How to add 'Strategy'to your Literature Search

AI-Powered Literature Mapping tools

Paperpal has partnered with Turnitin to add an “Advanced Plagiarism Detector!”

This was a feature I’ve been waiting for to call it a “Complete” solution for all Academic Editing Needs. If you want to know other Paperpal features, here’s a brief guide on Academic Writing with Paperpal. 

I’m excited to test out the performance of the new AI detector. 
Do you want me to share my findings in subsequent newsletter? 
Let me know in comments!

Finding the most relevant literature sometimes gets super challenging!

Researchers go to Pubmed and Google Scholar to search for the relevant academic papers.

When they enter the relevant keywords and get thousands of hits, they get confused and unsure about where to start!

Sometimes, the results are not very relevant to their entered keywords.

No doubt, finding relevant literature takes up an incredible amount of time and energy! 

Once you find the relevant information, then compiling it into a huge number of datasheets is another time-consuming task. 

But you no longer have to repeat this strategy. I will introduce you to AI-powered literature mapping tools. 

So, your question is, what do these literature mapping tools do? 

Finding relevant literature for your paper with a strategy is called literature mapping.  

It involves analyzing and visualizing the scientific literature on a particular topic.

Once you find the relevant papers, you often look for references or citations of those papers. 

This process lets you identify relevant authors and co-authors and research work.

It can then help you find the relevant professors to secure a scholarship! 

To avoid manual or hassle-free literature maps, these citation-based literature mapping tools play a pivotal role. 

Once you find the relevant papers in these tools using different filters, these tools use AI to recommend new ones which are similar to your search.

You can either input just a single most relevant paper (seed paper), or your complete collection.

You can then visualize similar papers on a map or a graph! 

I am familiar with a dozen such tools out there. Here, I list my favourite 4 literature mapping tools that offer FREE versions for academic researchers, including: 

Litmaps creates interactive literature maps: collections of articles that make up your different research topics. Also, has an option to use Semantic Search and lets you narrow down your research using keywords and year filters.  

ResearchRabbit generates visual citation networks and suggests related articles from a collection provided by the user. Offers suggestions for articles and potential collaborators, allows you to set up notifications, and enables collection sharing.

Inciteful uses a seed paper to help explore and discover new papers and ideas. Builds a network of papers in an iterative process using multiple seed papers.

Connected Papers uses similarity index to identify papers related to your seed paper. It also provides a map of 'Prior Works' (references) and 'Derivative Works' (papers citing the original article).

These tools not only let you search relevant papers but also import your collections from reference managers.  A few features of these tools are summarised below:

Do you want me to create a complete workflow on one of these tools?
💬 Let me know in comments!

Conclusion 

As a researcher, you are involved in many research, administrative and teaching tasks. Use AI tools to speed up your work and relieve yourself from unnecessary stress. 

AI is a game-changer for researchers, especially when it comes to literature reviews. 

These tools not only enhance the quality and comprehensiveness of your work but also save you significant time.

Compared to traditional keyword searching, AI mapping tools help you discover similar literature via seed papers and citation chains and allow you to import sources from referencing tools like Zotero and Endnote.   

However, while using these tools, there are a few important considerations to keep in mind: 

• Always VERIFY the authenticity of the output and determine that the selected research articles are indeed relevant to your research. 

• The AI era is constantly evolving, so stay updated about the capabilities and limitations of AI tools. I keep sharing my insights on LinkedIn and Twitter.

I choose a question from a subscriber to address in each newsletter.

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Answer

From the most recent study on this, 17% publishers & 70% journals have issued guidelines on using generative AI. Among them, there is no consensus on how to use it and where to report it! Here’s my post summarising the findings from the study.

We really need some clear and standard guidelines to make sure science stays honest as AI becomes more popular!