Daniel L. Chen

Daniel L. Chen, “Judicial Analytics and the Great Transformation of American Law”, Artificial Intelligence and the Law, vol. 27, n. 1, March 2019, pp. 15–42.

Daniel L. Chen, “Machine Learning and Rule of Law”, Computational Analysis of Law, vol. 27, n. 1, March 2019, pp. 15–42.

Daniel L. Chen, Vardges Levonyan, S.Eric Reinhart, and Glen Taksler, “Mandatory Disclosure: Theory and Evidence from Industry-Physician Relationships”, Journal of Legal Studies, 2019, forthcoming.

Daniel L. Chen, Charlotte Cavaillé, and Karine Van Der Straeten, “A Decision-Theoretic Approach to Understanding Survey Response: Likert vs. Quadratic Voting for Attitudinal Research”, The University of Chicago Law Review, 2019, forthcoming.

Daniel L. Chen, Manoj Kumar, Vishal Motwani, and Philip Yeres, “Is Justice Really Blind? And Is It Also Deaf?”, Computational Analysis of Law, 2019, forthcoming.

Daniel L. Chen, “Intermediated Social Preferences: Altruism in an Algorithmic Era”, in Advances in Economics of Religion, Jean-Paul Carvalho, Sriya Iyer, and Jared Rubin (eds.), Palgrave Macmillan, series “International Economic Association Series”, vol. 158, 2019, pp. 119–138.

Daniel L. Chen, Xing Cui, Lanyu Shang, and Junchao Zheng, “What Matters: Agreement Between U.S. Courts of Appeals Judges”, Journal of Machine Learning Research, 2019, forthcoming.

Daniel L. Chen, and Elliott Ash, “Case Vectors: Spatial Representations of the Law Using Document Embeddings”, Computational Analysis of Law, 2019, forthcoming.

Daniel L. Chen, “Does Empathy Beget Guile?”, Review of Law and Economics, 2019.

Daniel L. Chen, Yosh Halberstam, Manoj Kumar, and Alan Yu, “Attorney Voice and the U.S. Supreme Court”, Computational Analysis of Law, 2019, forthcoming.

Daniel L. Chen, Matt Dunn, Levent Sagun, and Hale Sirin, “Early Predictability of Asylum Court Decisions”, in Proceedings of the ACM Conference on AI and the Law, 2018.

Daniel L. Chen, and Jess Eagel, “Can Machine Learning Help Predict the Outcome of Asylum Adjudications?”, in Proceedings of the ACM Conference on AI and the Law, 2018.

Daniel L. Chen, Jacob Phillips, and Alan Yu, “Non-Segmental Conditioning of Sibilant Variation in American English”, in Proceedings of the 9th International Conference on Speech Prosody, 2018.

Ramya Vunikili, Hitesh Ochani, Divisha Jaiswal, Richa Deshmukh, Daniel L. Chen, and Elliott Ash, “Analysis of Vocal Implicit Bias in SCOTUS Decisions Through Predictive Modelling”, in Proceedings of Experimental Linguistics, 2018.

Elliott Ash, and Daniel L. Chen, “What Kind of Judge is Brett Kavanaugh?: A Quantitative Analysis”, Cardozo Law Review, 2018, pp. 70–100.

Daniel L. Chen, “Tastes for Desert and Placation: A Reference Point-Dependent Model of Social Preferences”, Research in Experimental Economics, 2018.

Daniel L. Chen, Adithya Parthasarathy, and Shivam Verma, “The Genealogy of Ideology: Identifying Persuasive Memes and Predicting Agreement in the U.S. Courts of Appeals”, in Proceedings of the ACM Conference on AI and the Law, 2018, forthcoming.

Elliott Ash, Daniel L. Chen, Nischal Mainali, and Liam Meier, “Automated Classification of Modes of Moral Reasoning in Judicial Decisions”, Computational Legal Studies, 2018, forthcoming.

Adam B. Badawi, and Daniel L. Chen, “The Shareholder Wealth Effects of Delaware Litigation”, American Law and Economics Review, vol. 19, n. 2, October 2017, pp. 287–326.

Carlos Berdejo, and Daniel L. Chen, “Electoral Cycles Among U.S. Courts of Appeals Judges”, The Journal of Law and Economics, vol. 60, n. 3, August 2017, pp. 479–496.