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Aging, obsolescence, impact, growth, and utilization: Definitions and relations

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  • Leo Egghe
  • Ronald Rousseau

Abstract

The notions aging, obsolescence, impact, growth, utilization, and their relations are studied. It is shown how to correct an observed citation distribution for growth, once the growth distribution is known. The relation of this correction procedure with the calculation of impact measures is explained. More interestingly, we have shown how the influence of growth on aging can be studied over a complete period as a whole. Here, the difference between the so‐called average and global aging distributions is the main factor. Our main result is that growth can influence aging but that it does not cause aging. A short overview of some classical articles on this topic is given. Results of these earlier works are placed in the framework set up in this article.

Suggested Citation

  • Leo Egghe & Ronald Rousseau, 2000. "Aging, obsolescence, impact, growth, and utilization: Definitions and relations," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 51(11), pages 1004-1017.
    • Handle: RePEc:bla:jamest:v:51:y:2000:i:11:p:1004-1017
    DOI: 10.1002/1097-4571(2000)9999:99993.0.CO;2-8
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    Cited by:

    1. P. Vinkler, 2010. "Indicators are the essence of scientometrics and bibliometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(3), pages 861-866, December.
    2. Wolfgang Glänzel, 2004. "Towards a model for diachronous and synchronous citation analyses," Scientometrics, Springer;Akadémiai Kiadó, vol. 60(3), pages 511-522, August.
    3. Hamid Bouabid & Vincent Larivière, 2013. "The lengthening of papers’ life expectancy: a diachronous analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 695-717, December.
    4. Lutz Bornmann & Rüdiger Mutz, 2015. "Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(11), pages 2215-2222, November.
    5. Lorena Espina-Romero & Doile Ríos Parra & José Gregorio Noroño-Sánchez & Gloria Rojas-Cangahuala & Luz Emerita Cervera Cajo & Pedro Alfonso Velásquez-Tapullima, 2024. "Navigating Digital Transformation: Current Trends in Digital Competencies for Open Innovation in Organizations," Sustainability, MDPI, vol. 16(5), pages 1-19, March.
    6. Lee, Changyong & Cho, Yangrae & Seol, Hyeonju & Park, Yongtae, 2012. "A stochastic patent citation analysis approach to assessing future technological impacts," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 16-29.
    7. Richard Klavans & Kevin W. Boyack, 2008. "Thought leadership: A new indicator for national and institutional comparison," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(2), pages 239-250, May.
    8. Mingyang Wang & Shi Li & Guangsheng Chen, 2017. "Detecting latent referential articles based on their vitality performance in the latest 2 years," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1557-1571, September.
    9. Jang, Hyun Jin & Woo, Han-Gyun & Lee, Changyong, 2017. "Hawkes process-based technology impact analysis," Journal of Informetrics, Elsevier, vol. 11(2), pages 511-529.
    10. Henneken, Edwin A. & Kurtz, Michael J. & Accomazzi, Alberto & Grant, Carolyn S. & Thompson, Donna & Bohlen, Elizabeth & Murray, Stephen S., 2009. "Use of astronomical literature—A report on usage patterns," Journal of Informetrics, Elsevier, vol. 3(1), pages 1-8.
    11. Shesen Guo & Ganzhou Zhang, 2017. "Analyzing concept complexity, knowledge ageing and diffusion pattern of Mooc," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 413-430, July.
    12. Wildgaard, Lorna, 2016. "A critical cluster analysis of 44 indicators of author-level performance," Journal of Informetrics, Elsevier, vol. 10(4), pages 1055-1078.
    13. Saralees Nadarajah & Samuel Kotz, 2007. "Models for citation behavior," Scientometrics, Springer;Akadémiai Kiadó, vol. 72(2), pages 291-305, August.
    14. Jerome K. Vanclay, 2009. "Bias in the journal impact factor," Scientometrics, Springer;Akadémiai Kiadó, vol. 78(1), pages 3-12, January.
    15. Leo Egghe & Ronald Rousseau, 2002. "A proposal to define a core of a scientific subject: A definition using concentration and fuzzy sets," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(1), pages 51-62, April.
    16. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    17. Emil Hudomalj & Gaj Vidmar, 2003. "OLAP and bibliographic databases," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(3), pages 609-622, November.
    18. Vicente P. Guerrero-Bote & Félix Moya-Anegón, 2014. "Relationship between downloads and citations at journal and paper levels, and the influence of language," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1043-1065, November.
    19. Xianwen Wang & Zhichao Fang & Xiaoling Sun, 2016. "Usage patterns of scholarly articles on Web of Science: a study on Web of Science usage count," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 917-926, November.

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