts are markedly harder to verify against late ones, suggesting a cumulative rather than a substitutive evolution. The pattern persists under random-pair controls, confirming that it is not a sampling artefact. All code, data, and evaluation scripts are released to encourage further research on temporally robust authorship analysis and to quantify both the dynamics and amplitude of idiolectal change over time.

University of Geneva (CH)
Openalex Percentile: Top 5%
Authorship Attribution and Profiling
4.74
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