Edit : Added a 2024 reddit post on academic search + Large Language Model functionality, eg Elicit. Com, Scopus AI, Consensus, Undermind etc

Why YSK: Doing narrative literature reviews is standard part of academia, these new cutting edge tools will help you do them much faster and better no matter which stage of the literature review you are in.

Keyword searching isn't the only or even best way to find relevant literature article papers. Sometimes you may not know the right keyword to use and miss papers or get the opposite problem and get too many results.

One way around this problem is to find a very relevant "Seed" paper (given to you by your supervisor, found via Wikipedia or other ways);and start mining the paper in both directions, both looking at the references or via citation indexes like Google Scholar, Web of Science, Microsoft academic, Semantic Scholar find papers that cite those seed papers.

But this gets unwieldly once you have a big bunch of relevant papers to mine for references/citations. Imagine if you decided to start with a dozen references from Wikipedia..

You should know in the past 2-3 years particularly in the past year, there has been many free or even open source tools released that will do all this tracing for you automatically and even visualize the results in various maps.

They can be useful depending on the stage of literature review you are in.. whether you are just exploring the space, want to check for unexpected connections between papers you have already found or just want to confirm you aren't missing anything obvious.

While bibliometric tools (also known as science mapping tools) like VOSviewer, Citespace, CitNet Explorer have existed for a decade or more, they are difficult to use, targeted at bibliometricians and full of Jargon. The new batch of mapping tools, I list below are designed for the researcher and do not require bibliometrics expertise to use and understand (though at the cost of flexibility).

I keep track of a dozen such tools here https://musingsaboutlibrarianship.blogspot.com/p/list-of-innovative-literature-mapping.html but here I list my top half dozen with honourary mentions

https://aarontay.medium.com/3-new-tools-to-try-for-literature-mapping-connected-papers-inciteful-and-litmaps-a399f27622a

My current recommendations

1. Connected Papers — Simple but powerful one shot visualization tool using one seed paper- Update Aug 2022: Free version now allows maximum 5 graphs a month, this is a fairly big limitation, so this is no longer one of my favorites.

2. ResearchRabbit - More advanced tools, helps reduce friction as you do iteratively keyword searching, exploration via references, citations and authors.

3. Inciteful — Customizable tool , use multiple seed papers in an iterative process

4. Litmaps —Use multiple seed papers and overlapping maps, combining search with citation relationships and visualization

5. Honorary mentions — CoCites, Citation Gecko, VOSviewer, CitationChaser + more

6. Citation context/sentiment tools (these classify by type of citation e.g. if a citation is "mentioning"/"supporting"/"disputing") — scite, Semantic Scholar. scite is freemium.

Incidentally, we are seeing the rise of a new class of innovative literature review mapping tools, built on the backs of increasingly open metadata and citations coupled with possibly some new machine learning techniques (particularly those that use machine learning on full text for citation contexts).

I expect such tools to be increasingly powerful as more and more Scholarly metadata and full text is made open.

Thanks for all the praise but I didn't make these tools, I only aggregate them. If any of these tools have helped you please let their creators know and or credit them !

Edit 1 : Others in reply have suggested Yewno Discovery which I do not include because it's a subscription only tool that only some University libraries have. its also more based on text similarity than citations (see below)

More academic libraries have access to EDS or Ebsco Discovery service. If you have access to that you can use the concept map that allows you to explore papers and reports by concepts (knowledge graph essentially) https://connect.ebsco.com/s/article/Concept-Map-Quick-Start-Guide

Another related class of tools are Iris.ai, open knowledge maps that rely more on textual analysis rather than just citations which imho leads to more unpredictable results. Some tools like Litmap starting to incorporate this in small amounts eg title similarity algo etc. This area likely to radical change as language models like GPT-3 become widely used

Another respondent suggested ASREVIEWS which is a tool that uses machine learning (active learning) to screen papers based on titles and abstracts.

You essentially train the model by telling it which papers are relevant or not and then it uses the model on remaining papers you feed it (typically via a keyword search).

There are a couple of tools like this but are typically used more for systematic reviews and meta-analysis which has a totally different ecosystem of tools to consider.

Edit 2

I have a complementary post up about finding review papers which you can use as another complimentary technique to help guide your literature review

https://www.reddit.com/r/PhD/comments/mvux6e/ysk_starting_your_research_by_finding_review/

Edit 3

Added a reddit post on academic search + Large Language Model functionality, eg Elicit. Com, Scopus AI, Consensus, Undermind