TY - JOUR
T1 - Quantifying long-term scientific impact
AU - Wang, Dashun
AU - Song, Chaoming
AU - Barabási, Albert László
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84885660552&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84885660552&partnerID=8YFLogxK
U2 - 10.1126/science.1237825
DO - 10.1126/science.1237825
M3 - Article
C2 - 24092745
AN - SCOPUS:84885660552
SN - 0036-8075
VL - 342
SP - 127
EP - 132
JO - Science
JF - Science
IS - 6154
ER -