Quantifying Long-term Scientific Impact
نویسندگان
چکیده
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.
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Comment on "Quantifying Long-term Scientific Impact"
The paper comments on “Quantifying long-term scientific impact”. It indicates that there is a mistake of [D. S. Wang, C. Song, A. L. Barabási. Quantifying long-term scientific impact, Science, 342, 127 (2013)].
متن کاملComment on “ Quantifying long - term scientific impact ”
Wang et al. (Reports, 4 October 2013, p. 127) claimed high prediction power for their model of citation dynamics. We replicate their analysis but find discouraging results: 14.75% papers are estimated with unreasonably large m (>5) and l (>10) and correspondingly enormous prediction errors. The prediction power is even worse than simply using short-term citations to approximate long-term citati...
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ورودعنوان ژورنال:
- Science
دوره 342 6154 شماره
صفحات -
تاریخ انتشار 2013