Abstract
New scientific ideas drive progress, yet measuring scientific novelty remains challenging. We use natural language processing to detect the origin and impact of new ideas in scientific publications. To validate our methods, we analyze No-bel Prize-winning papers, which likely pioneered impactful new ideas, and lit-erature review papers, which typically consolidate existing knowledge. We also show that novel papers have more intellectual neighbors published after them, indicating they are ahead of their intellectual peers. Finally, papers introducing new ideas, particularly those with greater follow-on reuse, attract more citations.
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© 2025 The President and Fellows of Harvard College and the Massachusetts Institute of Technology. Published under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.
2025
The President and Fellows of Harvard College and the Massachusetts Institute of Technology
This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the use is non-commercial and the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by-nc/4.0
