How to Use JSTOR

The tool empowers students, faculty, researchers, and librarians to expand their research and unearth new avenues for discovery within JSTOR's extensive collection of 12+ million academic journal articles and 100,000+ books. It helps researchers identify relevant materials faster by surfacing key points and arguments from a text being viewed, discover new topics and texts within the JSTOR corpus, engage conversationally by asking questions about the text, and search more effectively with semantic, natural language queries.

How to access the tool: The interactive research tool is available on content pages for journal articles, book chapters, and research reports, and as an alternative to JSTOR’s standard keyword search. Here’s how to get started:

1. Go to jstor.org.
2. Create a JSTOR personal account or sign in to your existing personal account.
3. Ensure you have institutional access through our institution (visible at the top of your JSTOR screen).
4. Run a search and open any journal article, book chapter, or research report to start using the tool.

With the release of this tool, we aim to equip students, faculty, researchers, and librarians with innovative tools that facilitate engagement with complex content and enrich research and learning. This early release harnesses the power of AI to help users:

• Identify relevant material faster by surfacing key points and arguments from the text being viewed.
• Discover new topics and content within the JSTOR corpus, enabling exploration of additional possible paths of inquiry.
• Be conversational by asking questions about the text being viewed.
• Search JSTOR in a new way with a semantic search-powered capability that works better for natural language queries than traditional keyword search.

JSTOR stays up to date on the latest technologies and applies them in ways that best serve our users. JSTOR has previously applied machine learning (ML) and artificial intelligence (AI) technologies to optimize the research experience. For example, we have created a citation graph to link all articles on JSTOR, and used ML to improve the relevance of search results and recommendations. As we extend our knowledge and application of new technologies to AI, we expect to iterate and evolve as we learn. By volunteering for our limited beta test, you will help us define the long-term scope of this exciting new tool.