Course description

Networks—of social relationships, economic interdependencies, and digital interactions—are critical in shaping our lives. This course introduces models and algorithms that help us understand networks. Fundamental concepts from applied mathematics, microeconomics, and computer science are presented through the lens of network science in order to equip students to usefully analyze the big data generated by online networks. Applications discussed include the viral spread of ideas, maximizing influence, and the contagion of economic downturns. Concepts and tools covered include game theory, graph theory, data mining, and machine learning.


  • Thomas J. Watson, Sr. Professor of Computer Science, Harvard University
  • Associate Professor of Computer Science, Harvard University
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