Sub-exponential Growth Dynamics in Complex Systems: A Piecewise Power-Law Model for the Diffusion of New Words and Names
arXiv:2511.04106v5 Announce Type: replace-cross Abstract: The diffusion of ideas and language in society has conventionally been described by S-shaped models, such as the logistic curve. However, the role of sub-exponential growth -- a slower-than-exponential pattern known in epidemiology -- has been largely overlooked in broader social phenomena. Here, we present a piecewise power-law model to characterize complex growth curves with a few parameters. We systematically analyzed a large-scale dataset of approximately one billion Japanese blog articles linked to Wikipedia vocabulary, and observe
This paper offers a new model for understanding language diffusion, building on established concepts in complex systems and epidemiology.
While interesting from an academic perspective, it doesn't immediately alter strategic planning or current market dynamics.
This research refines our understanding of how language and ideas spread, which could have long-term implications for fields like computational linguistics and sociology.
Improved models for tracking linguistic and conceptual spread in large datasets.
Better predictive capabilities for the emergence and decline of cultural trends or technological terms.
Enhanced AI systems for natural language processing and cultural trend analysis, if the model proves robust and generalizable.
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