Oracle Bone Inscriptions

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A01=Tingzhu Chen
ancient script analysis
Author_Tingzhu Chen
Category=CFF
Category=NHF
Category=NK
character frequency distribution
Chinese palaeography
Chinese Writing System
Compound Graphs
eq_bestseller
eq_dictionaries-language-reference
eq_history
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
forthcoming
glyph structure study
historical linguistics
Oracle Bone Inscriptions
quantitative analysis of early Chinese writing
writing system evolution

Product details

  • ISBN 9781041129356
  • Dimensions: 156 x 234mm
  • Publication Date: 28 Jul 2026
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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This book presents a systematic re-examination of the Oracle Bone Inscription writing system by integrating up-dated archaeological discoveries and scholarly advances, with the aim of illuminating new aspects of the early evolution of Chinese characters.
Building on this foundation, the study identifies variant character groups and tackles fundamental questions concerning the total reservoir of characters, thereby establishing a quantitative framework for further analysis. It outlines key structural features, such as the prevalence of monomeric glyphs and planar composition, and brings to light systemic properties including shallow structural hierarchy, positional flexibility coupled with spatial symmetry and limited functional diversity resulting from low graphic efficiency. Additionally, the work highlights the highly skewed distribution of character frequency, underscoring the primitive stage of the writing system.
This book will serve as an essential reference for scholars in the fields of paleography, Chinese historical linguistics and grammatology.

Tingzhu Chen is a professor at Shanghai Jiao Tong University. She is a leading expert in Oracle Bone Inscriptions (OBI) studies and has published numerous articles in this area. She currently directs the National Social Science Foundation of China (NSSFC) project, "Development of an Oracle Bone Inscriptions Dataset for Recognition Studies" (Grant No. 24Z300404220).

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