Week 11: Data analysis: networks
What does a network reveal that a list of records cannot?
Design stage: Data analysis. Match a computational method to an epistemic purpose, and work out what its output can and cannot support.
Prepare for class
Read: Chapter 8; networks, and the purposes they can serve. The chapters are in Canvas, and the companion page has the materials that go with them.
Reading focus: Read the sections on network construction and on descriptive and explanatory modeling. Ask what a tie means in your network before interpreting any measure built on it.
Bring your corpus with its author field, or the companion’s sample network data (a co-citation network of works, not of authors) if you chose the prediction route. Open the companion’s network notebook and read its saved outputs.
Weekly time budget
Outside class: 360 minutes (6 clock hours) maximum planned work per student. These allocations include all required preparation and submissions; they are planning estimates, not time logs for grading.
| Work | Planned minutes |
|---|---|
| Reading and discussion preparation | 90 |
| Exercises and project work, including troubleshooting | 210 |
| Writing, documentation, and reflection | 60 |
| Total | 360 |
Build the network or begin the predictive models, whichever route you chose. Use the companion notebook and sample data to see a complete example before adapting it.
How the weekly cap works. If required work will exceed the budget, save your attempt and contact the instructor to adjust scope or arrange support.
From the book
Exercise 8.1.1 builds the network, and Exercises 8.2.1 and 8.2.3 put it to descriptive and explanatory use. Each asks you to confront the gap between what an algorithm computes and what the result means.
- Exercise 8.1.1: Network construction and iterative search. One of your choices for Milestone 4.
- Exercise 8.2.1: Centrality and social capital. One of your choices for Milestone 4.
- Exercise 8.2.3: Community detection and explanatory analysis. One of your choices for Milestone 4.
- Exercise 8.1.2: Simulation and emergence. Optional.
The book gives each exercise’s steps. What to submit, and when.
On the companion website: Chapter 8 materials · Network notebook and sample network data · Computational analysis tools
Monday, March 22: Construct and inspect a network
12:45–2:00 PM · PV A203
Do Exercise 8.1.1: build the coauthor network from your corpus, report nodes, edges, density, components, and the diameter of the largest component, and compute a shortest path between two authors. If you chose the prediction route, follow along with the companion’s sample data, then start Exercise 8.1.3.
Check the reasoning: A coauthorship tie records a shared publication, not a friendship or a flow of ideas. Say what a short path between two authors does and does not suggest about your field.
Wednesday, March 24: Purposes workshop
12:45–2:00 PM · PV A203
Network route: do Exercise 8.2.1 on centrality and social capital, or Exercise 8.2.3 on community detection. Run community detection under several seeds before treating a partition as a finding. Prediction route: build features and fit the linear baseline for Exercise 8.1.3, using the companion’s supervised-learning primer.
Check the reasoning: For any measure you report, write one sentence on the gap between what it computes and the concept you want it to stand for. A high betweenness score is not yet social capital.
Work to carry forward
Keep the script, the statistics, and one result with its interpretation. Record the seeds you used.
Coming up: Milestone 4: Data analysis (15 points), due Wednesday, April 7.
Assignments and deliverables · Your project · The book and companion website