lab publications teaching software vita
Bruce Desmarais
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Governance and Administration in Networks (GAiN) Lab

The GAiN Lab, directed by Bruce Desmarais, conducts research focused on rigorously and precisely identifying the complex ways in which political actors and institutions exhibit interdependence. Approximately half of the Lab's work involves the development of analytical methods capable of illuminating these dependencies. The other half involves applications in the study of interdependence in law and policymaking. Below I provide summaries of our active projects. The Lab's funding is provided by the National Science Foundation, the Russel Sage Foundation and the William and Flora Hewlett Foundation. My lab has a site on GitHub.

Graduate Students

Sangyeon Kim

Sangyeon Kim is a Ph.D student in Political Science and Social Data Analytics. He studies contentious politics in general, ranging from social movement to civil war, by applying a network analysis approach.

szk922 [at] psu [dot] edu

Taegyoon Kim

Taegyoon Kim is a Dual-title Ph.D. student in Political Science and Social Data Analytics at Penn State, expecting to finish his degree in 2022. His primary research interests center around applying statistical and computational methods (network analysis, machine learning, and natural language processing) as well as experiments to achieve a better understanding of political attitude and behavior on social media.


taegyoon [at] psu [dot] edu

Nitheesha Nakka

Nitheesha Nakka is a Ph.D. student in Political Science. Her research investigates political framing via different social media platforms including Twitter, YouTube and TikTok. She is more generally interested in applying computational methods (such as text analysis and machine learning) to understand online political communication and the impacts of these communications on offline political participation. .

nvn5240 [at] psu [dot] edu

Omer Yalcin

Omer F. Yalcin is a Ph.D. student in Political Science and Social Data Analytics. He studies ruling coalitions and their implications for policy-making and governance using a network analysis approach and has interest in using text as a data source. Omer has Master's degrees from the Humboldt University of Berlin and the Pennsylvania State University.


oxy4 [at] psu [dot] edu

Former Graduate Students

  • Ted Hsuan Yun Chen, Postdoctoral Researcher at Aalto University and University of Helsinki
  • Matt Denny, Research Scientist at Facebook, and Adjunct Professor at Georgetown University
  • Fridolin Linder, Data Scientist at Siemens Intelligent Traffic Systems Digital Lab
  • Zachary Jones, Senior Analyst, Institute for Health Metrics and Evaluation

Lab Projects

Organizational Responsiveness to Open Outside Input

Sponsor: National Science Foundation

Period: 2013--2016

This project focuses on the development of new analytical tools for modeling the relationships between intra-organizational communication networks and open, external sources of text data. The massive quantities of textual communications generated within organizations constitute a largely untapped source for insightful, timely organizational analytics. The tools under development for this project are designed to jointly analyze the content of communications and the socio-organizational structure comprised by communication ties.

Scientific Evidence in Regulation and Governance

Sponsor: National Science Foundation

Period: 2015--2020

Public policymaking is enhanced through access to the best possible science. Central to the project is the development of the first large-scale, publicly available database that connects specific policies to specific scientific sources, allowing comparisons across time, policymaking domains, and scientific disciplines. This database better illuminates the basis of regulatory impact assessments, reveals how science is presented to policymakers, and provides scientific researchers as well as their funders with concrete evidence of real-world policy impact.

Specification and Estimation of Generalized ERGMs

Sponsor: National Science Foundation

Period: 2014--2016

The generalized exponential random graph model (GERGM) is a powerful tool for formulating and testing hypotheses about weighted networks. This project advances the current state of development of the GERGM by (1) developing a better understanding of the space of distributions that can be formulated with the GERGM; developing MCMC methods for estimation, which will broaden the class of available GERGM specifications; (3) developing constraints that facilitate the study of correlation matrices as networks; and (4) developing asymptotic theory of GERGM.

The Revolving Door in Financial Regulation

Sponsor: Russell Sage Foundation

Period: 2014--2016

We model the revolving door as a social network and assess the variable levels of advocacy success of interest groups who lobby over financial regulation designed by the Securities and Exchange Commission (SEC). The project employs data from personnel flows, lobbying and regulatory policy documents, and then utilizes best practice techniques to measure advocacy success, to control for confounding variables and to maximize causal inference within a social network analytical frame.


230 Pond Lab, (814) 863-1595, bdesmarais'at'

Deptartment of Political Science | Institute for Computational and Data Sciences | Penn State