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. 2023 Aug 11;102(32):e34578.
doi: 10.1097/MD.0000000000034578.

Visualizing burst spots on research for four authors in MDPI journals named to be Citation Laureates 2021 using temporal bar graph

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Visualizing burst spots on research for four authors in MDPI journals named to be Citation Laureates 2021 using temporal bar graph

Sam Yu-Chieh Ho et al. Medicine (Baltimore). .

Abstract

Background: The appearance of a topic in a document stream is signaled by a burst of activity, with certain features rising sharply in frequency as the topic emerges. Although temporal bar graph (TBG) is frequently applied to present the burst spot in the bibliographical study, none of the research has combined the inflection point (IP) to interpret the burst spot feature. The aims of this study are to improve the traditional TBG and apply the TBG to understand better the evolution of a topic (e.g., publications and citations for a given author).

Methods: The EISTL model, including entity, indicator, selection of a few vital ones (named attributes) with higher values in quantity (e.g., the citation data of the top 10 entities), TBG and line-chart plots to verify the trend of interest, was proposed to demonstrate the TBG as a whole. The IP locations compared to the median point in data along with the heap map and line-chart trend were identified. The burst strength was computed. A dashboard on Google Maps was designed and launched for bibliometric analysis. Four authors in MDPI (Multidisciplinary Digital Publishing Institute) journals named to be Citation Laureates 2021 were recruited to compare their research achievements shown on the TBG, particularly displaying the burst spots and the recent developments and stages (e.g., increasing, ready to increase, slowdown, or decreasing).

Results: We observed that the highest burst strengths in publication and citations are earned by Barry Halliwell (8.99) and Jean-Pierre Changeux (18.01). The breakthrough of TBG using the EISTL model to display the influence of authors in academics was made with 2 parts of the primary IP point and the trend feature in the data.

Conclusion: The dashboard-type TBG shown on Google Maps is unique and innovative and able to provide deeper insights to readers, not merely limited to the publications and citations for a given author as we did in this study.

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Conflict of interest statement

The authors have no funding and conflicts of interest to disclose.

Figures

Figure 1.
Figure 1.
IP features using the temporal bar graph to display.
Figure 2.
Figure 2.
Collaborations of research in affiliated countries for the 4 authors.
Figure 3.
Figure 3.
Geospatial research achievements in affiliated countries for the 4 authors.
Figure 4.
Figure 4.
Collaborations of research in coauthors with the 4 authors.
Figure 5.
Figure 5.
Cluster analysis of MeSH terms for the 4 authors. MeSH = medical subject headings.
Figure 6.
Figure 6.
Burst spots and evolutions on a temporal bar graph for the 4 authors.
Figure 7.
Figure 7.
Details about the trends using line-chart plots.

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