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Advances in Probabilistic Network Data Analysis
Wed, September 29, 6:00 to 7:30am PDT (6:00 to 7:30am PDT), TBASession Submission Type: Virtual Created Panel
Session Description
The panel features novel statistical approaches to analyzing network data, as well as innovative applications of existing modeling strategies to tackle open problems in the study of relational outcomes.
Sub Unit
Individual Presentations
Networks All the Way Down: Assessing Modeling Choices for Political Conversation - Sarah Shugars, New York University
Mixed-Membership Stochastic Blockmodels for Bipartite Networks - Adeline Lo, University of Wisconsin, Madison; Santiago Olivella, University of North Carolina; Kosuke Imai, Harvard University
Estimating Directionality from Event Data - Cassy Dorff, Vanderbilt University; Shahryar Minhas, Michigan State University
Identification of Social Influence in Bipartite Behavior Cascades - Sebastián MartÃnez Bustos; Laurence Brandenberger; Philip Leifeld, University of Essex