printer friendly pageMS&E 334: 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.
Terms: Aut
| Units: 3
Instructors:
Ugander, J. (PI)
;
Hong, J. (TA)
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