Journal of Language Service Studies

Quantifying Punctuation Patterns in Chinese Language for Language Service Applications

DOI:

https://doi.org/10.63385/jlss.v2i1.100997

Keywords:

Chinese Punctuation,Quantitative Linguistics,Language Services,Zipf’s Law,Weibull Distribution,Machine Translation,Multifractality,Complex Networks

Abstract

Punctuation is commonly treated as an auxiliary feature of writing, yet it encodes crucial information about syntactic organization, discourse rhythm, and narrative structure. In modern Chinese, punctuation forms a hybrid system shaped by traditional practices and imported Western conventions, making it especially relevant for quantitative analysis and language service applications. This review presents a concise summary of recent findings of a systematic investigation of punctuation in modern Chinese prose, with comparison to English translations, using a unified framework of the Zipf–Mandelbrot frequency statistics, the discrete Weibull spacing distributions, word-adjacency network analysis, and multifractal time-series methods. If punctuation marks are treated along with regular words as full linguistic tokens, Chinese punctuation follows robust power-law frequency scaling and its inclusion improves Zipfian behaviour. Inter-punctuation distances exhibit near-exponential Weibull distributions, reflecting frequent and regular segmentation, while English displays heavier tails indicative of longer punctuation-free spans. Network analyses reveal that punctuation functions as a central organizing hub in Chinese texts, reducing average shortest-path lengths and increasing clustering, whereas English networks are more lexically centered. Multifractal analysis further demonstrates that punctuation governs narrative dynamics across scales, with English translations exhibiting stronger multiscale variability. These results establish punctuation as a quantifiable structural signal rather than a peripheral orthographic feature and highlight its practical relevance for machine translation, speech technology, subtitling, accessibility services, and data-driven quality assurance.

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