This is a course on how the social, technological, and natural worlds are connected, and how the study of networks sheds light on these connections. Topics include: social network structure and its effects on business and culture; crowdsourcing; games on graphs; the propagation through networks of information, fads and disease; small worlds, network effects, and “rich-get-richer” phenomena; the power of networks for prediction; the power of the network for web search; networks and social revolutions, and the melding of economics, machine learning, and technology into new markets, such as “prediction markets” or markets for on-line advertisements.The class will be a combination of lectures based on the textbook and guest lectures from well-known experts on these topics, primarily Stern faculty (a well-known center of excellence for research on networks, crowds, and markets).One main goal of this class is to work our way through most of the new, acclaimed textbook: Networks, Crowds, and Markets: Reasoning About a Highly Connected World, by David Easley and Jon Kleinberg. http://www.cs.cornell.edu/home/kleinber/networks-book/networks-book.pdf The textbook readings will be complemented with classic and recent research papers.
Computing and Data Science (Undergraduate)
3 credits – 15 Weeks
Sections (Spring 2023)
TECH-UB 60-000 (19341)at Washington SquareInstructed by