This website contains interactive demonstrations intended to supplement the book, Introduction to Mathematical Sociology.

	ABOUT CDF These demonstrations are in Wolfram's Computable Document Format (CDF). These files can be either opened in your browser or downloaded for viewing after installing Wolfram's Free CDF plugin. Get the plugin!			ABOUT THE BOOK This textbook covers a wide range of topics, ranging from social networks, Markov processes, demography, and game theory. It is available from Princeton University Press. Website			DYNAMIC CONTENT Some demonstrations contain dynamic content. The user may receive an alert concerning a potential security issue. However, all of  the demonstrations on this webpage are completely safe. To proceed, click ENABLE DYNAMICS.

	CHAPTER 1 INTRODUCTION			Schelling's Model of Residential Segregation BY PHILIP S LU Wolfram: Link A re-creation of Thomas Schelling's original threshold model of residential segregation.			Simulated Epidemics BY PHILLIP BONACICH CDF: SimulatedEpidemics.cdf Explore how the density and size of a network affects the simulated growth of an infectious disease.
	CHAPTER 2 SETS			Boolean Algebra BY PHILLIP BONACICH CDF: BooleanAlgebra.cdf Use homomorphisms to analyze social group memberships			Set Intersection and Union BY PHILLIP BONACICH CDF: SetIntersectionandUnion.cdf This demonstration selects two randomly selected subsets of the alphabet and shows their intersection, union, and set differences.
				Venn Diagrams BY GEORGE BECK AND LIZ KENT Wolfram: Link Visualize the complete 127 nonempty unions and intersections of three sets, A, B, and C through Venn Diagrams
	CHAPTER 3 PROBABILITY			The Binomial Fit BY PHILIP S LU CDF: BinomialFit.cdf Explore the binomial distribution by fitting a curve to a randomly generated distribution. Adjust the n and p values and see how close you can come!			Convergence of Proportions BY PHILLIP BONACICH CDF: Convergence.nbp This demonstration shows that while the proportion of coin flips approaches the probability in the long run, the difference between the number of heads and expected number increases in the long run.
	CHAPTER 4 RELATIONS			Transitivity Game BY PHILIP S LU CDF: TransitivityGame.cdf These intransitive networks need your help! Try to achieve transitive closure with the fewest possible arc additions.			Relations Mini Quiz BY PHILIP S LU CDF: RelationsMiniQuiz.cdf Practice reflexitivity, symmetry, and transitivity with this mini quiz demonstration.
	CHAPTER 6 WEAK TIES			Finding Bridges BY PHILLIP BONACICH Wolfram: Link This demonstration will help you discern bridges from local bridges. Generate random networks of different sizes and density and challenge yourself to correctly categorizing each edge.			Random Graphs BY STEPHEN WOLFRAM Wolfram: Link Generate an array of random graphs and familiarize yourself with the qualitative and quantitative similarities.
	CHAPTER 7 MATRICES			Graphs from Matrices BY GEORGE BECK Wolfram: Link Each square matrix can correspond to a graph. Design a zero-one matrix and see the resulting network structure based on your matrix.
	CHAPTER 8 ADDING AND MULTIPLYING MATRICES			Matrix Multiplication BY ABBY BROWN Wolfram: Link Learning to multiply matrices? This demonstration helps you visualize the row and column operations that result in a matrix product.			Matrix Powers BY PHILLIP BONACICH CDF: MatrixPowers.cdf Generate a random network of your desired density and observe the relationship between walks and matrix powers.
	CHAPTER 9 CLIQUES AND OTHER GROUPS			Finding Cliques BY PHILLIP BONACICH Wolfram: Link This demonstration will locate n-cliques and k-plexes in randomly generated networks. Vary n and k and observe how strict or lenient each group definition is.			Community Structure BY PHILLIP BONACICH CDF: CommunityStructure.cdf Explore how the community structure algorithm assigns group membership in a network. Unlike other group definitions, community structure partitions the networks, so each vertex belongs to one and only one group.
	CHAPTER 10 CENTRALITY			Network Centrality BY PHILLIP BONACICH CDF: MeasureCentrality.cdf Generate random networks of different sizes and densities and explore the various aspects of centrality, represented by node size.			Centrality Game BY PHILIP S LU CDF: CentralityGame.cdf Centrality measures can be independent. Challenge yourself by designing a network where the top vertex is the most central under one measure, but near the bottom under another.
	CHAPTER 11 SMALL WORLD NETWORKS			Small World Networks: Lattice Model BY FELIPE DIMER DE OLIVEIRA Wolfram: Link Generate small-world networks based on random rewirings of a circular lattice.
	CHAPTER 12 SCALE-FREE NETWORKS			Contagion in Random and Scale-Free Networks BY PHILLIP BONACICH Wolfram: Link This demonstration compares the spread of an epidemic in random and scale-free networks of identical densities with and without inoculation of the most central 10% of the nodes.			Attack in Random and Scale-Free Networks BY PHILIP S LU CDF: Attack.cdf Explore how random and scale-free networks with the same density hold up against random failure and calculated attack. Multiple methods are offered to measure damage.
				Zipf's Law BY GIOVANNA RODA Wolfram: Link Power-laws are everywhere. This demonstration highlights the prevalence of the distribution in important political documents.
	CHAPTER 13 BALANCE THEORY			Triad Census on Random Graphs BY PHILIP S LU Wolfram: Link This Demonstration illustrates the expected frequencies in which these triads occur in random graphs of varying density.
	CHAPTER 14 MARKOV CHAINS			Transition Matrices for Markov Chains BY PHILLIP BONACICH Wolfram: Link Create your own Markov matrix and explore the equilibria in the matrix after a set number of transitions.
	CHAPTER 15 DEMOGRAPHY			Population Projection Using Leslie Matrices BY PHILIP S LU CDF: PopProjection.cdf Expose an initial population to death and birth rates and observe how the population changes over time, eventually approaching equilibrium. View the population as both a graph and a Leslie Matrix.
	CHAPTER 16 EVOLUTIONARY GAME THEORY			Evolutionary Prisoner's Dilemma Tournament BY PHILLIP BONACICH CDF: PDTournament.cdf Vary an initial population of strategies and let them compete in a 100-round PD tournament. Strategies reproduce themselves based on their payoff in the previous set of rounds. Learn how the effectiveness of a strategy is dependent on the composition of other strategies.			Nash Equilibrium in 2x2 Mixed Extended Games BY VALERIU UNGUREANU Wolfram: Link Adjust payoffs in a 2x2 matrix, and observe how it affects the set of Nash Equilibria.
	CHAPTER 17 POWER AND COOPERATIVE GAMES			Exchange Networks BY PHILLIP BONACICH Wolfram: Link Explore a simulation of behavior and development of power differences in negatively connected exchange networks. Observe how network position affects payoffs in repeated rounds of bargaining over 24 points.
	CHAPTER 18 COMPLEXITY AND CHAOS			Classic Logistic Map BY ROBERT M LURIE Wolfram: Link Use the classic logistic map to explore the properties of chaos dynamics.			Amaral-Meyer BY PHILLIP BONACICH CDF: AmaralMeyer.cdf Explore the Amaral-Meyer model of mass extinctions of species.
				Sand Pile BY PHILLIP BONACICH CDF: Sandpile.cdf An implementation of Per Bak's sandpile avalanche model. Find out which properties of the Sand Pile model generate a power-law distribution.			Pareto Distribution Comparison BY PHILLIP BONACICH CDF: ParetoCompare.cdf Compare the Pareto Distribution against three other distributions by looking at the differences in tail properties.
				Logistic Sequence Sensitivity BY PHILLIP BONACICH CDF: LogisticSensitivity.cdf This demonstration illustrates how sensitive the logistic sequence x(T+1) = \[Mu]x(T)(1-x(T) to small changes \[CapitalDelta] in starting values x(0) for values of \[Mu] in the appropriate range.