We've built Connected Papers - a visual tool for researchers to find and explore academic papers

by discordy2 min read8th Jun 202029 comments


Scholarship & LearningSoftware ToolsWorld ModelingWorld Optimization

Hi LessWrong. I'm a long time lurker and finally have something that I'm really proud to share with you.

After a long beta, we are releasing Connected Papers to the public!

Connected papers is a unique, visual tool to help researchers and applied scientists find and explore papers relevant to their field of work.

First - let's look at a couple of examples graphs for work that is representative of this community:

Nick Bostrom:


Eliezer Yudkowsky, Nate Soares:


Did you find new and interesting papers to read? Would this be helpful as an introduction to the literature of a new field of study?

The problem

Almost every research project in academia or industry involves phases of literature review. Many times we find an interesting paper, and we’d like to:

  • Find different methods and approaches to the same subject
  • Track down the state of the art research in the field
  • Identify seminal works and background reading
  • Explore and immerse ourselves in the topic and become aware of the trends and dynamics in the literature

Previously, the best ways to do this were to browse reference lists, or hope to find good keywords in textual search engines and databases.

Enter Connected Papers

It started as a side project between friends. We’ve felt the pains of academic literature review and exploration for years and kept thinking about how to solve it.

For the past year we’ve been meeting on weekends and prototyping a tool that would allow a very different type of search process for academic papers. When we saw how much it improved our own research and development workflows — and got increasingly more requests from friends and colleagues to use it — we committed to release it to the public.

You know… for science.

So how does it work?

Connected Papers is not a citation tree. Those have been done before.
In our 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 positioned close to each other in the graph.

To get a bit technical, our similarity is based primarily on the concepts of co-citation and bibliographic coupling (aka co-reference). 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.

Reading the graph

Our graph is designed to make the important and relevant papers pop out immediately

With our layout algorithm, similar papers cluster together in space and are connected by stronger lines (edges). Popular papers (that are frequently cited) are represented by bigger circles (nodes) and more recent papers are represented by a darker color.

So for example, finding an important new paper in your field is as easy as identifying the dark large node at the center of a big cluster.

List view

In some cases it is convenient to work with just a list of connected papers. For these occasions, we’ve built the List view which you can access by clicking “Expand” at the top of the left panel. Here you can view additional paper details as well as sort and filter them according to various properties.

Prior and derivative works

The Prior works feature lists the top common ancestral papers for the connected papers in the graph. It usually includes seminal works in the field that heavily influenced the next generation.

Meanwhile, the Derivative works feature is the opposite: it shows a list of common descendants of the papers in the graph. It usually includes relevant state of the art papers or systematic reviews and meta-analyses in the field.

We have found these features to be especially useful when we have a paper from one era of research and we would like to be directed to the preceding and succeeding generations of research on the same topic

Help us spread the word

Connected Papers will only grow by word of mouth. Please share Connected Papers in your scientific community!

We are very eager to see how the broader academic community adopts and responds to this tool. We welcome all forms of feedback and would love to brainstorm together about how it can further evolve and improve.