Nonuniversal power law scaling in the probability distribution of scientific citations
arXiv:1009.0574 · doi:10.1073/pnas.1010757107
Abstract
We develop a model for the distribution of scientific citations. The model involves a dual mechanism: in the direct mechanism, the author of a new paper finds an old paper A and cites it. In the indirect mechanism, the author of a new paper finds an old paper A only via the reference list of a newer intermediary paper B, which has previously cited A. By comparison to citation databases, we find that papers having few citations are cited mainly by the direct mechanism. Papers already having many citations ('classics') are cited mainly by the indirect mechanism. The indirect mechanism gives a power-law tail. The 'tipping point' at which a paper becomes a classic is about 21 citations for papers published in the Institute for Scientific Information (ISI) Web of Science database in 1981, 29 for Physical Review D papers published from 1975-1994, and 39 for all publications from a list of high h-index chemists assembled in 2007. The power-law exponent is not universal. Individuals who are highly cited have a systematically smaller exponent than individuals who are less cited.
7 pages, 3 figures, 2 tables
References in corpus (3)
Cited by in corpus (10)
- Principles of scientific research team formation and evolution
- Maximum Caliber: a general variational principle for dynamical systems
- Growing complex network of citations of scientific papers -- measurements and modeling
- Stochastic dynamical model of a growing network based on self-exciting point process
- A maximum entropy framework for non-exponential distributions
- Network-based statistical comparison of citation topology of bibliographic databases
- The distribution of shortest path lengths in a class of node duplication network models
- Towards a more realistic citation model: The key role of research team sizes
- The Demise of Single-Authored Publications in Computer Science: A Citation Network Analysis
- Do 'altmetric mentions' follow Power Laws? Evidence from social media mention data in Altmetric.com