Literature mapping on steroids
May 1, 2024
AI has put literature mapping on steroids, making it easier for you to find connected research. Literature mapping tools utilise artificial intelligence to enable users to explore and discover connections between peer reviewed articles on a research topic, based on citation networks and/or similarity.
Subject librarians have been exploring these mapping tools to find out how they work, and their pros and cons. And how well they work with New Zealand and Māori topics, plus Massey’s research disciplines. This will depend on the discipline, and the research area so your mileage will vary! We didn’t think they were great for Creative Arts but in most other areas worked well.
There are many tools already available, including ResearchRabbit, Litmaps, Elicit, Keenious to name just a few. Maquarie University Library has a guide to the most popular, and librarians at Texas Tech University have produced a daunting but probably still non-comprehensive list!
The tools are generally aimed at postgraduates or researchers and they can assist users with:
· Tracking and visualising connections between articles or authors
· Visualising citation and/or authorship connections and relationships
· Discovering articles based on papers you’ve already read
· Understanding research areas visually
· Generating or visualising search concepts
Typically, tools have a limited free version and various subscription levels. Some have institutional subscription options, but Massey at this stage doesn’t subscribe to any. This means Massey users should check Discover to see if they have access to articles as the tools don’t allow linking through to content that Massey subscribes to. New citations found can be exported to EndNote and Zotero. Tools vary where they draw citations from, which can affect their comprehensiveness. Usually the citation metadata comes from one or more open source databases such as Open Alex, Crossref, PubMed, and Semantic Scholar. Monash Health Library’s useful comparison graph of common tools covers where citations come from, import and export options and other useful info, including what they feel the tool is best used for.
What help can subject librarians offer? At this stage we’re not in a position to officially recommend any specific tool, however we think there’s enough potential for people to explore the tools and see if they find them useful for their research. Let us know what you think – are you currently using any AI literature mapping tool for your research? What support do you think the Library should provide?
Image by Markus Wexler, https://www.pexels.com/photo/a-green-scrabble-board-with-letters-spelling-out-ai-18524070/
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