Spring 2024 Quantitative Methods: Social Sciences GR5062 section 001

SOCIAL NETWORK ANALYSIS

Call Number 13157
Day & Time
Location
F 11:10am-1:00pm
310 Fayerweather
Points 3
Grading Mode Standard
Approvals Required None
Instructor Gregory M Eirich
Type SEMINAR
Method of Instruction In-Person
Course Description

The course is designed to teach students the foundations of network analysis including how to manipulate, analyze and visualize network data themselves using statistical software. We will focus on using the statistical program R for most of the work. Topics will include measures of network size, density, and tie strength, measures of network diversity, sampling issues, making ego-nets from whole networks, distance, dyads, homophily, balance and transitivity, structural holes, brokerage, measures of centrality (degree, betweenness, closeness, eigenvector, beta/Bonacich), statistical inference using network data, community detection, affiliation/bipartite networks, clustering and small worlds; positions, roles and equivalence; visualization, simulation, and network evolution over time.

Web Site Vergil
Department Quantitative Methods/Social Sciences
Enrollment 67 students (105 max) as of 5:05PM Wednesday, July 24, 2024
Subject Quantitative Methods: Social Sciences
Number GR5062
Section 001
Division Graduate School of Arts and Sciences
Note PRIORITY QMSS STUDENTS
Section key 20241QMSS5062G001