PrestigeRank: A new evaluation method for papers and journals

Su, Cheng; Pan, Yuntao; Yan-ning, Zhen; Ma, Zheng; Yuan, Jian; Guo, Hong; Yu, ZhengLu; Ma, Caifeng; Wu, Yulin

doi:10.1016/j.joi.2010.03.011

Cited by 38 publications

(12 citation statements)

References 10 publications

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“…The results showed that the weighted algorithm has higher stability under different damping factors by comparing with other traditional methods. Su et al [17] used PrestigeRank algorithm to study the missing data of PageRank, and they ranked journals in the physics field by using the PrestigeRank algorithm and PageRank algorithm. They found that the PrestigeRank algorithm had better robustness according to the results.…”

Section: A Two Main Metricsmentioning

confidence: 99%

A New Journal Ranking Method: The Reputation Analysis of Citation Behavior Model

Zhang

et al. 2019

IEEE Access

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The authority of journals is usually a key indicator in guiding people to choose important journals, and the journal ranking is a common way to distinguish the journals' authority. The common ranking methods or models are based on citation data, such as the impact factor (IF), the PageRank algorithm, and the hyperlink-induced topic search algorithm. In this paper, we present a new model, named the reputation analysis of citation behavior (RACB) model, which not only considers the number of citations but also considers the reputation of inter-citation behavior. First, the model fits the function relation of the citation desire index (CDI) based on the citation data of the most reputable journal (named the top journal in the remainder of this paper). Then, the CDI values of the target journals are calculated by using the function relation of the top journal. An improved gray correlation analysis is used to describe the deviation between the CDI and the actual citation rate, named the random citation rate, indicating the inter-citation reputation value of the target journals. Finally, a case study showed that the ranking result of the RACB model has a high similarity with the IF values of 2017, which indicates that the ranking results of the RACB model that considered journal reputation evaluations are more reasonable than those of the traditional PageRank algorithm. This paper proposes a new method of journal ranking from the perspective of reputation evaluation, which can rank the journals more reasonably. It encourages researchers to cite articles more fairly in order to avoid a situation in which the low reputation of the citation behavior affects the quality of the journal that published the article.

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Section: A Two Main Metricsmentioning

confidence: 99%

A New Journal Ranking Method: The Reputation Analysis of Citation Behavior Model

Zhang

et al. 2019

IEEE Access

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“…Inspired by the success of Google's ranking system for web pages, the popular algorithm PageRank as well as some of its variants have been used to show the prestige in citation networks of journals [23], [24], scientists [25]- [27], and publications [28]- [42]. The local and global structure of citation graph [27], [35], [37], [41], [42], the heterogeneity of the citation networks [32], the ''virtual node'' which considers the citations not included in the current systems [33], and the age of the publications [28], [31], [35] are taken into account in these researches.…”

Section: Introductionmentioning

confidence: 99%

Quantifying a Paper’s Academic Impact by Distinguishing the Unequal Intensities and Contributions of Citations

Wang

Ren

et al. 2019

IEEE Access

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Citation count is a widely-used indicator for calculating the academic impact of scientific papers, but it is limited because it assumes all citations are of similar value and weights each equally. By examining the influence changes in papers' citation distribution and the cited papers' unequal contributions to the citing ones, this study aims to distinguish citations and, on this basis, evaluate the academic impact of the papers. Three indices of time-weighted citation count, citation width and citation depth are proposed to distinguish citations and perform the evaluation task. The experimental results show that papers exhibit different influence intensity characteristics in different periods of citation life. Those papers got larger citations in recent years are more influential and more active to gain new citations. The papers show the different scope of influence in their citing environment, although they were originally published in the same journal and the same year. In addition, the different frequency of mentions and the different subject similarities with the citing works suggest that the papers have different importance and usefulness for subsequent research. These results suggest that these three indices do help to distinguish citations and reveal the different intensity and contribution of influences in citations. Finally, the three indices are integrated into the overall evaluation of the academic impact of the paper, and the weight of each index is calculated by the entropy weight method. Quite different overall impacts in the paper are shown due to their different performances in the three indices, even though they have the same total number of citations. INDEX TERMS Academic impact, time window, knowledge flow, mentioned frequency, entropy weight method.

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“…Several modications and variants of network models have been introduced in the context of Scientometrics (see, e.g. [65,121,171,188]).…”

Section: Citation Network and Scientometricsmentioning

confidence: 99%

Complex network models, graph mining and information extraction from real-world systems

London

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PrestigeRank: A new evaluation method for papers and journals

Cited by 38 publications

References 10 publications

A New Journal Ranking Method: The Reputation Analysis of Citation Behavior Model

A New Journal Ranking Method: The Reputation Analysis of Citation Behavior Model

Quantifying a Paper’s Academic Impact by Distinguishing the Unequal Intensities and Contributions of Citations

Complex network models, graph mining and information extraction from real-world systems

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