Skip to main content

A citation-based cross-disciplinary study on literature ageing: part II—diachronous aspects

Abstract

In the first part of our study (Zhang and Glänzel in Scientometrics, 2017) we provided a view of the literature ageing based on a synchronous approach. Taking up the ideas by Egghe (Scientometrics 27(2):195–214, 1993) and Glänzel et al. (Scientometrics 109(3):2165–2179, 2016) we extend our study in the second part by applying a diachronous approach on the basis of citing literature. For this purpose we used the Prospective Price Index which was recently introduced by Glänzel et al. (Scientometrics 109(3):2165–2179, 2016). Finally, we compare the two aspects of literature ageing. In particular, we analyze the correlation between the share of recent references and the share of fast response, and found a generally positive correlation between both aspects at different levels of aggregation (subfields, major fields and the individual paper level). However, the consistence varies among different aggregations. For examples, on the level of subject fields, Chemistry, Biology, Neuroscience & Behavior are found with evidently better ranks by Prospective Price Index than Price Index, indicating their faster ageing process in the mirror of citations than references, while Engineering and Social sciences are found with the opposite ageing features. At the journal level, we observed a striking divergence between the reference and citation ageing patterns in some cases. Thus several journals proved ‘hard’ from the perspective of information sources (cited papers) but, at the same time, rather ‘soft’ in the light of information targets (citing papers).

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

References

  • Avramescu, A. (1979). Actuality and obsolescence of scientific literature. Journal of the American Society for Information Science (pre-1986), 30(5), 296–303.

    Article  Google Scholar 

  • Bouabid, H. (2011). Revisiting citation aging: A model for citation distribution and life-cycle prediction. Scientometrics, 88(1), 199–211.

    Article  Google Scholar 

  • Bouabid, H., & Larivière, V. (2013). The lengthening of papers’ life expectancy: A diachronous analysis. Scientometrics, 97(3), 695–717.

    Article  Google Scholar 

  • Burrell, QL. (2003). Predicting future citation behavior. Journal of the American Society for Information Science and Technology, 54(5), 372–378.

    Article  Google Scholar 

  • Corbyn, Z. (2010). An easy way to boost a paper’s citations. Nature. doi:10.1038/news.2010.406, http://www.nature.com/news/2010/100813/full/news.2010.406.html.

  • Egghe, L. (1993). On the influence of growth on obsolescence. Scientometrics, 27(2), 195–214.

    MathSciNet  Article  Google Scholar 

  • Egghe, L., & Ravichandra Rao, I. K. (1992). Citation age data and the obsolescence function: Fits and explanations. Information and Processing Management, 28(2), 201–217.

    Article  Google Scholar 

  • Finardi, U. (2014). On the time evolution of received citations, in different scientific fields: An empirical study. Journal of Informetrics, 8(1), 13–24.

    Article  Google Scholar 

  • Glänzel, W. (1997). On the reliability of predictions based on stochastic citation processes. Scientometrics, 40(3), 481–492.

    Article  Google Scholar 

  • Glänzel, W. (2004). Towards a model for diachronous and synchronous citation analyses. Scientometrics, 60(3), 511–522.

    Article  Google Scholar 

  • Glänzel, W., & Garfield, E. (2004). The myth of delayed recognition. The Scientist, 18(11), 8–9.

    Google Scholar 

  • Glänzel, W., Schlemmer, B., & Thijs, B. (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 

  • Glänzel, W., & Schoepflin, U. (1995). A bibliometric study on ageing and reception processes of scientific literature. Journal of Information Science, 21(1), 37–53.

    Article  Google Scholar 

  • Glänzel, W., & Schoepflin, U. (1999). A bibliometric study of reference literature in the sciences and social sciences. Information Processing and Management, 35(1), 31–44.

    Article  Google Scholar 

  • Glänzel, W., & Schubert, A. (1995). Predictive aspects of a stochastic model for citation processes. Information Processing and Management, 31(1), 69–80.

    Article  Google Scholar 

  • Glänzel, W., Thijs, B., & Chi, P. S. (2016). The challenges to expand bibliometric studies from periodical literature to monographic literature with a new data source: The book citation index. Scientometrics, 109(3), 2165–2179.

    Article  Google Scholar 

  • Lercher, A., & Smolinsky, L. (2016). Persistent value of older scientific journal articles. Scientometrics, 108(3), 1205–1220.

    Article  Google Scholar 

  • Mingers, J., & Burrell, Q. L. (2006). Modeling citation behavior in management science journals. Information Processing and Management, 42(6), 1451–1464.

    Article  Google Scholar 

  • Nadarajah, S., & Kotz, S. (2007). Models for citation behaviour. Scientometrics, 72(2), 291–305.

    Article  Google Scholar 

  • Nakamoto, H. (1988). Synchronous and dyachronous citation distributions. In L. Egghe & R. Rousseau (Eds.), Informetrics 87/88 (pp. 157–163). Amsterdam: Elsevier.

    Google Scholar 

  • Peritz, B. C. (1983). Are methodological papers more cited than theoretical or empirical ones? The case of sociology. Scientometrics, 5(4), 211–218.

    Article  Google Scholar 

  • Price, D. J. D. (1970). Citation measures of hard science, soft science, technology, and nonscience. In C. E. Nelson & D. K. Pollock (Eds.), Communication among scientists and engineers (pp. 3–22). Lexington, MA: Heath.

    Google Scholar 

  • Stinson, E. R., & Lancaster, F. W. (1987). Synchronous versus diachronous methods in the measurement of obsolescence by citation studies. Journal of Information Science, 13, 65–74.

    Article  Google Scholar 

  • Yu, G., & Li, Y. J. (2010). Identification of referencing and citation processes of scientific journals based on the citation distribution model. Scientometrics, 82, 249–261.

    Article  Google Scholar 

  • Zhang, L., & Glänzel, W. (2017). A citation-based cross-disciplinary study on literature aging. Part I: The synchronous approach. Scientometrics. doi:10.1007/s11192-017-2289-y.

  • Zhang, L., Rousseau, R., & Glänzel, W. (2016). Diversity of references as an indicator for interdisciplinarity of journals: Taking similarity between subject fields into account. Journal of the American Society for Information Science and Technology, 67(5), 1257–1265.

    Article  Google Scholar 

Download references

Acknowledgements

Lin Zhang acknowledges the National Natural Science Foundation of China Grants 71573085 and 71103064, the Innovation talents of science and technology in HeNan Province (16HASTIT038; 2015GGJS-108) and the research center of information technology & economic and social development in Zhejiang Province. We are grateful for two anonymous reviewers’ insightful comments and valuable advices.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Lin Zhang.

Appendix

Appendix

See Table 4.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Zhang, L., Glänzel, W. A citation-based cross-disciplinary study on literature ageing: part II—diachronous aspects. Scientometrics 111, 1559–1572 (2017). https://doi.org/10.1007/s11192-017-2288-z

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-017-2288-z

Keywords

  • Literature ageing
  • Price Index
  • Prospective Price Index
  • References
  • Citations