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Introduction to Mathematical Sociology


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Table of Contents

List of Figures ix List of Tables xiii Preface xv Chapter 1. Introduction 1 Epidemics 2 Residential Segregation 6 Exercises 11 Chapter 2. Set Theory and Mathematical Truth 12 Boolean Algebra and Overlapping Groups 19 Truth and Falsity in Mathematics 21 Exercises 23 Chapter 3. Probability: Pure and Applied 25 Example: Gambling 28 Two or More Events: Conditional Probabilities 29 Two or More Events: Independence 30 A Counting Rule: Permutations and Combinations 31 The Binomial Distribution 32 Exercises 36 Chapter 4. Relations and Functions 38 Symmetry 41 Reflexivity 43 Transitivity 44 Weak Orders-Power and Hierarchy 45 Equivalence Relations 46 Structural Equivalence 47 Transitive Closure: The Spread of Rumors and Diseases 49 Exercises 51 Chapter 5. Networks and Graphs 53 Exercises 59 Chapter 6. Weak Ties 61 Bridges 61 The Strength of Weak Ties 62 Exercises 66 Chapter 7. Vectors and Matrices 67 Sociometric Matrices 69 Probability Matrices 71 The Matrix, Transposed 72 Exercises 72 Chapter 8. Adding and Multiplying Matrices 74 Multiplication of Matrices 75 Multiplication of Adjacency Matrices 77 Locating Cliques 79 Exercises 82 Chapter 9. Cliques and Other Groups 84 Blocks 86 Exercises 87 Chapter 10. Centrality 89 Degree Centrality 93 Graph Center 93 Closeness Centrality 94 Eigenvector Centrality 95 Betweenness Centrality 96 Centralization 99 Exercises 101 Chapter 11. Small-World Networks 102 Short Network Distances 103 Social Clustering 105 The Small-World Network Model 111 Exercises 116 Chapter 12. Scale-Free Networks 117 Power-Law Distribution 118 Preferential Attachment 121 Network Damage and Scale-Free Networks 129 Disease Spread in Scale-Free Networks 134 Exercises 136 Chapter 13. Balance Theory 137 Classic Balance Theory 137 Structural Balance 145 Exercises 148 The Markov Assumption: History Does Not Matter 156 Transition Matrices and Equilibrium 157 Exercises 158 Chapter 15. Demography 161 Mortality 162 Life Expectancy 167 Fertility 171 Population Projection 173 Exercises 179 Chapter 16. Evolutionary Game Theory 180 Iterated Prisoner's Dilemma 184 Evolutionary Stability 185 Exercises 188 Chapter 17. Power and Cooperative Games 190 The Kernel 195 The Core 199 Exercises 200 Chapter 18. Complexity and Chaos 202 Chaos 202 Complexity 206 Exercises 212 Afterword: "Resistance Is Futile" 213 Bibliography 217 Index 219

About the Author

Phillip Bonacich is professor emeritus of sociology at the University of California, Los Angeles. Philip Lu is a PhD candidate in sociology at UCLA.


"[T]he volume offers certain important building blocks that can represent a bonus for students willing to learn simulation in the future... Bonacich and Lu's work brillantly introduces much of what ABM students will be requested to know in their subsequent studies."--Giangiacomo Bravo, JASSS "If you are interested in sociology specifically, or in some of the others social sciences (especially political science), then this book is a very good introduction for you... I would certainly recommend it to students and others who have some mathematical maturity and are interested in mathematical sociology, mathematical political science, or mathematical psychology."--JamesM. Cargal, UMAP Journal

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