Complexity Characteristics of Natural Language

Dear Colleagues,

The science of complexity is an interdisciplinary approach to seeking answers to the question of the principles by which nature operates when composing basic elements of matter and energy into dynamic patterns and structures that propagate throughout the entire hierarchy of scales in the universe. The associated extraordinary emergent phenomenon, such as the syntactically organized natural language, superbly reflects these patterns and structures, expressed in its great ability to encode and transmit information about them and between them. Therefore, it is highly reasonable to expect that natural language—spontaneously created by nature—best mirrors the laws of nature and carries within it the essence of complexity. Indeed, the complex systems methodology, which includes time series analysis, various variants of the concept of entropy, scale-free laws, fractals and multifractals, and, of course, complex networks, proves to be very effective in quantifying universal as well as system-specific linguistic characteristics. For the most up-to-date related review, see “Complex Systems Approach to Natural Language” at https://doi.org/10.1016/j.physrep.2023.12.002.It can also be added that, from the perspective of human communities, natural language is a fundamental factor shaping the development of civilization in all its aspects. Nowadays, quantitative studies on language and the need to understand the principles governing it are also gaining particular importance in the context of products such as ChatGPT from the family of language models developed by OpenAI. It is expected, in particular, that these studies will contribute to further significant improvements and optimization of relevant procedures, which, as is widely known, is highly desirable in this context. 

We thus invite researchers representing various disciplines, including language studies, computer studies, physics, mathematics, data science, and others, to submit their original papers reporting studies—empirical as well as modeling—whose results may contribute to a better understanding of the origins of natural language and the principles of its organization. It is obvious that such research should include various complementary representations of natural language belonging to different families, not only the major ones such as Indo-European and Sino-Tibetan but also those in less common use.

Prof. Dr. Stanisław Drożdż
Dr. Jarosław Kwapień
Dr. Tomasz Stanisz
Guest Editors

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• natural language
• complexity
• hierarchical organization
• long-range correlations
• time series analysis
• scaling laws
• multifractals
• complex networks
• large language models
• natural language generation