Supercharge Your Literature Review With This Free AI App

Doing a literature review is one of the most time-consuming parts of any research project. Most scholars use databases like Google Scholar, PubMed, JSTOR, Project Muse, etc. to collect papers for their literature review.

These databases are, of course, useful, but they are not without their limitations. For example, when you look something up on Google Scholar, it gives you a list of books/articles relevant to your search. Google Scholar’s search results are all connected to the keywords/phrases you used.

But it doesn’t tell you how a particular book/article is related to another.

Similar is the case with a database like JSTOR.

If we were to figure out how a particular book/paper is related to other books/papers, we will have to first read it and then map the connections ourselves. This is the part that makes a literature review so time-consuming.

What if we had an app that made these connections for us? That would save us a lot of time and labor. Well, Research Rabbit is that app.

If you look up something in Research Rabbit, it will give you a list of articles just like Google Scholar or PubMed. But it will also give you the option to find works similar to the ones you have in your collection.

If you click on “Similar Work,“ Research Rabbit will give you a list of papers.

But it will also give you an interactive visualization of how these works are related.

This is something that a database like Google Scholar or JSTOR cannot do.

Green circles in the graph below are the papers you already have in your collection while blue circles are the papers suggested by Research Rabbit.

Research Rabbit also gives you the option to filter these search results. For example, here I am filtering papers that were published in 2017.

In addition to giving you an interactive visualization of the network of papers, Research Rabbit also gives you a timeline.

This is a much more efficient way of looking up papers for literature review than using a database like Google Scholar.

While Research Rabbit is an extremely useful app, it too has its limitations. For example, Research Rabbit uses the Semantic Scholar database, which seems less exhaustive than Google Scholar. Research Rabbits relies on Digital Object Identifiers (DOIs) of papers to make connections. So, if you have a source without a DOI, Research Rabbit won’t be able to do much with it.

My recommendation would be to not ditch Google Scholar for Research Rabbit. Instead, I’d suggest using both of these tools and, of course, others like them.

Become an Efficient Academic Writer with AI Apps

If you are interested in learning more about Research Rabbit and various other AI-powered apps, I have a complete tutorial for you that I updated earlier this week.

Earlier the tutorial had 170+ slides. Adding more slides would have made it unwieldy, so I divided it into 14 modules.

This tutorial will help you conceive, develop, draft, and revise your academic writing projects in a fraction of a time that you already spend.

This tutorial is being used by academics in universities like Harvard, Stanford, Columbia, University of New South Wales, University of Melbourne, Bristol University, Birmingham University and many others across the world.

Since the AI landscape is constantly evolving, I am updating the tutorial regularly. Anyone who buys the tutorial gets lifetime updates for free. Folks in lo-income countries can buy the tutorial at discounted prices.

Last night, I received an email from a scholar at a European university, and this is what they had to say about the tutorial:

“Your tips [in the tutorial] have helped me a lot, I just submitted my second paper and I used a few AI programs, which really speeded up my writing, even my supervisors were surprised by the quality of the work.“

That’s it for this week. I will see you next week.

Until then, keep writing.