Adeline Lo (Workshop in Applied Statistics)


Wednesday, March 10, 2021, 12:00pm to 1:30pm


Zoom - link below

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Today's presenter:

Adeline Lo (University of Wisconsin-Madison),  "Mixed-Membership Stochastic Blockmodels for Bipartite Networks: Application to Cosponsorship in the US Senate"

Conference link:


Many networks in political and social research are naturally bipartite—with two distinct types of actors (nodes), and edges connecting exclusively across the actor types. An example of such networks is the one that results from cosponsorship decisions, in which legislators are connected to the bills they support. Typically, researchers who wish to study these networks are forced to "project" or marginalize over one node type, in an effort to form the kinds of unipartite networks that standard models can handle. This can result in aggregation bias and loss of relevant information about the node type that is averaged over. To avoid these issues, we propose an extension of the mixed-membership stochastic blockmodel that operates directly on the bipartite network structure, incorporating both node and dyad-level covariates. We design and implement a fast, scalable stochastic variational algorithm to obtain estimates of latent variables and hyper-parameters, and illustrate our model using data from the 107th and 108th sessions of the U.S. Senate. We find that using our model allows us to uncover interesting groups of bills, explore the effects of individual ideology on the likelihood of bipartisan cosponsorship, and evaluate the norms of reciprocity in the legislative context.

The Applied Statistics Workshop (Gov 3009) is a forum for graduate students, faculty, and visiting scholars to present and discuss methodological or empirical work in progress in an interdisciplinary setting. The workshop features a tour of Harvard's statistical innovations and applications with weekly stops in different fields and disciplines and includes occasional presentations by invited speakers. It is co-hosted by Harvard University's Department of Government and Institute for Quantitative Social Science (IQSS).

For more information, visit the Applied Statistics website.