Presentation @ 24th International Conference on Legal Knowledge and Information Systems ( Jurix 2011 - Vienna )

Legal Language Explorer Presentation @ 24th International Conference onLegal Knowledge and Information Systems (Jurix 2011) daniel martin katz michael j bommarito ii julie seaman adam candeub eugene agichtein

Law is characterized by arelatively small number of highly influentialcases and jurists whoseconceptualization of law comes to dominate

Most Judges and CasesAre Quickly Forgotten

But A Select Few Persist ...

Extreme Skewing is a Typical Feature of Legal Systems Katz, et al (2011) Katz & Stafford (2010) Geist (2009)American Legal Academy American Federal Judges Austrian Supreme Court Smith (2007) Smith (2007) Post & Eisen (2000) U.S. Supreme Court U.S. Law Reviews NY Ct of Appeals

innovative use of language and metaphor is In Part

How Holmesbecame “Holmes”and how Posnerbecame “Posner”

And how certain casescame to dominate the rest of the corpus

We BelieveThe decision corpus is our archeological record

We Believe The decision corpus is our archeological record and that record can beusefully explored using the tools of computational linguistics

We WantTo Democratize the Exploration of Legal Language ...

We Want To Democratize the Exploration of Legal Language ...to folks who are not programmers

We Want To Democratize the Exploration of Legal Language ...to folks who are not programmers to folks who are not technically inclined

We Develop a Simple WebInterface that Leverages the Visual Cortex

Relies on Our Ability to Engage in Pattern Detection

To Explore Linguistic Patterns in Large Corpora of Legal Documents

We Start with the Full Text Corpus of Decisions of theUnited States Supreme Court 1791-2005

Develop a N-Gram Based Explorerwith a Portal to the Full Text, etc.

From Text to N-Grams...

Generate the N-Gram Mapping (1) extract the opinion text from each case and store it as a sequence of characters (2) convert this sequence of characters into a sequence of words through Word Tokenization (Penn Tree Bank Algorithm) (3) iterate over words in the length M sequence from index 1 to index M + 1 – N

Generate the N-Gram Mapping

Legal Language Explorer: A Brief Tour of The Interface

Go toLegalLanguageExplorer.com And Access This Interface

Notice The Default Search IsInterstate Commerce, Railroad, Deed

For Each Comma Separated PhraseThe Frequency Plot Appears Below

Currently Supporting Every U.S. Supreme Court Decision From 1791 - 2005

Years Can Be Changed By The End User

Click Here to Access Various Advanced Search Features

The AdvancedSearch Features

Are the Observed Trendsa Function of changes in the volume of the case docket?

Normalization allows End User to control for the Size of the Case Docket

Change the Graph Type By Clicking Here

An Alternative Presentation of the Data

Export the Chart Data(If You Want to Replot in Stata, Excel, R, etc.)

The Results(If You Want to Replot in Stata, Excel, R, etc.)

Access a Case List and Full Text Results

Here are the Returned Results

Download List in Excel(or any .csv)

Access theFull Text aParticular Case

Click Through to AccessResults fromBulkResource.org

For More Information - Full Version of the Paperhttp://papers.ssrn.com/sol3/papers.cfm?abstract_id=1971953

ForImplementation Details (Including the Key Value Storage Method, etc.) http://www.michaelbommarito.com/ blog/2011/12/16/building-legal- language-explorer-interactivity- and-drill-down-nosql-and-sql/

Slides will Be Posted to CLS Blog http://computationallegalstudies.com/

This is Only The BeginningStay Tuned for More in 2012 :) daniel martin katz michael j bommarito ii julie seaman adam candeub eugene agichtein

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Presentation @ 24th International Conference on Legal Knowledge and Information Systems ( Jurix 2011 - Vienna )

by Daniel Katz on Dec 17, 2011

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