research paper analyzer

Use AI to summarize scientific articles and research papers in seconds

Send a document, get a summary. It's that easy.

If GPT had a PhD

• Unlimited Summaries
• Summarize articles up to 200,000 words.
• 5 Figure and table analysis with AI
• Unlimited Chat Messages
• Unlimited article searches
• Import and summarize references with the click of a button
• 30,000 words summarized
• 5 Figures or Tables analyzed with AI
• 100 Chat Messages
• Maximum document length of 200,000 words
• Unlimited bulk summaries
• Unlimited chat messages per month
• Unlimited figure and table analysis with AI
• 1,000 documents indexed for semantic search

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Text Analyzer

First released: Feb 2017

Last major update: Jan 2018

Graduated: Aug 2024

Text Analyzer Graduation:

Text Analyzer, which has a long and exciting run, will graduate on August 30, 2024. The tool has been useful to thousands and inspired many more. Just here at ITHAKA , it has informed the vision for two services  that you may find useful:

• JSTOR’s AI-powered interactive research tool that opens up new ways to search and understand our content. If you used Text Analyzer primarily as a tool to discover new content on JSTOR, try this new cutting-edge tool.
• Constellate , a platform for teaching, learning, and performing text analysis with scholarly and primary source content. If you used Text Analyzer primarily to understand your own document, try Constellate.

Upload your own document to search JSTOR. Text Analyzer finds the topics discussed in your document and recommends articles and chapters about the same topics from JSTOR.

What we did:

• During a design sprint exploring ways that JSTOR could support scholars and their preprints, we tested the concept of allowing users to upload their nearly-finished papers to find additional content. Users were exceptionally positive about both the idea and an early functional prototype.
• We released Text Analyzer as a beta tool on the primary JSTOR website and, as users began to find it valuable, we went through multiple cycles of improvement and promotion.
• We continiued to improve the algorithm that powers it throughout, adding one major new feature: the ability to submit texts in fifteen different languages and get results in English .

What we built:

Reactions to Our Work:

We collected reactions to Text Analyzer on social media, published media and in (anonymized) email. We used the late, great Storify to retain these, but when that site went dark, created our own repository:

• February and March 2017
• Summer 2017
• September 2017
• October 2017
• November 2017
• Winter 2017-18
• February and March 2018

What we learned:

• Searching using a document can help junior researchers who are "keyword thrashing," i.e. looking for the right term in a keyword search.
• Searching using a document also helps established researchers to find relevant material outside of the specific disciplines or fields they work in.
• Driving adoption of a new means of search takes partnership with librarians and faculty teaching research methods.