Using Networks to Measure Influence and Impact

Zhang, Li Xian; Liu, Yu Jia; Lu, Xin

doi:10.4028/www.scientific.net/amm.556-562.2668

Cited by 1 publication

(1 citation statement)

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“…In the previous studies, several types of schemes have employed network-based indices to find the most influential authors from the co-author network and ranked them within that network (Zhang, Liu and Lu 2014). The power of centrality metrics has been acknowledged by evaluating their capability to identify the awardees of prestigious scientific societies.…”

Section: Methodsmentioning

confidence: 99%

A comprehensive author ranking evaluation of network and bibliographic indices

Maqsood

Islam

Afzal

et al. 2020

MJLIS

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With the immense growth of scientific literature over the Web, the authors of research papers are being ranked for various purposes such as for being shortlisted for different scientific awards, for prestigious position, for tenured appointments, for keynote speaker invitation or for allocation of research grants. The traditional paradigm to attain these aspects is based on bibliometric indices, such as publication count, citation count and h-index. The quintessential indicator among all these indices are based on a number of citations received by the publication of an author. Generally, when a research paper is published, it receives citations after some time and may take more than a couple of years to attain a reasonable number of received citations which could make a difference in researcher ranking based on bibliometric parameters. Therefore, dependability over these bibliometric indices for authors ranking is not beneficial for researchers at the start of their academic career. Such authors are less likely to have a fair chance to compete with their senior counterparts. This study aims at overcoming the above-mentioned deficiency with the assistance of network centrality measures using the co-author network. The experiments are conducted to rank authors in order to identify the awardees of various scientific societies. The obtained ranking is further evaluated by comparing the results of bibliographic indices and network-based indices. The results revealed that network indices have equal potential to identify influential authors as compared with bibliometric indices such as h-index, particularly in the case of networks having a high value of cluster coefficient. Based on the obtained results, it is observed, awardees that are exclusively identified by network centrality measures are more than 5 years younger as compared to their counterparts who are exclusively identified by bibliometric indices

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Section: Methodsmentioning

confidence: 99%