MS&E334 - Topics in Social Data

This course provides a in-depth survey of methods research for the analysis of large-scale social and behavioral data. There will be a particular focus on recent developments in discrete choice theory and preference learning. Connections will be made to graph-theoretic investigations common in the study of social networks. Topics will include random utility models, item-response theory, rank aggregation, centrality and ranking on graphs, and random graphs. The course is intended for Ph.D. students, but masters students interested in research topics are welcome. Recommended: 221, 226, CS161, or equivalents.
Career
Graduate
Grading Basis
ROP - Letter or Credit/No Credit
Min
3
Max
3
Course Repeatable for Degree Credit?
No

Course Component
Lecture
Enrollment Optional?
No