Predicting the number of citations of polycystic kidney disease with 100 top-cited articles since 2010: Bibliometric analysis

Wang, Chenyu; Chien, Tsair‐Wei; Chou, Willy; Wang, Hsien-Yi

doi:10.1097/md.0000000000030632

Cited by 6 publications

(20 citation statements)

References 26 publications

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“…The characteristics of 100 top-cited articles are commonly visualized with 3 categories of information on descriptive statistics, research domain, and research achievement (RA). [8,44–49] Some studies [8,44–48,49] have applied citation prediction to predict article citations based on the mean citations of article keywords, but the themes have not been definitely classified and clearly visualized through Equation 4. [9]…”

Section: Discussionmentioning

confidence: 99%

The 100 most cited articles have fewer citations than other bibliometric articles: A pairwise comparison using a temporal bubble graph

2022

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Background: More than 400 articles with the title of 100 top-cited articles (Top100) have been published in PubMed. It is unknown whether their citations are fewer (or more) than those found in other bibliometric studies (Nontop100). After determining article themes using coword analysis, a temporal bubble graph (TBG) was used to verify the hypothesis that the Top100 had fewer citations than the Nontop100. Methods: Using the Web of Science core collection, the top 50 most cited articles were compiled by Top100 and Nontop100, respectively, based on the research area of biomedicine and bibliometrics only. Coword analysis was used to extract themes. The study results were displayed using 6 different visualizations, including charts with bars, pyramids, forests, clusters, chords, and bubbles. Mean citations were compared between Top100 and Nontop100 using the bootstrapping method. Results: There were 18 citations in total for the 2 sets of the 50 most cited articles (range 1–134; 5 and 26.5 for Top100 and Nontop100, respectively). A significant difference in mean citations was observed between the 2 groups of Top100 and Nontop100 based on the bootstrapping method (3, 95% confidence interval: [1.18, 4.82]; 26.5, 95% confidence interval: [23.82, 29.18], P < .001). The 11 themes were clustered using coword analysis and applied to a TBG, which is composed of 4 dimensions: themes, years, citations and groups of articles. Among the 2 groups, the majority of articles were published in the journal of Medicine (Baltimore), with 9 and 7, respectively. Conclusion: Eleven themes were identified as a result of this study. In addition, it reveals distinct differences between the 2 groups of Top100 and Nontop100, with the former containing more recently published articles and the latter containing more citations for articles. Clinical and research clinicians and researchers can use bibliometric analysis to appraise published literature and to understand the scientific landmark using TBG in bibliometrics.

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Section: Discussionmentioning

confidence: 99%

The 100 most cited articles have fewer citations than other bibliometric articles: A pairwise comparison using a temporal bubble graph

2022

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“…The correlation coefficient ( r ) was used to determine the predictive power between the weighted keywords and original article citations. The t value of the correlation coefficient ( r ) was calculated using the following formula false(=normalr×n−21−r×r) [23–26]…”

Section: Methodsmentioning

confidence: 99%

“…It is common for bibliographical studies to refer to three types of information: descriptive statistics (DS), significant topics or article types with research domains (RD), and research achievements in entities (RA). [14] Based on keywords in articles, citation prediction (CP) [23][24][25][26] has been employed in bibliometrics to predict article citations. In this manner, bibliometric analyses can identify study characteristics as well as article citations that are related to their keywords in a particular field of study.…”

Section: Citation Prediction Required In Bibliometricsmentioning

confidence: 99%

“…The characteristics of 100 top-cited articles are commonly visualized with three categories of information on DS, RD, and RA. [14,18,[23][24][25][26][27] Some studies [18,[23][24][25][26][27] have applied CP to predict article citations based on the mean citations of article keywords, but the visual presentation is not comparable to the Kano diagram with the unidimensional feature from the left-bottom corner to the top-right corner. Additionally, many articles include many tables and graphs in bibliometrics without applying radar plots and chord diagrams to condense information of interest for readers, as we did in Figures 1 and 2, particularly with the IBP in Figure 3 to display all those T31SVOAIs on a dashboard and save article spaces when compared to those with 50 articles in a study.…”

Section: Chord Diagrams Used To Present the Relationship Between Them...mentioning

confidence: 99%

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Thematic analysis of articles on artificial intelligence with spine trauma, vertebral metastasis, and osteoporosis using chord diagrams: A systematic review and meta-analysis

et al. 2022

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Background: Spine trauma, vertebral metastases, and osteoporosis (SVO) can result in serious health problems. If the diagnosis of SVO is delayed, the prognosis may be deteriorated. The use of artificial intelligence (AI) is an essential method for minimizing the diagnostic errors associated with SVO. research achievements (RAs) of SVO on AI are required as a result of the greatest number of studies on AI solutions reported. The study aimed to: classify article themes using visualizations, illustrate the characteristics of SVO on AI recently, compare RAs of SVO on AI between entities (e.g., countries, institutes, departments, and authors), and determine whether the mean citations of keywords can be used to predict article citations. Methods: A total of 31 articles from SVO on AI (denoted by T31SVOAI) have been found in Web of Science since 2018. The dominant entities were analyzed using the CJAL score and the Y-index. Five visualizations were applied to report: the themes of T31SVOAI and their RAs in comparison for article entities and verification of the hypothesis that the mean citations of keywords can predict article citations, including: network diagrams, chord diagrams, dot plots, a Kano diagram, and radar plots. Results: There were five themes classified (osteoporosis, personalized medicine, fracture, deformity, and cervical spine) by a chord diagram. The dominant entities with the highest CJAL scores were the United States (22.05), the University of Pennsylvania (5.72), Radiology (6.12), and Nithin Kolanu (Australia) (9.88). The majority of articles were published in Bone, J. Bone Miner. Res., and Arch. Osteoporos., with an equal count (=3). There was a significant correlation between the number of article citations and the number of weighted keywords ( F = 392.05; P < .0001). Conclusion: A breakthrough was achieved by displaying the characteristics of T31SVOAI using the CJAL score, the Y-index, and the chord diagram. Weighted keywords can be used to predict article citations. The five visualizations employed in this study may be used in future bibliographical studies.

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“…); Diagnostic (e.g., classification of themes, keywords, or author collaborations, which answers the question of why did this happen? ); Predictive (e.g., using weighted keyword mean citations to predict article citations [27][28][29][30] ), and; Prescriptive (e.g., with heatmaps to highlight the roadmap for the future, which answers the question of what should we do next?) facets.…”

Section: Four Analytics In Bibliographical Studiesmentioning

confidence: 99%

Using temporal heatmaps to identify worthwhile articles on immune checkpoint blockade for melanoma (ICBM) in Mainland China, Hong Kong, and Taiwan since 2000: A bibliometric analysis

et al. 2023

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Background: Melanoma is a life-threatening form of skin cancer. Due to its remarkable effectiveness, the immune checkpoint blockade is widely used to treat melanoma (ICBM). No research has been conducted on ICBM for identifying the most readable articles. A bibliometric analysis of 100 top-cited ICBM (T100ICBM) in recent decades is required to highlight articles worth reading. Methods: Based on the Web of Science Core Collection, we summarized the articles on ICBM published in each year from 2000 to 2022, with first authors from Mainland China, Hong Kong, and Taiwan (CHT). Using the CJAL score, data extraction and visualization of the distribution of ICBM publications were conducted on 2718, and 100 top-cited articles, respectively. We used the temporal heatmap to identify the most readable articles. Four descriptive, diagnostic, predictive, and prescriptive analytics (called DDPP model) were applied to describe the features of T100ICBM articles. The absolute advantage coefficient was used to determine the dominance extent of the most influential region, institute, department, and author. Results: A total of 2718 publications was included after removing first or corresponding authors who were not affiliated with CHT. Publications by year showed a sharp increase from 2014 onward and either peaked in 2022 or have not yet peaked. It was evident that there was a large difference between the number of publications in provinces/metropolitan cities/regions on CHT. Beijing, Sichuan University, Oncology, and Guo Jun from Beijing are the most prolific and influential region, institute, department, and author. When comparing research achievements to the next productive authors based on the CJAL score, only Dr Jun has a medium effect of dominance (=0.60). On the basis of their consecutive growth in citations over the past 4 years, 20 T100ICBM articles were recommended for readers. Conclusion: The field of ICBM is growing rapidly, and Beijing and Sichuan University are taking the lead in CHT. Furthermore, the study provides references for worth-reading articles using the temporal heatmap. Future research hot spots may focus on these 4 themes of immunotherapy, melanoma, metastatic melanoma, regulatory T cells, cells, and activation, which may pave the way for additional study.

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Predicting the number of citations of polycystic kidney disease with 100 top-cited articles since 2010: Bibliometric analysis

Cited by 6 publications

References 26 publications

The 100 most cited articles have fewer citations than other bibliometric articles: A pairwise comparison using a temporal bubble graph

The 100 most cited articles have fewer citations than other bibliometric articles: A pairwise comparison using a temporal bubble graph

Thematic analysis of articles on artificial intelligence with spine trauma, vertebral metastasis, and osteoporosis using chord diagrams: A systematic review and meta-analysis

Using temporal heatmaps to identify worthwhile articles on immune checkpoint blockade for melanoma (ICBM) in Mainland China, Hong Kong, and Taiwan since 2000: A bibliometric analysis

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