2020/08/06 by Jake Ryland Williams, Diana Solano-Oropeza, Williams, Jake Ryland +3
Computer Science · Physics and Astronomy · #Computation and Language (cs.CL) #Computers and Society (cs.CY) #FOS: Computer and information sciences #FOS: Physical sciences #Physics and Society (physics.soc-ph) #cs.CL #cs.CY #physics.soc-ph
paper · pdf · doi:10.48550/arxiv.2008.02885
arxiv created 2020/08/06 · arxiv updated 2020/08/10
We provide a general analytic solution to Herbert Simon's 1955 model for time-evolving novelty functions. This has far-reaching consequences: Simon's is a pre-cursor model for Barabasi's 1999 preferential attachment model for growing social networks, and our general abstraction of it more considers attachment to be a form of link selection. We show that any system which can be modeled as instances of types---i.e., occurrence data (frequencies)---can be generatively modeled (and simulated) from a distributional perspective with an exceptionally high-degree of accuracy.