Author Page for John Nay

Gov2Vec: Learning Distributed Representations of Institutions and Their Legal Text

Nay, J. (2016). “Gov2Vec: Learning Distributed Representations of Institutions and Their Legal Text.” Proceedings of 2016 Empirical Methods in Natural Language Processing Workshop on NLP and Computational Social Science, 49–54, Association for Computational Linguistics.,

Number of pages: 6 Posted: 21 Dec 2017

John Nay

New York University School of Law

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Topic Modeling the President: Conventional and Computational Methods

George Washington Law Review, Forthcoming, Vanderbilt Law Research Paper No. 17-62

Number of pages: 54 Posted: 12 Dec 2017 Last Revised: 23 Dec 2017

J. B. Ruhl, John Nay and Jonathan M. Gilligan

Vanderbilt University - Law School, New York University School of Law and Vanderbilt University - Department of Earth and Environmental Sciences

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Data-Driven Dynamic Decision Models

Nay, J. J., Gilligan, J. M. (2015). “Data-Driven Dynamic Decision Models”. Proceedings of the 2015 Winter Simulation Conference, 2752–2763. IEEE Press.,

Number of pages: 12 Posted: 21 Sep 2017

John Nay and Jonathan M. Gilligan

New York University School of Law and Vanderbilt University - Department of Earth and Environmental Sciences

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4.

Predicting Human Cooperation

Nay JJ, Vorobeychik Y (May 2016) Predicting Human Cooperation. PLoS ONE 11(5)

Number of pages: 19 Posted: 21 Sep 2017

John Nay and Yevgeniy Vorobeychik

New York University School of Law and Vanderbilt University, Department of Electrical Engineering and Computer Science

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5.

Predicting and Understanding Law-Making with Machine Learning

Nay JJ (2017) Predicting and understanding law-making with word vectors and an ensemble model. PLoS ONE 12(5): e0176999

Number of pages: 12 Posted: 20 Jul 2016 Last Revised: 21 Sep 2017

John Nay

New York University School of Law

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6.

Betting and Belief: Prediction Markets and Attribution of Climate Change

Nay, J. J., Van der Linden, M., Gilligan, J. (2016). “Betting and Belief: Prediction Markets and Attribution of Climate Change.” Proceedings of the 2016 Winter Simulation Conference, 1666–1677. IEEE Press.,

Number of pages: 11 Posted: 13 Jul 2016 Last Revised: 21 Sep 2017

John Nay, Martin Van der Linden and Jonathan M. Gilligan

New York University School of Law, Utah State University - Department of Economics and Finance and Vanderbilt University - Department of Earth and Environmental Sciences

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John Nay

New York University School of Law

Post-Doctoral Research Fellow

Harvard University - Berkman Klein Center for Internet & Society

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Scholarly Papers (6)

Gov2Vec: Learning Distributed Representations of Institutions and Their Legal Text

Abstract:

Topic Modeling the President: Conventional and Computational Methods

Abstract:

Data-Driven Dynamic Decision Models

Abstract:

Predicting Human Cooperation

Abstract:

Predicting and Understanding Law-Making with Machine Learning

Abstract:

Betting and Belief: Prediction Markets and Attribution of Climate Change

Abstract: