Our paper on the mobility of scientists through the knowledge landscape has been accepted in EPJ Data Science! In this study, we build on our earlier work on the rise and fall of scientific fields in arXiv (see this post), and propose a new lens: what if we studied science like we study human movement?

We constructed a low-dimensional map of scientific knowledge using t-SNE embeddings of 1.5 million arXiv preprints across physics, computer science, and mathematics. This space allows us to track researchers as they “move” through fields via their publications—each trajectory forming a unique scientific path through the landscape.

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