32 citations · 118 across the 12 of their papers we have counts for
6 papers · 1 filter
Gov2Vec: Learning Distributed Representations of Institutions and Their Legal Text
John J. Nay
We compare policy differences across institutions by embedding representations of the entire legal corpus of each institution and the vocabulary shared across all corpora into a co…
Predicting and Understanding Law-Making with Word Vectors and an Ensemble Model
John J. Nay
Out of nearly 70,000 bills introduced in the U.S. Congress from 2001 to 2015, only 2,513 were enacted. We developed a machine learning approach to forecasting the probability that…
Data-Driven Dynamic Decision Models
John J. Nay, Jonathan M. Gilligan
This article outlines a method for automatically generating models of dynamic decision-making that both have strong predictive power and are interpretable in human terms. This is u…
Betting and Belief: Prediction Markets and Attribution of Climate Change
John J. Nay, Martin Van der Linden, Jonathan M. Gilligan
Despite much scientific evidence, a large fraction of the American public doubts that greenhouse gases are causing global warming. We present a simulation model as a computational…
A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health
John J. Nay, Emily Burchfield, Jonathan Gilligan
Drought threatens food and water security around the world, and this threat is likely to become more severe under climate change. High resolution predictive information can help fa…
Predicting Human Cooperation
John J. Nay, Yevgeniy Vorobeychik
The Prisoner's Dilemma has been a subject of extensive research due to its importance in understanding the ever-present tension between individual self-interest and social benefit.…