Connected Papers: a visual tool to explore related papers for your research

When I opened my email this morning I’ve received the most unimaginable gift that I could ever think that I would have in my hands and that would help me instantaneously with my PhD. “What was it? What was it?” You might be wondering. Well, it’s a visual tool to help researchers and applied scientists find and explore papers relevant to their field of work. It’s called Connected Papers. Isn’t it just marvellous that this tool exists? At least for visual people (like me) can help us to have a general visual framework with a unique graph embedded with all the literature regarding a specific topic. This tool can be really beneficial for exploring related papers and for building a more collaborative and open-minded science community.

Note: You can read about the story behind this tool here.


How do Connected Papers work?

  • To create a graph (coming from a paper), they analyze ~50,000 papers and select the few dozen with the strongest connections to the origin paper.
  • In the graph, papers are arranged according to their similarity. That means that even papers that do not directly cite each other can be strongly connected and very closely positioned. Connected Papers is not a citation tree.
  • Their similarity metric is based on the concepts of Co-citation and Bibliographic Coupling. According to this measure, two papers that have highly overlapping citations and references are presumed to have a higher chance of treating a related subject matter.
  • Their algorithm then builds a Force Directed Graph to distribute the papers in a way that visually clusters similar papers together and pushes less similar papers away from each other.
  • Their database is connected to the Semantic Scholar Paper Corpus (licensed under ODC-BY), a team that has compiled hundreds of millions of published papers across many scientific fields.

Let’s see an example!

  • First of all, you have to choose an article related to your topic. In my case, I wonder about “modulations of alpha-oscillations in visual perception“. Thus, I selected a recent paper by Zazio et al., 2020 under the title “Modelling the effects of ongoing alpha activity on visual perception: The oscillation-based probability of response“.


  • Then, you select your paper among the options they give you, according to the input you gave (e.g., paper title, paper URL), and select the button “Build a graph“.


  • Boom! You now have the graph right in front of you and you can start exploring all the nodes. Here are a few notes on how to read the graph:
    • Each node is an academic paper related to the input paper.
    • Node size is the number of citations.
    • Node colour is the publishing year.
    • Similar papers cluster together in space and have stronger connecting lines.


  • If you explore with the cursor the nodes, you can see more detailed information about the selected paper on the right panel:
    • General info (e.g., the title, the authors, the journal, the year of publication, number of citations and references)
    • Abstract of the paper
    • A link to Semantic Scholar with further details about the paper.
    • The option of building another graph with this paper.


Hope you find this tool useful (as I do) and can help you to make your life easier (at least, in your research).


Feature image from Pexels – C0 license.

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