Beyond Zipf's law: Modeling the structure of human language
IFISC (CSIC-UIB) Instituto de Física Interdisciplinar y Sistemas Complejos（IFISC（西班牙国家研究委员会-巴利阿里群岛大学）跨学科物理与复杂系统研究所）；Indiana University（印第安纳大学）；ISI Foundation（ISI基金会）
M. Angeles Serrano, Alessandro Flammini, Filippo Menczer
Human language, the most powerful communication system in history, is closely associated with cognition. Written text is one of the fundamental manifestations of language, and the study of its universal regularities can give clues about how our brains process information and how we, as a society, organize and share it. Still, only classical patterns such as Zipf's law have been explored in depth. In contrast, other basic properties like the existence of bursts of rare words in specific documents, the topical organization of collections, or the sublinear growth of vocabulary size with the length of a document, have only been studied one by one and mainly applying heuristic methodologies rather than basic principles and general mechanisms. As a consequence, there is a lack of understanding of linguistic processes as complex emergent phenomena. Beyond Zipf's law for word frequencies, here we focus on Heaps' law, burstiness, and the topicality of document collections, which encode correlations within and across documents absent in random null models. We introduce and validate a generative model that explains the simultaneous emergence of all these patterns from simple rules. As a result, we find a connection between the bursty nature of rare words and the topical organization of texts and identify dynamic word ranking and memory across documents as key mechanisms explaining the non trivial organization of written text. Our research can have broad implications and practical applications in computer science, cognitive science, and linguistics.
On the class of coding optimality of human languages and the origins of Zipf's law
Quantitative, Mathematical and Computational Linguistics Research Group, Department of Computer Science, Universitat Politècnica de Catalunya, 08034 Barcelona, Catalonia (Spain)（计算机科学系量化、数学和计算语言学研究组，巴塞罗那理工大学，西班牙加泰罗尼亚地区08034）
Zipf's law in 50 languages: its structural pattern, linguistic interpretation, and cognitive motivation
Communication University of China（中国传媒大学）；Anhui Jianzhu University（安徽建筑大学）；Zhejiang University（浙江大学）；Ningbo Institute of Technology, Zhejiang University（浙江大学宁波理工学院）
Zipf's law for word frequencies: word forms versus lemmas in long texts
Centre de Recerca Matemàtica（数学研究中心）；Universitat Autònoma de Barcelona（巴塞罗那自治大学）；Universitat Pompeu Fabra（庞培法布拉大学）；Universitat Politècnica de Catalunya（加泰罗尼亚理工大学）
Pre-trained Models Perform the Best When Token Distributions Follow Zipf's Law
School of Mathematical Sciences, Peking University（北京大学数学科学学院）；Department of Computer Science and Engineering, University of Notre Dame（圣母大学计算机科学与工程系）；College of Computer Science, Nankai University（南开大学计算机学院）
Empirical Analysis of Zipf's Law, Power Law, and Lognormal Distributions in Medical Discharge Reports
Australian Institute of Health Innovation, Macquarie University（麦考瑞大学澳大利亚健康创新研究所）；Centre for Big Data Research in Health, UNSW（新南威尔士大学健康大数据研究中心）；University of Sydney（悉尼大学）；University of Technology Sydney（悉尼科技大学）；Swinburne University of Technology（斯威本科技大学）
G. K.齐普夫对词频与其他词的特征之间关系的研究导致了各种语言学规律的制定。最流行的是Zipf的词频定律。在这里，我们集中在两个法律，已经研究得不太深入：意义频率的法律，即更频繁的词是多义的趋势，和缩写的法律，即更频繁的词是更短的趋势。在以前的工作中，我们测试了这些Zipfian定律对英语的鲁棒性，粗略地测量了字长的字符数，并区分了成人和儿童的语音。在本文中，我们将我们的研究扩展到其他语言（荷兰语和西班牙语），并介绍了两个额外的长度措施：音节长度和音素长度。相关分析表明，意义频率规律和缩略语规律在所有被分析的语言中总体上是一致的。
A Zipf's Law-based Text Generation Approach for Addressing Imbalance in Entity Extraction
School of Information Resource Management, Renmin University of China（中国人民大学信息资源管理学院）；College of Information Science and Technology, Beijing University of Chemical Technology（北京化工大学信息科学与技术学院）
A statistical test for correspondence of texts to the Zipf-Mandelbrot law
Novosibirsk State Technical University（新西伯利亚国立技术大学）；Novosibirsk State University（新西伯利亚国立大学）；Nankai University（南开大学）；Sobolev Institute of Mathematics（索博列夫数学研究所）
Laboratoire de Physique Statistique et Systèmes Complexes, ISMANS（ISMANS统计物理与复杂系统实验室）；Hua-Zhong Normal University（华中师范大学）；Université du Maine（曼恩大学）；Yerevan Physics Institute（埃里温物理研究所）；University of Heilongjiang（黑龙江大学）
