Social and Economic Networks

by Matthew O. Jackson

Networks of relationships help determine the careers that people choose, the jobs they obtain, the products they buy, and how they vote. The many aspects of our lives that are governed by social networks make it critical to understand how they impact behavior, which network structures are likely to emerge in a society, and why we organize ourselves as we do. In Social and Economic Networks , Matthew Jackson offers a comprehensive introduction to social and economic networks, drawing on the latest findings in economics, sociology, computer science, physics, and mathematics. He provides empirical background on networks and the regularities that they exhibit, and discusses random graph-based models and strategic models of network formation. He helps readers to understand behavior in networked societies, with a detailed analysis of learning and diffusion in networks, decision making by individuals who are influenced by their social neighbors, game theory and markets on networks, and a host of related subjects. Jackson also describes the varied statistical and modeling techniques used to analyze social networks. Each chapter includes exercises to aid students in their analysis of how networks function.


This book is an indispensable resource for students and researchers in economics, mathematics, physics, sociology, and business.

Genres: Economics, Sociology, Mathematics, Science, Nonfiction, Textbooks, Reference

520 pages, Paperback

First published August 18, 2008

About the author

Matthew O. Jackson is a professor of Economics at Stanford University. He has been researching social and economic networks for more than twenty-five years.

Reviews

[Arash Yazdiha · Rating 5 out of 5]

My first exposure to this book was through an online course in coursera with the same name as in the book title. To me, this book compared to other texts in social and economic networks, would be more appropriate for a grad student. It is true that since there are so many amazing social network scientists, whether they are economists, computer scientists, or..., it is always worth it to have a look at different texts to get acquainted with other ways of telling a story, such as Barabasi's, Gladwell's, Easeley&Kleinberg's, ... . But I would definitely recommend this book for graduate students especially with economics predilection.

[Jörn Dinkla · Rating 2 out of 5]

This book is written from a strict mathematical and theoretical point of view and does not consider computer algorithms. I was a little disappointed. It reminded me of books i read in the 90s before computer algorithms became common. The title of the book should be "Mathematical analysis of s. and e. networks for theoretical economists". I always thought that only german professors can write boring mathematical books from a very distant theoretical standpoint.

[Dogsandbooks · Rating 4 out of 5]

Textbook for coursera course spring 2014. Not easy going but definitive quant Econ approach to network analysis. Of course i do have objections to quan approach to Econ but still worth slogging through

[Ji]

A great read to unpack ideas in understanding social networks. I didn't intend to get too deep with the main topic of the book - social network game theory - though. So saving it for future reference.

[Heather · Rating 4 out of 5]

Solutions tip for those of you who are studying independently: The solutions for many of the exercises can be found on the author's Coursera course (which is free to register for without a certificate). Many of the exercises in the book appear as Advanced Problem Sets in the online course, and solutions for each problem set can be found in the following week's content.

I love learning through problems so this is a resource I'm using heavily in my study of networks. The problems are not too difficult once you grapple with the notation and abstraction, but they are interesting nonetheless!

[Janid · Rating 5 out of 5]

I read it more than three times, and went also through the reference list too :)
a well written introduction to social network analysis that lists questions and shows how to answer them using social network analysis thinking and models.

[Zhijing Jin · Rating 5 out of 5]

Good math materials for network science by, e.g., graph theories. I took a brief scan, and will come back later if doing related research.

For a more high-level review, see my review of the prof's other book, The Human Network: https://www.goodreads.com/review/show...

[Yasiru · Rating 4 out of 5]

Read in tandem with the online class, which is excellent and should offer another run within a few months on Coursera. The subject is very much interdisciplinary (which might give the flawed impression of great breadth but not much depth) and this particular text distinguishes itself by presenting economic aspects of network theory with more than the usual stress. While being more descriptive than some accounts and carefully referencing the social sciences literature, this is still an applied mathematics textbook at heart.

[Austin · Rating 4 out of 5]

This is a textbook I referenced as part of an eponymous Coursera MOOC by the same author. The course and book survey the fundamentals of network science, the models of network formation, the implications of network structure, and the methods and tools used in their analysis. Much of the course was less relevant for my work in business strategy and marketing, but portions, such as diffusion models, are highly relevant.

[Ramón Cornejo-Muñoz · Rating 5 out of 5]

Uno de los mejores libros para aprender teoría de redes con aplicaciones simples y digeribles. Es un libro para pregrado pero puede extenderse para postgrado fácilmente. No conozco un libro más actual que englobe los últimos requerimientos en network theory. Muy recomendable como libro base de esta literatura.