INFO 4613/5613

Network Science

INFO 4613/5613 “Network Science” is a semester-length and cross-listed undergraduate elective and graduate course. Data involving relationships and interactions are pervasive in contemporary information society but these data require distinct methods and theories for analysis and interpretation. Network science is an umbrella term that encompasses interdisciplinary theories and methods for analyzing social, information, and other complex networks. Network science provides tools to develop quantitative representations linking micro-level processes to macro-level structures across diverse empirical settings like organizations, online communities, and archives. Students will develop their familiarity with the methods and theories to understand the fundamentals of networks, metrics for characterizing their structure, and the dynamics of and on networks.

Learning objectives

  • Understand the theoretical and methodological implications of relational data
  • Apply and interpret metrics for understanding network structure and dynamics
  • Develop familiarity with computational tools for analyzing and visualizing networks
  • Integrate and explain network methods and theories for general audiences


Module Week Skills
Fundamentals 1 Introductions
  2 Data and ethics
  3 Visualizing networks
Structure 4 Node-level structure
  5 Local-level structure
  6 Network-level structure
  7 Community structure
Dynamics 8 Random networks
  9 Network growth
  10 Diffusion and influence
  11 Homophily and selection
Applications 12 Bipartite networks
  13 Weighted networks
  14 Fall Break
  15 Presentations
  16 Presentations

Course materials