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Statistical physics of complex substitutive systems

by Qing Jin

Institution: Northeastern University
Year: 2017
Keywords: complex network; complex substitutive system; complex system; statistical physics
Posted: 02/01/2018
Record ID: 2181230
Full text PDF: http://hdl.handle.net/2047/D20260325


Abstract

Diffusion processes are central to human interactions. Despite extensive studies that span multiple disciplines, our knowledge is limited to spreading processes in non-substitutive systems. Yet, a considerable number of ideas, products, and behaviors spread by substitution; to adopt a new one, agents must give up an existing one. This captures the spread of scientific constructs forcing scientists to choose, for example, a deterministic or probabilistic worldview, as well as the adoption of durable items, such as mobile phones, cars, or homes. In this dissertation, I develop a statistical physics framework to describe, quantify, and understand substitutive systems. By empirically exploring three collected high-resolution datasets pertaining to such systems, I build a mechanistic model describing substitutions, which not only analytically predicts the universal macroscopic phenomenon discovered in the collected datasets, but also accurately captures the trajectories of individual items in a complex substitutive system, demonstrating a high degree of regularity and universality in substitutive systems. I also discuss the origins and insights of the parameters in the substitution model and possible generalization form of the mathematical framework. The systematical study of substitutive systems presented in this dissertation could potentially guide the understanding and prediction of all spreading phenomena driven by substitutions, from electric cars to scientific paradigms, and from renewable energy to new healthy habits.

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