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Abstract
This thesis is a case study attempting to solve the question of how and why specific mathematical knowledge may rapidly spread in the modern academic system. In post-war academia, large-scale revolutions in pure mathematics appear to be unusual. However, the phenomena of mass innovation and dissemination in the field of applied mathematics can be quite prevalent. Using historical text library research and publication data analysis, this thesis examines the sudden spread of the sampling method Markov chain Monte Carlo (MCMC) in the 1990s. What happened to MCMC in that decade demonstrates that the development and transfer of mathematical knowledge can be a complex, multi-faceted process in which conferences, computing power, software, and "explaining" publications all played their roles. The analysis shows that there is no one dominant force in the spread of such a technique. Spread always depends on the contingent interaction of various forces. Detailed discussion of the example allows us both to list those forces and to show the various ways they interact.