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Quantifying Long-Term Scientific Impact

arXiv 1306.3293 ↗First posted 14 Jun 2013cs.DL cs.SI physics.soc-phcited by 28

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Abstract (arXiv)

The lack of predictability of citation-based measures frequently used to gauge impact, from impact factors to short-term citations, raises a fundamental question: Is there long-term predictability in citation patterns? Here, we derive a mechanistic model for the citation dynamics of individual papers, allowing us to collapse the citation histories of papers from different journals and disciplines into a single curve, indicating that all papers tend to follow the same universal temporal pattern. The observed patterns not only help us uncover basic mechanisms that govern scientific impact but also offer reliable measures of influence that may have potential policy implications.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Jun 2013.

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Citing papers per year: 2021: 1; 2022: 2; 2023: 5; 2024: 5; 2025: 5; 2026: 10.

28 papers.

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  1. 2024Forecasting high-impact research topics via machine learning on evolving knowledge graphscited by 21
  2. 2025How Deep Do Large Language Models Internalize Scientific Literature and Citation Practices?cited by 10
  3. 2026AutoResearch AI: Towards AI-Powered Research Automation for Scientific Discoverycited by 9
  4. 2026AI Can Learn Scientific Tastecited by 8
  5. 2026Proof of Time: A Benchmark for Evaluating Scientific Idea Judgmentscited by 5
  6. 2023H2CGL: Modeling Dynamics of Citation Network for Impact Predictioncited by 3
  7. 2023CasCIFF: A Cross-Domain Information Fusion Framework Tailored for Cascade Prediction in Social Networkscited by 2
  8. 2024Is Peer-Reviewing Worth the Effort?cited by 2
  9. 2026SciImpact: A Multi-Dimensional, Multi-Field Benchmark for Scientific Impact Predictioncited by 2
  10. 2021A Measure of Research Tastecited by 1
  11. 2022Quantifying the Online Long-Term Interest in Researchcited by 1
  12. 2023A multiple k-means cluster ensemble framework for clustering citation trajectoriescited by 1
16 more
  1. 2023Predicting Scientific Impact Through Diffusion, Conformity, and Contribution Disentanglementcited by 1
  2. 2025BioMedJImpact: A Comprehensive Dataset and LLM Pipeline for AI Engagement and Scientific Impact Analysis of Biomedical Journalscited by 1
  3. 2026ReviewGuard: Aligning LLM-Assisted Peer Review with Long-Term Scientific Impactcited by 1
  4. 2026Can Large Language Models Forecast What Researchers Study Next?cited by 1
  5. 2022Using Full-Text Content to Characterize and Identify Best Seller Bookscited by 0
  6. 2023Hidden Citations Obscure True Impact in Sciencecited by 0
  7. 2024Time to Cite: Modeling Citation Networks using the Dynamic Impact Single-Event Embedding Modelcited by 0
  8. 2024Learning the mechanisms of network growthcited by 0
  9. 2024On Your Mark, Get Set, Predict! Modeling Continuous-Time Dynamics of Cascades for Information Popularity Predictioncited by 0
  10. 2025A Causal Inference Approach for Quantifying Research Impactcited by 0
  11. 2025Emergent evaluation hubs in a decentralizing large language model ecosystemcited by 0
  12. 2025Deep versus Broad Technology Search and the Timing of Innovation Impactcited by 0
  13. 2026LitPivot: Developing Well-Situated Research Ideas Through Dynamic Contextualization and Critique within the Literature Landscapecited by 0
  14. 2026FAME: Forecasting Academic Impact via Continuous-Time Manifold Evolutioncited by 0
  15. 2026MIRAI: Prediction and Generation of High-Impact Academic Researchcited by 0
  16. 2026GitScholar: A Dataset for Predicting AI Research Impact from GitHub Engagementcited by 0