Abstract
In this study, we introduce a new literature-aging conceptual model to study the citation curve and discuss its implications. First, we improve the conceptual model by adding a period to describe the “death” of citations. Second, we offer a feasible operationalization for this conceptual model and implement a set of cross-discipline publications in the Web of Science to test its performance. Furthermore, we propose two measurements according to the new model—“Sleeping Period” and “Recognition Period”—to capture publications’ citation curve patterns. For instance, we find that half of the papers in Arts & Humanities published in 1985 receive no or extremely few citations in the first 5 years after their publication; after that, on average, those papers in Arts & Humanities have a 5-year-long period when their citations grow rapidly. In addition, we observe a special phenomenon named “literature revival” as some publications may have multiple citation life-cycles, which has received little attention from current research. Finally, we discuss the implications of our study, especially the application of the Sleeping Period and Recognition Period in improving scientific evaluation and collection development in libraries, and the inspiration of the “literature revival”.
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Notes
In the current study, the “uncited paper” always refers to the publications which only have Period I, not the publications whose number of citations is zero.
Some papers were published in January and some papers were published at the end of 1985. Thus, we select the data from 1985 to 2015 (including 2015) to ensure the citation window is not shorter than 30 years. This would lead some papers’ citation window to be close to 31 years. Yet, compared to the citation window, the nuance is very insignificant and we thus ignore it practically.
To ensure that HC publications strictly have more citations than the other 99%, we exclude publications from the HC group that have the same number of citations as other publications in the 99% group. Thus, the number of HC publications may not exactly equal the 1% of the total number of all publications. This is also the case for NHC publications.
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Acknowledgements
An early version of this paper was presented at the 18th International Conference on Scientometrics and Informetrics (ISSI 2021) (Gou et al., 2021). The authors are grateful to all members in the KD lab at Peking University and for the financial support from the Youth Project of the Humanities and Social Sciences of the Ministry of Education of China (No. 21YJC870001). This research was supported by the High-performance Computing Platform of Peking University. This work uses Web of Science data by Clarivate Analytics provided by the Indiana University Network Science Institute and the Cyberinfrastructure for Network Science Center at Indiana University.
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See Tables 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, and Fig. 5.
Boxplot for length of SP/RP for different disciplines. Note: Number 1–6 represent Arts & Humanities, Clinical, Pre-clinical & Health, Engineering & Technology, Life Sciences, Physical Sciences, and Social Sciences, respectively
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Gou, Z., Meng, F., Chinchilla-Rodríguez, Z. et al. Encoding the citation life-cycle: the operationalization of a literature-aging conceptual model. Scientometrics 127, 5027–5052 (2022). https://doi.org/10.1007/s11192-022-04437-z
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DOI: https://doi.org/10.1007/s11192-022-04437-z