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A general approach for predicting the behavior of the Supreme Court of the United States

Citations

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Cited by:

  1. Bokwon Lee & Kyu-Min Lee & Jae-Suk Yang, 2019. "Network structure reveals patterns of legal complexity in human society: The case of the Constitutional legal network," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-15, January.
  2. Zhong, Weifeng & Chan, Julian & Ho, Kwan-Yuet & Lee, Kit, 2020. "Words Speak Louder Than Numbers: Estimating China’s COVID Severity with Deep Learning," Working Papers 10955, George Mason University, Mercatus Center.
  3. Martin Karim, 2026. "From Big Data to Big Justice: AI and Automation in EU Consumer Collective Redress," Journal of Consumer Policy, Springer, vol. 49(2), pages 1-31, June.
  4. Zhong, Weifeng & Chan, Julian, 2020. "Predicting Authoritarian Crackdowns: A Machine Learning Approach," Working Papers 10464, George Mason University, Mercatus Center.
  5. Dat Nguyen & Minh-Phuong Nguyen & Quang-Huy Chu & Son T. Luu & Nguyen-Hoang Chu & Trung Vo & Le-Minh Nguyen, 2026. "Enhancing Legal Text Processing and Structural Analysis with Large Language Models at COLIEE 2025," The Review of Socionetwork Strategies, Springer, vol. 20(1), pages 361-383, April.
  6. Giansiracusa, Noah & Ricciardi, Cameron, 2019. "Computational geometry and the U.S. Supreme Court," Mathematical Social Sciences, Elsevier, vol. 98(C), pages 1-9.
  7. Bălan Carmen, 2018. "The Impact of Conversational Agents on Humans in Services: Research Questions and Hypotheses," International Conference on Marketing and Business Development Journal, The Bucharest University of Economic Studies, vol. 1(2), pages 33-55, December.
  8. Alain Marciano & Antonio Nicita & Giovanni Battista Ramello, 2020. "Big data and big techs: understanding the value of information in platform capitalism," European Journal of Law and Economics, Springer, vol. 50(3), pages 345-358, December.
  9. Amedeo Santosuosso & Giulia Pinotti, 2020. "Bottleneck or Crossroad? Problems of Legal Sources Annotation and Some Theoretical Thoughts," Stats, MDPI, vol. 3(3), pages 1-20, September.
  10. Luis Enriquez, 2024. "A Personal data Value at Risk Approach," Papers 2411.03217, arXiv.org, revised Nov 2024.
  11. repec:eur:ejmejr:133 is not listed on IDEAS
  12. So-Hui Park & Dong-Gu Lee & Jin-Sung Park & Jun-Woo Kim, 2021. "A Survey of Research on Data Analytics-Based Legal Tech," Sustainability, MDPI, vol. 13(14), pages 1-24, July.
  13. , Aisdl, 2020. "Becoming Attuned," OSF Preprints j7f8y, Center for Open Science.
  14. Davis, Yehuda & Govindaraj, Suresh & Suslava, Kate, 2024. "Does the stock market anticipate events and supreme court decisions in corporate cases?," Global Finance Journal, Elsevier, vol. 60(C).
  15. Anthony Niblett, 2018. "Regulatory Reform in Ontario: Machine Learning and Regulation," C.D. Howe Institute Commentary, C.D. Howe Institute, issue 507, March.
  16. Eduardo da Silva Mattos, 2025. "The Judiciary as a fiscal policy tool? Budget stress and judicial decision-making in Brazil," Public Choice, Springer, vol. 205(3), pages 563-588, December.
  17. Yang, Guancan & Lu, Guoxuan & Xu, Shuo & Chen, Liang & Wen, Yuxin, 2023. "Which type of dynamic indicators should be preferred to predict patent commercial potential?," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
  18. Ulenaers Jasper, 2020. "The Impact of Artificial Intelligence on the Right to a Fair Trial: Towards a Robot Judge?," Asian Journal of Law and Economics, De Gruyter, vol. 11(2), pages 1, August.
  19. Świtała Maciej, 2024. "Predicting the Amount of Compensation for Harm Awarded by Courts Using Machine-Learning Algorithms," Central European Economic Journal, Sciendo, vol. 11(58), pages 214-232.
  20. Yıldırım, Engin & Sert, Mehmet Fatih & Kartal, Burcu & Çalış, Şuayyip, 2023. "Non-compliance of the European Court of Human Rights decisions: A machine learning analysis," International Review of Law and Economics, Elsevier, vol. 76(C).
  21. Daniyal Alghazzawi & Omaimah Bamasag & Aiiad Albeshri & Iqra Sana & Hayat Ullah & Muhammad Zubair Asghar, 2022. "Efficient Prediction of Court Judgments Using an LSTM+CNN Neural Network Model with an Optimal Feature Set," Mathematics, MDPI, vol. 10(5), pages 1-30, February.
  22. Frederike Zufall & Rampei Kimura & Linyu Peng, 2021. "Towards a simple mathematical model for the legal concept of balancing of interests," Discussion Paper Series of the Max Planck Institute for Behavioral Economics 2021_09, Max Planck Institute for Behavioral Economics, revised 19 Oct 2021.
  23. Xiner Zhou & Hans-Georg Müller, 2022. "The dynamics of ideology drift among U.S. Supreme Court justices: A functional data analysis," PLOS ONE, Public Library of Science, vol. 17(7), pages 1-21, July.
  24. repec:eur:ejesjr:223 is not listed on IDEAS
  25. Bruno Mathis, 2022. "Extracting Proceedings Data from Court Cases with Machine Learning," Stats, MDPI, vol. 5(4), pages 1-16, December.
  26. Nasa Zata Dina & Sri Devi Ravana & Norisma Idris, 2025. "Legal Judgment Prediction using Natural Language Processing and Machine Learning Methods: A Systematic Literature Review," SAGE Open, , vol. 15(2), pages 21582440251, April.
  27. Mindock, Maxwell R. & Waddell, Glen R., 2019. "Vote Influence in Group Decision-Making: The Changing Role of Justices' Peers on the Supreme Court," IZA Discussion Papers 12317, IZA Network @ LISER.
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