ScholarSift & JStor Text Analyzer Use AI to Identify Law & Multidisciplinary Articles that You Might Have Missed

ScholarSift is a new resource that legal scholars and law librarians should keep an eye on.  Using artificial intelligence, it analyzes the text and citations of law journal articles to find other relevant law journal articles.  You can either search for articles already in the database or upload your own draft.  It’s designed to identify scholarship that you might otherwise have missed in the course of your research.  It’s currently in beta but is expected to publicly launch on April 12th.

Here’s a screenshot of the analysis from my recent paper on Representing Law Faculty Scholarly Impact which I uploaded to ScholarSift.

ScholarSift screenshot

From my cursory analysis, ScholarSift seems to be harvesting content from repositories that use Digital Commons.  Once it launches, authors or librarians can also upload law faculty scholarship to the ScholarSift database so that these works will appear in search results.  This may become an important way to promote scholarly visibility for law scholars.

If you’re interested in learning more about ScholarSift, the podcast Ipse Dixit recently interviewed Robert Anderson, one of the developers.  Definitely worth a listen.  See also this recent post to TechDirt.

JStor offers a similar tool called JStor Text Analyzer.  You upload a document and it locates related articles in JStor’s collection of academic journals.  It’s a great resource for finding multidisciplinary articles that you might otherwise have missed.  It’s also a nifty way to identify keywords and phrases that describe your work when posting it to SSRN or a digital repository.

Here’s a screenshot of the analysis from my same paper in JStor Text Analyzer.
JStor Text Analyzer screen shot