Networks, Crowds and Markets
Discover how networks, game theory, and market dynamics reveal the hidden connections shaping our interconnected modern world.
Discover how networks, game theory, and market dynamics reveal the hidden connections shaping our interconnected modern world.
This interdisciplinary course examines the complex connections between social, economic, and technological realms in the modern world. Students will delve into graph theory, game theory, and network analysis to understand phenomena such as social contagion, information cascades, and the spread of influence. The course covers topics like Internet structure, Web search processes, strategic behavior in various settings, and the dynamics of matching markets.
Instructors:
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What you'll learn
Use graph theory tools to study Internet social networks and Web search processes
Apply game theory to analyze strategic behavior in auctions, advertising, and social marketing
Understand strategic behavior in matching markets linking buyers and sellers
Explore relationships between markets, information, and consumer expectations
Analyze how ideas, beliefs, and technologies spread through social networks
Skills you'll gain
This course includes:
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Graded assignments, Exams
Access on Mobile, Tablet, Desktop
Limited Access access
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Module Description
This course offers a comprehensive exploration of how networks, crowds, and markets interconnect in the modern world. It covers a wide range of topics, including graph theory as a tool for studying the Internet and social networks, game theory for analyzing strategic behavior in various contexts, and the dynamics of matching markets. Students will learn about the structure of the Internet, social contagion processes, the spread of social power and popularity, and information cascades. The course also delves into the relationships between markets, information, and consumer expectations, providing insights into how ideas, beliefs, opinions, products, technologies, and social conventions spread through social networks. Based on an interdisciplinary Cornell University course, this MOOC is designed to be accessible to students at the introductory undergraduate level, requiring only a background in high school algebra and some familiarity with probability concepts.
Fee Structure
Instructors
Expert in Economics, Information Science, and Network Analysis at Cornell University
David Easley, the Henry Scarborough Professor of Social Science at Cornell University, is a distinguished scholar with joint appointments in the departments of Economics and Information Science. His research, focusing on learning and wealth dynamics, market microstructure, and networks, bridges multiple disciplines and contributes significantly to understanding complex social and economic systems in highly connected environments. A Fellow of the Econometric Society with a Ph.D. from Northwestern University, Easley has made notable contributions to the field, particularly through his co-authored book "Networks, Crowds and Markets: Reasoning About a Highly Connected World." This work, based on the popular undergraduate course "Networks" that he developed at Cornell with Jon Kleinberg, integrates perspectives from economics, sociology, computing, information science, and applied mathematics. Easley's interdisciplinary approach to studying networks and behavior in networked environments has positioned him as a key figure in the emerging field at the interface of these disciplines, making him a valuable asset to Cornell's academic community and the broader field of social science research.
Pioneering Researcher in Network Science and Information Systems at Cornell University
Jon Kleinberg is the Tisch University Professor of Computer Science and Information Science at Cornell University, where he currently chairs the Department of Information Science. A renowned expert in network science, Kleinberg's research focuses on the interface between networks and information, particularly social and information networks underlying the World Wide Web and online media. His groundbreaking work has earned him numerous accolades, including a MacArthur Fellowship and membership in the National Academy of Engineering, the National Academy of Sciences, and the American Academy of Arts and Sciences. Kleinberg's contributions span various fields, including algorithmic aspects of the small world phenomenon, link analysis for web search, and the study of cascading behaviors in networks. With a Ph.D. from MIT, Kleinberg has co-authored influential textbooks and significantly shaped the understanding of complex networks in the digital age. His leadership at Cornell and his interdisciplinary approach to studying networks and algorithms have established him as a key figure in computer science and information systems research.
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