Networks, Crowds, and Markets

David Easley is the Henry Scarborough Professor of Social Science and a Professor of Economics at Cornell University. He was previously an Overseas Fellow of Churchill College, Cambridge. His research is in the fields of economics, finance, and decision theory. In economics, he focuses on learning, wealth dynamics, and natural selection in markets. In finance, his work focuses on market microstructure and asset pricing. In decision theory, he works on modeling decision making in complex environments. He is a Fellow of the Econometric Society and a member of the NASDAQ-OMX Economic Advisory Board. Jon Kleinberg is the Tisch University Professor in the Computer Science Department at Cornell University. He is a member of the National Academy of Engineering and the American Academy of Arts and Sciences. His research focuses on issues at the interface of networks and information, with an emphasis on the social and information networks that underpin the Web and other online media. He is the recipient of MacArthur, Packard, and Sloan Foundation Fellowships; the Nevanlinna Prize; the ACM-Infosys Foundation Award; and the National Academy of Sciences Award for Initiatives in Research.

'The first college-level text on network science, it should be a big hit for students in economics and business.' Stan Wasserman, Indiana University

• 1. Overview; Part I. Graph Theory and Social Networks: 2. Graphs; 3. Strong and weak ties; 4. Networks in their surrounding contexts; 5. Positive and negative relationships; Part II. Game Theory: 6. Games; 7. Evolutionary game theory; 8. Modeling network traffic using game theory; 9. Auctions; Part III. Markets and Strategic Interaction in Networks: 10. Matching markets; 11. Network models of markets with intermediaries; 12. Bargaining and power in networks; Part IV. Information Networks and the World Wide Web: 13. The structure of the Web; 14. Link analysis and Web search; 15. Sponsored search markets; Part V. Network Dynamics: Population Models: 16. Information cascades; 17. Network effects; 18. Power laws and rich-get-richer phenomena; Part VI. Network Dynamics: Structural Models: 19. Cascading behavior in networks; 20. The small-world phenomenon; 21. Epidemics; Part VII. Institutions and Aggregate Behavior: 22. Markets and information; 23. Voting; 24. Property.