Topics

The course will cover 14 topics. Each topic represents a week of guided engagement, structured to support a progressive transition from foundational concepts to the autonomous execution of a computational social network analysis project. The course is organized into four sequential phases—Introduction, Computation, Analysis, and Synthesis—that collectively scaffold students’ learning and skill development. Corresponding handouts and resources are linked to each topic to facilitate coherence and continuity across the learning trajectory.

Read the topic preface: Tracing Patterns, Computing Connection*

1. Orientation: Mapping the Networked World
   Learning Focus: Course overview, research ethics, data privacy
   Guide Questions:

   • How do networks define the digital world we inhabit?

   • What responsibilities arise when studying people’s connections?

2. Social Networks and Graphs
   Learning Focus: Nodes, edges, relationships; graph theory basics
   Guide Questions:

   • How can a friendship be represented as an edge? 

   • What do structure and degree reveal about community?

3. Constructing Network Data
   Learning Focus: Data sources, surveys, APIs, anonymization
   Guide Questions:

   • How can we transform social interactions into analyzable data? 

   • What biases may enter this process?

4. Quantifying Structure
   Learning Focus: Density, components, connectivity, diameter
   Guide Questions:

   • What makes a network cohesive or fragmented?

   • How can we measure such cohesion?

5. Validity and Reliability in Network Data
   Learning Focus: Measurement errors, sampling bias, temporal effects
   Guide Question: How can we ensure that our computed measures truly reflect social realities?

6. Graphs, Matrices, and Representation
   Learning Focus: Adjacency and incidence matrices, weighted graphs
   Guide Questions: How do matrices help computers “see” networks?

7. Advanced Network Forms
   Learning Focus: Directed, signed, multigraphs, and hypergraphs
   Guide Questions: How do direction and sign enrich or complicate interpretation?

8. Prominence and Influence
   Learning Focus: Centrality, prestige, authority, eigenvectors
   Guide Question: 

   • What defines an “influencer”?

   • How do we measure social importance?

9. Structural Balance and Conflict
   Learning Focus: Signed networks, triads, balance theory
   Guide Question: Why do some social groups stabilize while others polarize?

10. Community and Clustering
    Learning Focus: Cliques, cores, modularity, transitivity
    Guide Question: How can communities emerge from individual connections?

11. Diffusion and Contagion
    Learning Focus: Information flow, viral spread, innovation adoption
    Guide Question: How do rumors, ideas, or behaviors propagate through networks?

12. Temporal and Dynamic Analysis
    Learning Focus: Evolving networks, longitudinal data
    Guide Question: 

    • What happens when networks change over time?

    • How do we model evolution?

13. Project Development and Ethics Review
    Learning Focus: Proposal presentation, peer feedback, dataset selection
    Guide Question: How do we frame a good research question in CSNA?

14. Implementation, Presentation, and Reflection (3 weeks)
    Learning Focus: Coding, analysis, visualization, defense
    Guide Question: 

    • What insights did we uncover?

    • How can they be responsibly communicated?

Read the topic postface: Reflections from the Web of Connection*