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This concentration helps students to understand formal models, data and policy issues surrounding networked systems. Models: Foundations of formal analysis and design of interconnected systems--understanding networks and human behavior drawing on ideas from economics, sociology, computing and information science, and applied mathematics. Data: Tools and techniques to analyze data related to analyzing networked behavior. Policy/Values: Ethical, legal and social issues around networked behavior and data, and designing networked systems.
Students interested in analytical frameworks for online social systems and formal models of human behavior and decision making; applying formal models for analysis and design of online systems.
The core course related to this concentration is INFO 2040: Networks.
Some faculty members whose research is related to this concentration include: Larry Blume, Cristobal Cheyre, David Easley, Jon Kleinberg, Michael Macy, and Evá Tardos.
Career paths
- Professional careers in online Web companies and startups as algorithm designers, data scientists, etc (Google, Facebook, Twitter)
- Graduate study in Information Science; Computational Social Science; Computer Science; Applied Economics---Masters or PhD programs.
Networks, Crowds, and Markets Courses
Please reference the Cornell Class Roster for details on the courses below.
A. Models (choose two)
- INFO 4220: Networks II: Market Design
- INFO 4360: Communication Networks and Social Capital
- COMM 3150: Organizational Communication: Theory and Practice
- ECON 3810: Decision Theory I
- ECON 4020: Game Theory
- ECON 4022: Game Theory II
- ECON 4610: Industrial Organization I
- ECON 4660: Behavioral Economics
- ORIE 4350: Introduction to Game Theory
- SOC 3080: Social Networks and Power
B. Data (choose one)
- INFO 3300: Visual Data Analytics for the Web (previously Data-Driven Web Applications)
- INFO 3950: Data Analytics for Information Science
- INFO 4300: Language and Information
- INFO 4350: Conversations and Information
- CS 4740: Natural Language Processing
- CS 3780 (previously 4780): Machine Learning for Intelligent Systems
- CS 4786: Machine Learning for Data Science
- ECON 3120: Applied Econometrics
- ECON 3140: Econometrics
C. Policy/Values (choose one)
- INFO 3561: Computing Cultures
- INFO 4145: Privacy and Security in the Data Economy
- INFO 4200: Information Policy: Applied Research and Analysis
- INFO 4240: Designing Technology for Social Impact
- INFO 4250: Surveillance and Privacy
- INFO 4940: Special Topics - U.S. Copyright Law
- INFO 4940 Special Topics - Good Tech, Bad Tech
- INFO 4940: Special Topics - Technology and Social Change Practicum
- INFO 4940: Special Topics - Law, Policy, and Politics of Cybersecurity
- INFO 4940: Special Topics - Law, Policy and Politics of Artificial Intelligence (AI)
- COMM 4940: Special Topics - Human-Algorithm Behavior
- PUBPOL 3460: Culture, Law, and Politics of Information Policy
- STS 3440: The Data Science & Society Lab