Citation trends in ophthalmology articles and keywords in mainland China, Hong Kong, and Taiwan since 2013 using temporal bar graphs (TBGs): Bibliometric analysis

Abstract

Background: We selected authors from mainland China, Hong Kong, and Taiwan (CHT) to examine citation trends on articles and keywords. The existence of suitable temporal bar graphs (TBGs) for displaying citation trends is unknown. It is necessary to enhance the traditional TBGs to provide readers with more information about the citation trend. The purpose of this study was to propose an advanced TBG that can be applied to understand the most worth-reading articles by ophthalmology authors in the CHT. Methods: Using the search engine of the Web of Science core collection, we conducted bibliometric analyses to examine the article citation trends of ophthalmology authors in CHT since 2013. A total of 6695 metadata was collected from articles and review articles. Using radar plots, the Y-index, and the combining the Y-index with the CJAL scores (CJAL) scores, we could determine the dominance of publications by year, region, institute, journal, department, and author. A choropleth map, a dot plot, and a 4-quadrant radar plot were used to visualize the results. A TBG was designed and provided for readers to display citation trends on articles and keywords. Results: We found that the majority of publications were published in 2017 (2275), Shanghai city (935), Sun Yat-Sen University (China) (689), the international journal Ophthalmology (1399), the Department of Ophthalmology (3035), and the author Peizeng Yang (Chongqing) (65); the highest CAJL scores were also from Guangdong (2767.22), Sun Yat-Sen University (China) (2147.35), and the Ophthalmology Department (7130.96); the author Peizeng Yang (Chongqing) (170.16) had the highest CAJL; and the enhanced TBG features maximum counts and recent growth trends that are not included in traditional TBGs. Conclusion: Using the Y-index and the CJAL score compared with research achievements of ophthalmology authors in CHT, a 4-quadrant radar plot was provided. The enhanced TBGs and the CJAL scores are recommended for future bibliographical studies.

The ascendancy of research in acronyms related to COVID-19 displayed on a growth-share matrix (GSM): Bibliometric analysis

“…The top 1 acronym with the greatest number of counts in each year was compared to the next 2 using the AAC [27] via Eqs 3 to 5.…”

“…The top 1 acronym with the greatest number of counts in each year was compared to the next 2 using the AAC [27] via Eqs 3 to 5. (5) where the AAC ratio is determined by the 3 consecutive numbers of values (e.g., counts denoted by A1, A2, and A3 in descending order via Eqs 3 and 4) in the top 3 acronyms.…”

Analysis of citation trends to identify articles on delirium worth reading using DDPP model with temporal heatmaps (THM): A bibliometric analysis

“…The THM [38] contains 4 dimensions, namely, attributes (e.g., articles or keywords) on the row, years on the column, and color darkened by citation or count, and the burst point starts at the beginning of red font and ends at citations (or counts) smaller than the count at the burst point. [20][21][22][23] With the THM, the most worth-reading articles with higher growing citation trends in T100delirium were highlighted by the respective burst strength. [20][21][22][23] The trend signals include 5 possible outcomes (e.g., ready to rise, increasing, slow down, declining, and stationarity).…”

“…The inflection points (IPs) on ogive curves can be obtained through the Newton-Raphson Iteration Method [23,42,43] and the link [41] (or with the Solver add-in function in Micro Soft Excel [44][45][46] ). We can see that the IP (or the burst spot) can be obtained along with other statistics in Panel B of Figure 2, including IPcase (namely, burst strength), [20][21][22][23] absolute advantage coefficient, [39] growth types, [39] slope parameter based on item response theory, [45,46] and growth based on CC between observed counts and a series of numbers as the string of {1,2,3,4} over the last 4 years. The THM is demonstrated in Panel C of Figure 2 when compared to the traditional TBG [20][21][22][23] without providing article citations for readers, as shown in Panel D of Figure 2.…”

“…The THM was demonstrated to display articles worthy of reading, which is clearer and easier for readers at a glance when compared to traditional TBGs. [20][21][22][23]…”