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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.22196 |
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| _version_ | 1866910062344142848 |
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| author | Wang, Qizhi |
| author_facet | Wang, Qizhi |
| contents | Digital-humanities work on semantic shift often alternates between handcrafted close readings and opaque embedding machinery. We present a reproducible expert-system style pipeline that quantifies lexical drift and its instability in the Old Bailey Corpus (1674-1913), coupling interpretable trajectories with legally meaningful axes. We bin proceedings by decade with dynamic merging for low-resource slices, train skip-gram embeddings, align spaces through orthogonal Procrustes to a 1900s anchor, and measure both geometric displacement and neighborhood turnover. We add split-half baselines and seed-sensitivity checks to separate within-bin instability from temporal change. Three visual analytics outputs (drift magnitudes, semantic trajectories, and movement along a mercy-versus-retribution axis) expose how justice, crime, poverty, and insanity evolve with penal reforms, transportation debates, and Victorian moral politics. The pipeline is implemented as auditable scripts so results can be reproduced in other historical corpora. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_22196 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | AETAS: Analysis of Evolving Temporal Affect and Semantics for Legal History Wang, Qizhi Digital Libraries Computers and Society Machine Learning 68T50 (Primary) 91F20, 62H25 (Secondary) I.2.7; J.5; I.2.1; K.4.1 Digital-humanities work on semantic shift often alternates between handcrafted close readings and opaque embedding machinery. We present a reproducible expert-system style pipeline that quantifies lexical drift and its instability in the Old Bailey Corpus (1674-1913), coupling interpretable trajectories with legally meaningful axes. We bin proceedings by decade with dynamic merging for low-resource slices, train skip-gram embeddings, align spaces through orthogonal Procrustes to a 1900s anchor, and measure both geometric displacement and neighborhood turnover. We add split-half baselines and seed-sensitivity checks to separate within-bin instability from temporal change. Three visual analytics outputs (drift magnitudes, semantic trajectories, and movement along a mercy-versus-retribution axis) expose how justice, crime, poverty, and insanity evolve with penal reforms, transportation debates, and Victorian moral politics. The pipeline is implemented as auditable scripts so results can be reproduced in other historical corpora. |
| title | AETAS: Analysis of Evolving Temporal Affect and Semantics for Legal History |
| topic | Digital Libraries Computers and Society Machine Learning 68T50 (Primary) 91F20, 62H25 (Secondary) I.2.7; J.5; I.2.1; K.4.1 |
| url | https://arxiv.org/abs/2512.22196 |