Tag Archives: Michael Bommarito

Katz and Bommarito: Legal Analytics Course: Website, Course Materials, and Code

Daniel Martin Katz and Michael Bommarito of Michigan State University and its ReInvent Law Laboratory have launched a Website for their course entitled Legal Analytics. The site includes course materials, slides, and code. The site is described in their recent … Continue reading

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Katz and Bommarito: Slides: Legal Analytics – Introduction to the Course

Daniel Martin Katz and Michael Bommarito have posted slides from the first class session of their course entitled Legal Analytics, which they are teaching at Michigan State University College of Law. Here is an excerpt from Dan’s post describing the … Continue reading

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Katz and Bommarito: The Three Forms of (Legal) Prediction: Experts, Crowds and Algorithms

Daniel Martin Katz and Michael Bommarito of Michigan State University and the ReInvent Law Lab have posted slides of their presentation entitled The Three Forms of (Legal) Prediction: Experts, Crowds and Algorithms, given 19 November 2014 at Chicago Legal Innovation … Continue reading

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FantasySCOTUS moves to LexPredict, and will feature Katz, Bommarito, and Blackman’s prediction model

FantasySCOTUS — Josh Blackman’s prediction market for U.S. Supreme Court decisions — is now hosted by Michael Bommarito, Daniel Martin Katz, and Blackman’s firm, LexPredict, and is sponsored by Thomson Reuters, according to the service’s new About page. The new … Continue reading

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Kuhlman: Legal Synonyms Project, and word cloud of U.S. Code

Casey Kuhlman of the U.S. Open Data Institute has posted a word cloud of the U.S. Code. Casey says the data are “actual word counts piped into a JQuery lib,” and that he is also working on “N grams and … Continue reading

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Katz and Bommarito: Measuring the Complexity of the Law: The United States Code

Daniel Martin Katz and Michael J. Bommarito II have published Measuring the Complexity of the Law: The United States Code, forthcoming in Artificial Intelligence and Law. A preprint of the paper is available on SSRN. Samuel Arbesman has published a … Continue reading

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Katz, Bommarito, and Blackman: Predicting the Behavior of the Supreme Court of the United States: A General Approach

Daniel Martin Katz, Michael Bommarito, and Josh Blackman have posted a working paper entitled Predicting the Behavior of the Supreme Court of the United States: A General Approach. Here is the abstract: Building upon developments in theoretical and applied machine … Continue reading

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