Quantifying Long-term Scientiﬁc Impact
Dashun Wang, Chaoming Song, and Albert-L´aszl´o Barab´asi
Center for Complex Network Research, Department of Physics,
Biology and Computer Science, Northeastern University, Boston, Massachusetts 02115, USA
An ability to accurately assess the long-term impact of a scientiﬁc discov-ery has implications from science policy to individual reward. Yet, the documented 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 pat-terns? 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 follow the same universal temporal pattern. The observed patterns not only help us uncover the basic mechanisms that govern scientiﬁc impact, but also oﬀer reliable measures of inﬂuence with potential policy implications.