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Introduction to Mathematical Sociology Hardcover – Apr 1 2012
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"[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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"A first-rate introduction. The coverage is exemplary, starting with basic math techniques and progressing to models that incorporate a number of these techniques. Chapters on evolutionary game theory, cooperative games, and chaos are significantly innovative, as is the incorporation of simulations. This book brings mathematics to life for students who may entertain doubts about the role of math in sociology."--Peter Abell, professor emeritus, London School of Economics and Political Science
"This book provides a concise and up-to-date introduction to mathematical sociology and social network analysis. It presents a solid platform for engaging undergraduates in mathematical approaches to sociological inquiry, and includes Mathematica modules with which students can explore the properties and implications of a variety of formal models. I plan on using it in my courses on social networks."--Noah E. Friedkin, coauthor of Social Influence Network Theory: A Sociological Examination of Small Group Dynamics
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Most Helpful Customer Reviews on Amazon.com (beta)
With that said, it does a good job of bringing together a lot of mathematical topics that the typical student in sociology will not be exposed to if they take the basic quantitative regimen of statistics and survey data analysis. It has a lot of overlap with social networks. Some of the chapters are nearly identical to the subject matter in an undergraduate social networks course. The later chapters on game theory also offer content that is not available anywhere else.
In short, this book isn't for seasoned veterans of the field, but written for new and curious minds. Though the writing style may vary, some chapters are very friendly and explain concepts in a very accessible manner, sometimes even with humor. As an introductory book, it could have used more references, or at least point the inspired reader to additional resources if they wanted to explore each of the different topics in the book further.
The biggest flaw in this book -- in my opinion, anyway -- is the ridiculous choice of examples in some chapters. The central examples in Chapter 3 on probability concern dice and playing cards. Chapter 14 (Markov Chains) centers on drawing balls from an urn. The demography chapter (15) employs an example of the life cycle of a cat. Where is the sociology?
The book concludes with an "Afterword: 'Resistance is Futile'" that tries to make the case that the mathematical is a necessary component of education in sociology. That may be the case, but my advice is: "Resist this book!".
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