I'd like to see how a given paper has impacted its own discipline and then spilled over to others.

Let's take Nash's paper on Equilibrium points in n-person games as an example. This work has eventually yielded him a Nobel prize and has +6k citations on Google Scholar.

I'm assuming it must have been first cited primarily by other mathematics papers; but over time, scholars from other disciplines would increasingly cite it.

Are you familiar with any tool/method that would provide this kind of information? It would be the most useful if it's possible to visualize the data.

  • Seems related to academia.stackexchange.com/questions/14258/… (and a few posts linked to there...) but I'm not sure whether any of the answers suggested would conclusively help here. Commented Apr 3, 2018 at 4:54
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    Thanks, I had seen this discussion, but it's not exactly what I have in mind. Producing a graph like this would still require data that accounts for 1) dates 2) disciplines Commented Apr 3, 2018 at 6:50
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    The date is part of the citation, the discipline is part of the journal. It is not convenient, but such coding of data is just part of doing research. Data doesn't fall from the sky like mana, collecting it is hard work. Commented Apr 3, 2018 at 9:51

2 Answers 2


You may try Microsoft Academic for that. They have an interesting semantic-web approach to finding answers to your queries and they also aggregate a lot of context information. This includes citations that can be filtered in various ways.

Have a look at this search regarding your questions's example: https://academic.microsoft.com/paper/2067050450/citedby/search?q=Equilibrium%20points%20in%20n-person%20games&qe=RId%3D2067050450&f=&eyl=Y%3C%3D1956&orderBy=0 (you were right: initially, most citations were from mathematics).


A second-best solution is LENS.ORG; it allows you to see such patterns (at least partly):

  1. Search for the paper and click on its citations (example for Nash's Equilibrium Points here).
  2. Click on "View items in Scholar Search" (example for Nash's paper here)
  3. Click on "Analysis" (example for Nash's paper here)
  4. Look at the graphs "Scholarly Works over Time" and "Top Fields of Study"

This may give you a vague (but not precise) idea about the inter-disciplinary spread of the paper's impact.

The better solution would be a bibliometric analysis which you'd have to code by your own, perhaps using a downloaded, machine-readable bibliography from Web of Science (Journal Citation Reports) or CrossRef. Tools like Bibliometrix for R could help you with that. The exact approach would require a much more complex answer.

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