This thesis studies the relationship between people in a two good economy on a social network. Each person in the network is allotted a certain number of firewood and a certain number of candy bars. Each person tries to increase his or her happiness through trading. Each person in the network knows at least one other person in the network. The people in the network can trade with the people they know to increase their happiness. The goal of the thesis is to be able to predict how each person's happiness is affected, just by knowing who knows whom within the network. That is, is there a network importance metric that is a good predictor of happiness? The thesis presents many trading simulations with different networks, through a MATLAB code that was created using an agent-based model. The size of the network is varied through the experiments, and the probability that people know each other within the network is also varied. Data is collected from all the trading simulations in order to understand clearly what different factors affect the networks. Most importantly what affects happiness within the networks is studied. Three different standard measures of centrality are studied to determine which is the best indicator of happiness. The three centrality measures include: degree, clustering coefficients, and eigenvalue centrality. Throughout many different trading simulations, each person's centrality measurement is compared to his or her ending happiness, in order to determine which standard measure of centrality is the best predictor of happiness.

Library of Congress Subject Headings

Social networks--Mathematical models; Commerce--Mathematical models; Social exchange--Simulation methods; Multiagent systems; Game theory

Publication Date


Document Type


Department, Program, or Center

School of Mathematical Sciences (COS)


Brooks, Bernard


Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works. Physical copy available through RIT's The Wallace Library at: HM741 .L38 2012


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