Evaluating the impact of citations of articles based on knowledge flow patterns hidden in the citations


Autoři: Mingyang Wang aff001;  Jiaqi Zhang aff001;  Shijia Jiao aff001;  Tianyu Zhang aff001
Působiště autorů: College of Information and Computer Engineering, Northeast Forestry University, Harbin, People’s Republic of China aff001
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: 10.1371/journal.pone.0225276

Souhrn

The effective evaluation of the impact of a scholarly article is a significant endeavor; for this reason, it has garnered attention. From the perspective of knowledge flow, this paper extracted various knowledge flow patterns concealed in articles citation counts to describe the citation impact of the articles. First, the intensity characteristic of knowledge flow was investigated to distinguish the different citation vitality of articles. Second, the knowledge diffusion capacity was examined to differentiate the size of the scope of articles’ influences on the academic environment. Finally, the knowledge transfer capacity was discussed to investigate the support degree of articles on the follow-up research. Experimental results show that articles got more citations recently have a higher knowledge flow intensity. The articles have various impacts on the academic environment and have different supporting effects on the follow-up research, representing the differences in their knowledge diffusion and knowledge transfer capabilities. Compared with the single quantitative index of citation frequency, these knowledge flow patterns can carefully explore the citation value of articles. By integrating the three knowledge flow patterns to examine the total citation impact of articles, we found that the articles exhibit distinct value of citation impact even if they were published in the same field, in the same year, and with similar citation frequencies.

Klíčová slova:

Astronomy – Bibliometrics – Citation analysis – Deep learning – Entropy – Scientific publishing – Astrophysics – Information entropy


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Článek vyšel v časopise

PLOS One


2019 Číslo 11