Visual Genealogy of Typography: Computational Provenance-Based Analysis of Typeface Evolution

Hendi Thamrin; Shierly Everlin; Puguh Hiskiawan; Valentina Valentina; Angelyn Stevanie Lee; Paskalis Peter

doi:10.30871/jaic.v10i5.14211

Authors

Hendi Thamrin Universitas Bunda Mulia
Shierly Everlin Universitas Bunda Mulia
Puguh Hiskiawan Universitas Bunda Mulia
Valentina Valentina Universitas Bunda Mulia
Angelyn Stevanie Lee Universitas Bunda Mulia
Paskalis Peter Universitas Bunda Mulia

DOI:

https://doi.org/10.30871/jaic.v10i5.14211

Keywords:

Typography, Visual Geanology, visual humanities, computational typography, corpus composition

Abstract

Computational analyses of typographic corpora increasingly produce similarity networks that are read as evidence of stylistic descent, yet no study has tested what such morphology-based genealogical inference can legitimately support; this study provides that test. Using a quantitative re-analysis design, we took an existing dataset of 33 typeface families, with 1,188 glyph images and eleven morphological descriptors, and added an auditable provenance layer recording designer, foundry, dates, revival status and script category. Five diagnostics were applied at family level: chronological correspondence, script-category composition tested with Fisher's exact test and the adjusted Rand index, multiple-comparison correction, classification stability, and a comparison of documented derivations with undocumented pairs. Eleven of sixteen families designated historical carry design dates after the declared period of 1450–1899, and no rendered file belongs to it. The era groups differ in serif composition before any morphology is measured (50.0% versus 5.9%, p = 0.0066); recovered clusters align with script category rather than period (adjusted Rand index 0.534 versus 0.090) under all corpus configurations examined; and among sans-serif families no era difference is detected on the descriptors testable (all p > 0.70). Only two of eleven descriptor differences survive family-wise correction, a headline accuracy of 75.8% falls to a mean near 0.68 under repeated validation against a 51.5% baseline, and undocumented pairs reach similarities above documented derivations. Morphological similarity therefore measures formal affinity conditioned on corpus composition, a necessary but not sufficient basis for claims of descent. A five-point reporting protocol for computational typography is proposed.

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