Scientometric engineering: Exploring citation dynamics via arXiv eprints
- URL: http://arxiv.org/abs/2106.05027v2
- Date: Sat, 5 Feb 2022 09:13:12 GMT
- Title: Scientometric engineering: Exploring citation dynamics via arXiv eprints
- Authors: Keisuke Okamura
- Abstract summary: We investigate the citation data of more than 1.5 million eprints on arXiv.
We find that the typical growth and obsolescence patterns vary across disciplines.
We derive a model consistent with the observed quantitative and temporal characteristics of citation growth and obsolescence.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Scholarly communications have been rapidly integrated into digitised and
networked open ecosystems, where preprint servers have played a pivotal role in
accelerating the knowledge transfer processes. However, quantitative evidence
is scarce regarding how this paradigm shift beyond the traditional journal
publication system has affected the dynamics of collective attention on
science. To address this issue, we investigate the citation data of more than
1.5 million eprints on arXiv (https://arxiv.org/) and analyse the long-term
citation trend for each discipline involved. We find that the typical growth
and obsolescence patterns vary across disciplines, reflecting different
publication and communication practices. The results provide unique evidence on
the attention dynamics shaped by the research community today, including the
dramatic growth and fast obsolescence of Computer Science eprints, which has
not been captured in previous studies relying on the citation data of journal
papers. Subsequently, we develop a quantitatively-and-temporally normalised
citation index with an approximately normal distribution, which is useful for
comparing citational attention across disciplines and time periods. Further, we
derive a stochastic model consistent with the observed quantitative and
temporal characteristics of citation growth and obsolescence. The findings and
the developed framework open a new avenue for understanding the nature of
citation dynamics.
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