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Total influence and mainstream measures for scientific researchers

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  • Liu, John S.
  • Lu, Louis Y.Y.
  • Ho, Mei Hsiu-Ching

Abstract

We propose two new indices that are able to measure a scientific researcher's overall influence and the level of his/her works’ association with the mainstream research subjects within a scientific field. These two new measures – the total influence index and the mainstream index – differ from traditional performance measures such as the simple citation count and the h-index in that they take into account the indirect influence of an author's work. Indirect influence describes a scientific publication's impact upon subsequent works that do not reference it directly. The two measures capture indirect influence information from the knowledge emanating paths embedded in the citation network of a target scientific field. We take the Hirsch index, data envelopment analysis, and lithium iron phosphate battery technology field to examine the characteristics of these two measures. The results show that the total influence index favors earlier researchers and successfully highlights those researchers who have made crucial contributions to the target scientific field. The mainstream index, in addition to underlining total influence, also spotlights active researchers who enter into a scientific field in a later development stage. In summary, these two new measures are valuable complements to traditional scientific performance measures.

Suggested Citation

  • Liu, John S. & Lu, Louis Y.Y. & Ho, Mei Hsiu-Ching, 2012. "Total influence and mainstream measures for scientific researchers," Journal of Informetrics, Elsevier, vol. 6(4), pages 496-504.
    • Handle: RePEc:eee:infome:v:6:y:2012:i:4:p:496-504
    DOI: 10.1016/j.joi.2012.04.005
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    References listed on IDEAS

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    Cited by:

    1. Chao Min & Qingyu Chen & Erjia Yan & Yi Bu & Jianjun Sun, 2021. "Citation cascade and the evolution of topic relevance," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(1), pages 110-127, January.
    2. Yan, Jianghui & Tseng, Fang-Mei & Lu, Louis Y.Y., 2018. "Developmental trajectories of new energy vehicle research in economic management: Main path analysis," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 168-181.
    3. Jiang, Xiaorui & Zhuge, Hai, 2019. "Forward search path count as an alternative indirect citation impact indicator," Journal of Informetrics, Elsevier, vol. 13(4).

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