Modeling and Simulation Analysis of Journal Impact Factor Dynamics Based on Submission and Citation Rules

Zhou, Jian; Feng, Lin; Cai, Ning; Yang, Jie

doi:10.1155/2020/3154619

Cited by 6 publications

(9 citation statements)

References 40 publications

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“…• Journal impact factor and the publication time of articles are helpful to rank scientific articles [3] [5] [16] [17] [24].…”

Section: Heterogeneous Scholarly Networkmentioning

confidence: 99%

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Weighted P-Rank Algorithm Based on aHeterogeneous Scholarly Network

Zhou

Feng

Liu

et al. 2021

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The evaluation of scientific article has always been a very challenging task because of the dynamicchange of citation networks. Over the past decades, plenty of studies have been conducted on thistopic. However, most of the current methods do not consider the link weightings between differentnetworks, which might lead to biased article ranking results. To tackle this issue, we develop aweighted P-Rank algorithm based on a heterogeneous scholarly network for article ranking evaluation.In this study, the corresponding link weightings in heterogeneous scholarly network can be updatedby calculating citation relevance, authors’ contribution, and journals’ impact. To further boost theperformance, we also employ the time information of each article as a personalized PageRank vectorto balance the bias to earlier publications in the dynamic citation network. The experiments areconducted on three public datasets (arXiv, Cora, and MAG). The experimental results demonstratedthat weighted P-Rank algorithm significantly outperforms other ranking algorithms on arXiv andMAG datasets, while it achieves competitive performance on Cora dataset. Under different networkconfiguration conditions, it can be found that the best ranking result can be obtained by jointlyutilizing all kinds of weighted information.

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“…• Journal impact factor and the publication time of articles are helpful to rank scientific articles [3] [5] [16] [17] [24].…”

Section: Heterogeneous Scholarly Networkmentioning

confidence: 99%

“…Scholarly impact assessment and ranking have always been a hot issue, which plays an important role in the process of the dissemination and development of academic research [1] [2] [3]. However, it is diffcult to assess the real quality of academic articles due to the dynamic change of citation networks [4].…”

Section: Introductionmentioning

confidence: 99%

Weighted P-Rank Algorithm Based on aHeterogeneous Scholarly Network

Zhou

Feng

Liu

et al. 2021

Preprint

Self Cite

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“…Zhou et al. (2020) modeled the IF as a function of the average review time, the average number of references, and the distribution of the citation's ages, and Zhou et al. (2019) modeled the impact of citation networks on the IF.…”

Section: Introductionmentioning

confidence: 99%

“…Through a statistical analysis, Huang et al (2019) demonstrated that modifying a journal's status to "Open Access" leads to a higher IF. Zhou et al (2020) modeled the IF as a function of the average review time, the average number of references, and the distribution of the citation's ages, and Zhou et al (2019) modeled the impact of citation networks on the IF. Hoffmann et al (2014) applied social network analysis to the assessment of scientific impact.…”

mentioning

confidence: 99%

How Reliable Are Impact Factors for Ranking Water Resources Journals? An Analysis of the 70,878 Citation Records of the 2002 and 2021 Top 10 Journals for the Last Two Decades

Pauwels

2023

Water Resources Research

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For a variety of reasons, which include confirmations and promotions of researchers, and grant funding, journal Impact Factors (IFs) remain widely used. Not surprisingly, a number of disciplines have begun to study the evolutions and trends of these metrics, to the point of van Leeuwen and Wouters (2017) noticing that this has become a research field of its own. For example, Van Hooydonk et al. (1994) investigated the link between library management and journal IFs, and concluded that libraries tend to locally hold journals with a high IF. Interestingly, a very large part of the research on IFs is situated in the medical sciences. Bienert et al. (2015) compared cardiology journals performance indices in different databases, and predicted the use of new and constantly improved quality indicators in the future. Ugolini et al. (2013) showed an increase in the publication numbers and consequent decrease in IF values in literature on cerebrovascular and cardiovascular diseases rehabilitation. In the dermatology discipline, Reiter et al. (2016) investigated the importance of author self-citations in the IF. They concluded that in general the importance was low, except for journals with a relatively low IF. Sims et al. (2003) analyzed trends in the IFs for journals in ophthalmology and vision science. Bador and Lafouge (2010) compared the h-index and the IF of journals in pharmacology and pychiatry, and concluded that these indices are highly complementary. A similar analysis was performed by Bird (2008) for toxicology journals. Also in pharmacology, Amiri and Michel (2018) concluded that review papers do not increase the IF unless they account for more than 10% of all published articles. In the field of ergonomics, Smith (2010) documented a rising trend in the IFs between 200% and 613% from 1975 to 2007. For journals focusing on Orthopedics, Erivan et al. (2020) concluded that publishing papers on case reports lowers the journal IF, because of their low citation rates. For the clinical sciences in general, Royle et al. (2013) showed that the journal IF accounts for 50% of the variations to

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“…Scholarly impact evaluation has always been a hot topic, which is benefcial to promote the public understanding and application of scientifc achievements [1][2][3]. Nevertheless, assessing and computing academic achievements has proven to be a difcult task due to the constantly changing nature of citation networks [4,5].…”

Section: Introductionmentioning

confidence: 99%

An Optimization Ranking Approach Based on Weighted Citation Networks and P-Rank Algorithm

Jiang

You

2023

Complexity

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Evaluating scientific articles has always been a challenging task, made even more difficult by the constantly evolving citation networks. Despite numerous attempts at solving this problem, most existing approaches fail to consider the link relationships within the citation network, which can often result in biased evaluation results. To overcome this limitation, we present an optimization ranking algorithm that leverages the P-Rank algorithm and weighted citation networks to provide a more accurate article ranking. The proposed approach employs two hyperbolic tangent functions to calculate the corresponding age of articles and the number of citations, while also updating the link relationships of each paper node in the citation network. We validate the effectiveness of the proposed approach using three evaluation indicators and conduct experiments on three public datasets. The obtained experimental results demonstrate that the optimization article ranking method can achieve competitive performance when compared to other unweighted ranking algorithms. In addition, we note that the optimal Spearman’s rank correlation and robustness can all be achieved by using a combination of the following parameters: α = 10 , β = 5 , and γ = 2 .

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Modeling and Simulation Analysis of Journal Impact Factor Dynamics Based on Submission and Citation Rules

Cited by 6 publications

References 40 publications

Weighted P-Rank Algorithm Based on aHeterogeneous Scholarly Network

Weighted P-Rank Algorithm Based on aHeterogeneous Scholarly Network

How Reliable Are Impact Factors for Ranking Water Resources Journals? An Analysis of the 70,878 Citation Records of the 2002 and 2021 Top 10 Journals for the Last Two Decades

An Optimization Ranking Approach Based on Weighted Citation Networks and P-Rank Algorithm

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