Skip to main content
SpringerLink
Log in

Breakthrough paper indicator 2.0: can geographical diversity and interdisciplinarity improve the accuracy of outstanding papers prediction?

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

We report progress on new developments in the breakthrough paper indicator, which allows early selection of a small group of publications which may become potential breakthrough candidates based on dynamics of publication citations and certain qualitative characteristics of citations. We used a quantitative approach to identify typical citation patterns of highly cited papers. Based on these analyses, we propose two forecasting models to select groups of breakthrough paper candidates that exceed high citation thresholds five years post-publication. Here we study whether interdisciplinarity in the subject categories or geographical diversity serve as possible measures to improve ranking of breakthrough paper candidates. We found that ranked geographical diversities of known breakthrough papers have equal or better ranks than corresponding citations ranks. This allows us to apply additional filtering for better identifications of breakthrough candidates. We studied several interdisciplinarity indices, including richness, Shannon index, Simpson index, and Rao-Stirling-Porter index. We did not find any correlations between citation ranks and ranked interdisciplinarity indices.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. For example, compare more than 97,000 publications in the WOS “Material Science, Multidisciplinary” subject category versus 585 publications in “Literature, African, Australian, Canadian” in 2011.

References

  • Abrahams, E., et al. (1979). Scaling theory of localization: absence of quantum diffusion in two dimensions. Physical Review Letters, 42(10), 673–676.

    Article  Google Scholar 

  • Aversa, E. S. (1985). Citation patterns of highly cited papers and their relationship to literature aging: a study of the working literature. Scientometrics, 7, 383–389.

    Article  Google Scholar 

  • Barábasi, A.-L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286, 509–512.

    Article  MathSciNet  Google Scholar 

  • Chen, Chaomei, et al. (2009). Towards an explanatory and computational theory of scientific discovery. Journal of Informetrics, 3, 191–209.

    Article  Google Scholar 

  • Conover, W. J. (1999). Practical nonparametric statistics (3rd ed.). New York: John Willey & Sons.

    Google Scholar 

  • De Solla Price, D. J. (1965). Network of Scientific Papers. Science, 149, 510–515.

    Article  Google Scholar 

  • De Solla Price, D. J. (1976). General theory of bibliometric and other cumulative advantage processes. Journal of the American Society for Information Science, 27(5–6), 292–306.

    Article  Google Scholar 

  • Distel, R. J., et al. (1987). Nucleoprotein complexes that regulate gene expression in adipocyte differentiation: direct participation of c-fos. Cell, 49(6), 835–844.

    Article  Google Scholar 

  • Edwards, R. G., & Steptoe, P. C. (1978). Birth after reimplantation of a human embryo. Lancet, 312(8085), 366.

    Google Scholar 

  • Frenken, K., et al. (2005). The citation impact of research collaboration in science-based industries: A spatial-institutional analysis. Papers in regional science, 89(2), 351–371.

    Article  Google Scholar 

  • Garfield, E. (1955). Citation indexes for science: a new dimension in documentation through association of ideas. Science, 122(3159), 108–111.

    Article  Google Scholar 

  • Garfield, E. (1972). Citation analysis as a tool in journal evaluation: journals can be ranked by frequency and impact of citations for science policy studies. Science, 178, 471.

    Article  Google Scholar 

  • Garfield, E. (1990). Who will win the nobel prize in economics: here is a forecast based on citation indicators. Current Contents, 11, 3–7.

    Google Scholar 

  • Garfield, E., & Welljams-Dorof, A. (1992). Of nobel class: a citation perspective on high impact research authors. Theoretical Medicine, 13, 117–135.

    Article  Google Scholar 

  • Geller, N. L., de Cani, J. S., & Davis, R. E. (1981). Lifetime-citation rates: a mathematical model to compare scientists’ work. Journal of the American Society for Information Science, 32(1), 3–15.

    Article  Google Scholar 

  • Glänzel, W., et al. (2003). Better late than never? On the chance to become highly cited only beyond the standard bibliometric time horizon. Scientometrics, 58(3), 571–586.

    Article  Google Scholar 

  • Heck, R. F. (1968). Acylation, methylation, and carboxyalkylation of olefins by Group VIII metal derivatives. The Journal of the American Chemical Society, 90(20), 5518–5526.

    Article  Google Scholar 

  • Katz, J. S. (1994). Geographical proximity and scientific collaboration. Scientometrics, 31, 31–43.

    Article  Google Scholar 

  • Katz, J. S., & Martin, B. R. (1997). What is research collaboration? Research Policy, 26(1), 1–18.

    Article  Google Scholar 

  • Kohn, W., & Sham, L. J. (1965). Self-consistent equations including exchange and correlation effects. Physical Review Letters, 140(4A), A1133–A1138.

    MathSciNet  Google Scholar 

  • Leydesdorff, L., & Rafols, I. (2011). Indicators of the interdisciplinarity of journals: diversity, centrality, and citations. Journal of Informetrics, 5, 87–100.

    Article  Google Scholar 

  • Merton, R. K. (1968). Matthew effect in science. Science, 159(3810), 56–63.

    Article  Google Scholar 

  • Nalimov V.V. and Mul’chenko Z.M. (1969): Naukometriya. Izuchenie nauki kak informatsionnogo protsessa (Scientometrics. Study of science as an information process.) Moscow: Nauka, 192 pgs (Available in English: http://www.garfield.library.upenn.edu/nalimov/nalimovmeasurementofscience/book.pdf).

  • Novoselov, K. S., et al. (2004). Electric field effect in atomically thin carbon films. Science, 306(5696), 666–669.

    Article  Google Scholar 

  • Pendlebury, D. (1989). The 1989 nobel prize in medecine: 20 who desrve it. Scientist, 3(19), 14–15.

    Google Scholar 

  • Ponomarev, I. V., et al. (2014). Predicting highly cited papers: A method for early detection of candidates breakthroughs. Technological Forecasting and Social Change, 81, 49–55.

    Article  Google Scholar 

  • Porter, A. L., et al. (2007). Measuring researcher interdisciplinarity. Scientometrics, 72, 117–147.

    Article  Google Scholar 

  • Rafols, I., & Meyer, M. (2010). Diversity and network coherence as indicators of interdisciplinarity: case studies in bionanoscience. Scientometrics, 82, 263–287.

    Article  Google Scholar 

  • Rao, C. R. (1982). Diversity, its meausrement, decomposition, apportionment and analysis. Sankhya: The Indian Journal of Statistics, 44, 1–21.

    MATH  Google Scholar 

  • Redner, S. (2005). Citation statistics from 110 years of Physical Review. Physics Today, 58, 49–54.

    Article  Google Scholar 

  • Rousseau, L., & Egghe, R. (1990). Introduction to informetrics: quantitative methods in library, documentation and information science. Amsterdam: Elsevier.

    Google Scholar 

  • Small, H. G. (1973). Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for Information Science, 24, 265–269.

    Article  Google Scholar 

  • van Raan, A. F. J. (2000). On growth, ageing, and fractal differentiation of Science. Scientometrics, 47, 347–362.

    Article  Google Scholar 

  • Weinberg, S. (1973). A model of leptons. Physical Review Letters, 19(21), 1264–1266.

    Article  Google Scholar 

Download references

Acknowledgments

We are very thankful to Y. Seger for editorial assistance.

Author information

Authors and Affiliations

  1. Thomson Reuters, 1455 Research Blvd., 2nd Floor, Rockville, MD, 20850, USA

    Ilya V. Ponomarev, Duane E. Williams & Joshua D. Schnell

  2. Redtail Creek Software, Rockville, MD, USA

    Brian K. Lawton

Authors
  1. Ilya V. Ponomarev
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Brian K. Lawton
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Duane E. Williams
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Joshua D. Schnell
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ilya V. Ponomarev.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ponomarev, I.V., Lawton, B.K., Williams, D.E. et al. Breakthrough paper indicator 2.0: can geographical diversity and interdisciplinarity improve the accuracy of outstanding papers prediction?. Scientometrics 100, 755–765 (2014). https://doi.org/10.1007/s11192-014-1320-9

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-014-1320-9

Keywords

Search

Navigation