用几何机制解释语言中齐普夫定律的成因，无需依赖语义。
Zipf Distributions from Two-Stage Symbolic Processes: Stability Under Stochastic Lexical Filtering
- 基于符号组合的双阶段模型生成词长几何分布
- 词频排名呈幂律分布，由字母表大小和空符概率决定
- 模拟结果匹配英俄语及混合文本数据，适合复杂系统研究者
语言中的齐普夫定律尚无定论，跨学科争论不断。本研究通过无语言元素的几何机制解释齐普夫型行为。全组合词模型（FCWM）从有限字母表生成单词，导致词长服从几何分布。相互作用的指数力产生幂律型频率排名曲线，其形式由字母表大小和空白符号概率决定。模拟结果支持理论预测，与英语、俄语及混合题材文本数据吻合。该符号模型表明，齐普夫型规律源于几何约束，而非交际效率。
原文摘要 · Abstract (English)
Zipf's law in language lacks a definitive origin, debated across fields. This study explains Zipf-like behavior using geometric mechanisms without linguistic elements. The Full Combinatorial Word Model (FCWM) forms words from a finite alphabet, generating a geometric distribution of word lengths. Interacting exponential forces yield a power-law rank-frequency curve, determined by alphabet size and blank symbol probability. Simulations support predictions, matching English, Russian, and mixed-genre data. The symbolic model suggests Zipf-type laws arise from geometric constraints, not communicative efficiency.
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