How predictable : patterns of human economic behavior in the wild

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 40-41).Shopping is driven by needs (to eat, to socialize, to work), but it is also a driver of where we go. I examine the transaction records of 80 million customers and find that while our economic choices predict mobility patterns overall, at the small scale we transact unpredictably. In particular, we bundle together multiple store visits, and interleave the order in which we frequent those stores. Individual predictability also varies with income level. I end with a description of how merchant composition emerges in US cities, as seen through the lens of credit card swipes.by Katherine (Coco) Krumme.S.M

Modeling rates of change in individuals and populations

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 81-84).This thesis develops methodologies to measure rates of change in individual human behavior, and to capture statistical regularities in change at the population level, in three pieces: i) a model of individual rate of change as a function of search and finite resources, ii) a structural model of population level change in urban economies, and iii) a statistical test for the deviation from a null model of rank chum of items in a distribution. First, two new measures of human mobility and search behavior are defined: exploration and turnover. Exploration is the rate at which new locations are searched by an individual, and turnover is the rate at which his portfolio of visited locations changes. Contrary to expectation, exploration is open-ended for almost all individuals. A present a baseline model is developed for change (or churn) in human systems, relating rate of exploration to rate of turnover. This model recasts the neutral or random drift mechanism for population-level behavior, and distinguishes exploration due to optimization, from exploration due to a taste for variety. A relationship between the latter and income is shown. Second, there exist regular relationships in the economic structure of cities, with important similarities to ecosystems. Third, a new statistical test is developed for distinguishing random from directed churn in rank ordered systems. With a better understanding of rates of change, we can better predict where people will go, the probability of their meeting, and the expected change of a system over time. More broadly, these findings propose a new way of thinking about individual and system-level behavior: as characterized by predictable rates of innovation and change.by Coco Krumme.Ph.D

Lending behavior and community structure in an online peer-to-peer economic network

Increasingly, economic transactions are taking place over social networks. We study the static and dynamic characteristics of a peer-to-peer lending network through 350,000 loan listings and accompanying member profiles from the online marketplace Prosper.com. Our results imply that social factors such as participation in affinity groups and descriptive profile text are correlated with financial indicators; at the same time, we see evidence of suboptimal lending decisions, minimal learning, and herding behavior in the network. We discuss implications and suggest possible improvements to the online peer-to-peer lending model