Computational Social Networks Sequence

Department of Sociology, UCLA

Welcome to the course repository for the Graduate Computational Social Networks Sequence (SOCIOL 208A & 208B) at UCLA. This website hosts all syllabi, reading schedules, interactive lecture notes, R code snippets, and instructional materials.

SOCIOL 208A

Social Networks Methods
Fall Quarter

A graduate-level seminar focused on the data-analytic and computational techniques used in Social Network Analysis (SNA). This course covers the practical application of network theory using R and igraph.

Key Topics Covered:
  • Centrality, status, and prestige measures
  • Cohesion, equivalence, and similarity
  • Community detection and subgroups
  • Two-mode (bipartite) networks
  • Statistical models (ERGM, QAP, Swapping)

SOCIOL 208B

Social Networks Theory
Spring Quarter

A substantive graduate seminar exploring the theories, perspectives, and empirical research in sociology through a social networks lens. The focus is on substantive contributions and conceptual frameworks.

Key Topics Covered:
  • Relational sociology & network thinking
  • Weak ties, homophily, and brokerage
  • Collaboration networks & field dynamics
  • Network diffusion and contagion
  • Historical social networks & inequality

Sequence Overview

The sequence is designed to equip students with both the theoretical foundations and the methodological toolkit required to conduct original, publication-quality research using network analytic approaches:

Code
flowchart LR
    A[SOCIOL 208A: Methods] -->|Methodological Toolkit| C(Original Research)
    B[SOCIOL 208B: Theory] -->|Theoretical Foundations| C

flowchart LR
    A[SOCIOL 208A: Methods] -->|Methodological Toolkit| C(Original Research)
    B[SOCIOL 208B: Theory] -->|Theoretical Foundations| C

To get started, select a course syllabus from the cards above or browse the lecture topics directly using the sidebar navigation.