Hi all,
Our next virtual meeting will be Wednesday, September 16, where we will
hear Connor Jerzak (Harvard University; practice job talk) presents
research on "Detecting and Characterizing Latent Influence Dynamics in
Social Science Data Using Machine Learning."
Abstract:
Unobserved interactions between people and groups play a fundamental role
in domestic and international politics. Yet, despite their importance, the
vast complexity of these unobserved interactions has typically frustrated
efforts to quantify them, forcing scholars to assume that the units in an
analysis are independent or to study a limited range of interactions. Here,
I develop a framework and machine learning model for detecting and
characterizing unobserved interference dynamics using all available
information: outcome, covariate, and independent variable data. Given
minimal assumptions, this approach guarantees an analyst-set cap on the
rate of false influence detection. It is able to satisfactorily reconstruct
the influence structure of a network that was approximately measured by
investigators in a school bullying experiment. I apply the method to 12
social science experiments and focus on one of these, a voter turnout
intervention in the UK, as a case study. I also discuss the application of
this method to the analysis of influence in observational data and in
answering questions about individual-level spillovers.
Zoom link:
https://harvard.zoom.us/j/99424949004?pwd=aWtPNFM3ZzFYbWxIMXNoZDlyUElVZz09
(Login required)
When: Wednesday, September 16 at 12noon -- 1:30pm.
The information and schedule of the seminar can be found on our website
<https://projects.iq.harvard.edu/applied.stats.workshop-gov3009/home> and
Google calendar
https://bit.ly/30QZJ9k.
Best,
Soichiro Yamauchi
--
Soichiro Yamauchi
PhD candidate
Harvard University
URL:
https://soichiroy.github.io/