Science of Success

Quantifying Long-Term Scientific Impact

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.


More publications
G. Ghoshal, L. Chi, A.-L. Barabási

Scientifc Reports 3, 1-8 (2013)

B. Barzel, A.-L. Barabási

Nature Biotechnology 31: Num 8, 1-8 (2013)