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A study of the correlation between publication delays and measurement indicators of journal articles in the social network environment—based on online data in PLOS

Author

Listed:
  • Jingda Ding

    (Shanghai University)

  • Dehui Du

    (Shanghai University)

Abstract

The development of network technique and open access has made numerous research results freely obtained online, thereby facilitating the growth of the emerging evaluation methods of Altmetrics. However, it is unknown whether the time interval from reception to publication has an impact on the evaluation indicators of articles in the social network environment. We construct a range of time-series indexes that represent the features of the evaluation indicators and then explore the correlation of acceptance delay, technical delay, and overall delay with the relevant indicators of citations, usage, sharing and discussions, and collections that are obtained from the open access journal platform PLOS. Moreover, this research also explores the differences in the correlations of the delays for the literature in six subject areas with the corresponding indicators and the discrepancies of the correlations of delays and indexes in various metric quartiles. The results of the Mann–Whitney U test reveal that the length of delays affects the performance of the literature on some indicators. This study indicates that reducing the acceptance time and final publication time of articles can improve the efficiency of knowledge diffusion through the formal academic citation channel, but in the context of social networking communication, an appropriate interval at a particular stage in the publishing process can enhance the heat of sharing, discussion, and collection of articles to a small extent, hence boosting the influence and attention received by the literature on the internet.

Suggested Citation

  • Jingda Ding & Dehui Du, 2023. "A study of the correlation between publication delays and measurement indicators of journal articles in the social network environment—based on online data in PLOS," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1711-1743, March.
    • Handle: RePEc:spr:scient:v:128:y:2023:i:3:d:10.1007_s11192-023-04640-6
    DOI: 10.1007/s11192-023-04640-6
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    References listed on IDEAS

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