Mathematical and Computational Study of Law and Society
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Law
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Abstract
This dissertation develops and applies mathematical and computational methods to examine law and society, including their interactions with technology. Following an introductory chapter, Chapter 2 proposes and analyzes a mathematical model that integrates complex contagion with payoff-biased imitation, offering a unified framework for understanding social learning processes. Chapter 3 employs a theoretical model to investigate whether and under what conditions institutions, which may not always reflect the interests of the population they serve, foster cooperation through wealth redistribution. Chapter 4 continues the theoretical analysis by shifting focus to reputation institutions that promote trust in markets, as exemplified by online transaction platforms that have become increasingly significant in our economy. Chapter 5 explores the nascent intersection of copyright law and generative AI, contributing to the development of methodologies for quantifying and strengthening copyright protection. Together, these chapters advance the frontiers of mathematical and computational approaches to the study of law and society.