Content- and proximity-based author co-citation analysis using citation sentences

The Message of the Glasgow Coma Scale: A Comprehensive Bibliometric Analysis and Systematic Review of Clinical Practice Guidelines Spanning the Past 50 years

BACKGROUND

Despite the ubiquitous use of the Glasgow Coma Scale (GCS) worldwide, no study to date has objectively and quantitatively assessed its impact on the scientific literature and clinical practice. Therefore, we comprehensively analyzed scientific publications and clinical practice guidelines employing the GCS to gauge its clinical and academic impact, identify research hotspots, and inform future research on the topic.

METHODS

A cross-sectional bibliometric analysis was performed on Scopus to obtain relevant publications incorporating the GCS from 1974 to 2022. In addition, a systematic review of existing clinical practice guidelines in PubMed, Scopus, Web of Science, and Trip Database was performed. Validated bibliometric parameters including article title, journal, publication year, authors, citation count, country, institution, keywords, impact factor, and references were assessed. When evaluating clinical practice guidelines, the sponsoring organization, country of origin, specialty, and publication year were assessed.

RESULTS

A total of 37,633 articles originating from 3924 different scientific journals spanning 1974-2022 were included in the final analysis. The compound annual growth rate of publications referencing the GCS was 16.7%. Of 104 countries, the United States had the highest total number of publications employing the GCS (n = 8517). World Neurosurgery was the scientific periodical with the highest number of publications on the GCS (n = 798). The top trending author-supplied keyword was "traumatic brain injury" (n = 3408). The 97 included clinical practice guidelines most commonly employed the GCS in the fields of internal medicine (n = 22, 23%), critical care (n = 21, 22%), and neurotrauma (n = 19, 20%).

CONCLUSIONS

At the turn of the 50th anniversary of the GCS, we provided a unique and detailed description of the "path to success" of the GCS both in terms of its scientific and clinical impact. These results have not only a historical but also an important didactic value. Ultimately our detailed analysis, which revealed some of the factors that led the GCS to become such a widespread and highly influential score, may assist future researchers in their development of new outcome measures and clinical scores, especially as such tools become increasingly relevant in an evidence-based data-driven age.

The status and trends of mitochondrial dynamics research: A global bibliometric and visualized analysis

BACKGROUND

Mitochondria are remarkably dynamic organelles encapsulated by bilayer membranes. The dynamic properties of mitochondria are critical for energy production.

AIMS

The aim of our study is to investigate the global status and trends of mitochondrial dynamics research and predict popular topics and directions in the field.

METHODS

Publications related to the studies of mitochondrial dynamics from 2002 to 2021 were retrieved from Web of Science database. A total of 4,576 publications were included. Bibliometric analysis was conducted by visualization of similarities viewer and GraphPadPrism 5 software.

RESULTS

There is an increasing trend of mitochondrial dynamics research during the last 20 years. The cumulative number of publications about mitochondrial dynamics research followed the logistic growth model [Formula: see text]. The USA made the highest contributions to the global research. The journal Biochimica et Biophysica Acta (BBA)-Molecular Cell Research had the largest publication numbers. Case Western Reserve University is the most contributive institution. The main research orientation and funding agency were cell biology and HHS. All keywords related studies could be divided into three clusters: "Related disease research", "Mechanism research" and "Cell metabolism research".

CONCLUSIONS

Attention should be drawn to the latest popular research and more efforts will be put into mechanistic research, which may inspire new clinical treatments for the associated diseases.

Research focus and theme trend on fulminant myocarditis: A bibliometric analysis

Aims

This study intends to explore the research focus and trends of fulminant myocarditis (FM) to have a better understanding of the topic.

Materials and methods

The data were downloaded from the Web of Science (WoS) database using the topic (TS) advanced search strategy. Many instruments were used to extract, analyze, and visualize the data, such as Microsoft Excel, HistCite Pro, GunnMap, BibExcel, and VOSviewer.

Results

From 1985 to 2022, 726 documents were indexed in the WoS. The United States and Columbia University were the most productive country and institutions. Keywords co-occurrence was carried out and four research themes were identified. In addition, the top three prolific authors, the first three highly cited authors, and the core authors of the author co-citation network were identified. The topics that they kept an eye on were analyzed, and the research areas of key authors were similar to the results of keyword co-occurrence. The hot topics of FM were related to the mechanical circulatory support, etiology, diagnosis, and the disease or therapy associated with FM.

Conclusion

This study carried out a systematic analysis of the documents related to FM from 1985 to 2022, which can provide a guideline for researchers to understand the theme trend to promote future research to be carried out.

A review of research on driving distraction based on bibliometrics and co-occurrence: Focus on driving distraction recognition methods

INTRODUCTION

The existing selection of driving distraction recognition methods is based on a specific research perspective and does not provide comprehensive information on the entire field of view.

METHOD

We conducted a systematic review of previous studies, aiming to come up with appropriate research methods to identify the driver's distraction state. First, this article selects four sets of search keywords related to driving distraction discrimination from five databases (Web of Science, ScienceDirect, Springer Link, IEEE, and TRID) and identifies 1,620 peer-reviewed documents from 2000 to 2020; these 1,620 documents underwent bibliographic analysis and co-occurrence network analysis. The co-occurrence coupling relationship is analyzed from the aspects of time, country, publication, author and keywords. Second, 37 papers published were screened, and the driving distraction recognition methods proposed by these 37 papers were summarized and analyzed.

RESULTS

The results show that this field has been prevalent since 2013; countries such as the United States, Britain, Germany, Australia, China, and Canada are in the forefront of research in this field, and the cooperation between related countries is relatively close. The cooperation between authors is characterized by aggregation, and the mobile phone as the main keyword is almost connected to other keyword nodes; the recognition model of deep learning algorithm based on video surveillance data sources has become the mainstream hot spot distraction recognition method. The recognition model of machine learning algorithm based on vehicle dynamics data, driver physiology, and eye movement data sources has specific advantages and disadvantages.

PRACTICAL APPLICATIONS

The results can help people to understand the current situation of driving distraction comprehensively and systematically, provide better theoretical support for researchers to choose the subsequent driving distraction recognition model, and provide research direction for driving distraction recognition in the future.

A Bibliometric Analysis of the Scientific Research on Artisanal and Small-Scale Mining

Mineral resource exploitation is one of the activities that contribute to economic growth and the development of society. Artisanal and small-scale mining (ASM) is one of these activities. Unfortunately, there is no clear consensus to define ASM. However, its importance is relevant in that it represents, in some cases, the only employment alternative for millions of people, although it also significantly impacts the environment. This work aims to investigate the scientific information related to ASM through a bibliometric analysis and, in addition, to define the new lines that are tending to this field. The study comprises three phases of work: (i) data collection, (ii) data processing and software selection, and (iii) data interpretation. The results reflect that the study on ASM developed intensively from 2010 to the present. In general terms, the research addressed focuses on four interrelated lines: (i) social conditioning factors of ASM, (ii) environmental impacts generated by ASM, (iii) mercury contamination and its implication on health and the environment, and (iv) ASM as a livelihood. The work also defines that geotourism in artisanal mining areas is a significant trend of the last decade, explicitly focusing on the conservation and use of the geological and mining heritage and, in addition, the promotion of sustainable development of ASM.

Worldwide Research Trends in Landslide Science

Landslides are generated by natural causes and by human action, causing various geomorphological changes as well as physical and socioeconomic loss of the environment and human life. The study, characterization and implementation of techniques are essential to reduce land vulnerability, different socioeconomic sector susceptibility and actions to guarantee better slope stability with a significant positive impact on society. The aim of this work is the bibliometric analysis of the different types of landslides that the United States Geological Survey (USGS) emphasizes, through the SCOPUS database and the VOSviewer software version 1.6.17, for the analysis of their structure, scientific production, and the close relationship with several scientific fields and its trends. The methodology focuses on: (i) search criteria; (ii) data extraction and cleaning; (iii) generation of graphs and bibliometric mapping; and (iv) analysis of results and possible trends. The study and analysis of landslides are in a period of exponential growth, focusing mainly on techniques and solutions for the stabilization, prevention, and categorization of the most susceptible hillslope sectors. Therefore, this research field has the full collaboration of various authors and places a significant focus on the conceptual evolution of the landslide science.

Intellectual structure of information science 2011–2020: an author co-citation analysis

Purpose

This study continues a long history of author co-citation analysis of the intellectual structure of information science into the time period of 2011–2020. It also examines changes in this structure from 2006–2010 through 2011–2015 to 2016–2020. Results will contribute to a better understanding of the information science research field.

Design/methodology/approach

The well-established procedures and techniques for author co-citation analysis were followed. Full records of research articles in core information science journals published during 2011–2020 were retrieved and downloaded from the Web of Science database. About 150 most highly cited authors in each of the two five-year time periods were selected from this dataset to represent this field, and their co-citation counts were calculated. Each co-citation matrix was input into SPSS for factor analysis, and results were visualized in Pajek. Factors were interpreted as specialties and labeled upon an examination of articles written by authors who load primarily on each factor.

Findings

The two-camp structure of information science continued to be present clearly. Bibliometric indicators for research evaluation dominated the Knowledge Domain Analysis camp during both fivr-year time periods, whereas interactive information retrieval (IR) dominated the IR camp during 2011–2015 but shared dominance with information behavior during 2016–2020. Bridging between the two camps became increasingly weaker and was only provided by the scholarly communication specialty during 2016–2020. The IR systems specialty drifted further away from the IR camp. The information behavior specialty experienced a deep slump during 2011–2020 in its evolution process. Altmetrics grew to dominate the Webometrics specialty and brought it to a sharp increase during 2016–2020.

Originality/value

Author co-citation analysis (ACA) is effective in revealing intellectual structures of research fields. Most related studies used term-based methods to identify individual research topics but did not examine the interrelationships between these topics or the overall structure of the field. The few studies that did discuss the overall structure paid little attention to the effect of changes to the source journals on the results. The present study does not have these problems and continues the long history of benchmark contributions to a better understanding of the information science field using ACA.

Exploring the intellectual cores of the blockchain–Internet of Things (BIoT)

Purpose

Due to the rapid growth of blockchain technology in recent years, the fusion of blockchain and the Internet of Things (BIoT) has drawn considerable attention from researchers and industrial practitioners and is regarded as a future trend in technological development. Although several authors have conducted literature reviews on the topic, none have examined the development of the knowledge structure of BIoT, resulting in scattered research and development (R&D) efforts.

Design/methodology/approach

This study investigates the intellectual core of BIoT through a co-citation proximity analysis–based systematic review (CPASR) of the correlations between 44 highly influential articles out of 473 relevant research studies. Subsequently, we apply a series of statistical analyses, including exploratory factor analysis (EFA), hierarchical cluster analysis (HCA), k-means clustering (KMC) and multidimensional scaling (MDS) to establish the intellectual core.

Findings

Our findings indicate that there are nine categories in the intellectual core of BIoT: (1) data privacy and security for BIoT systems, (2) models and applications of BIoT, (3) system security theories for BIoT, (4) frameworks for BIoT deployment, (5) the fusion of BIoT with emerging methods and technologies, (6) applied security strategies for using blockchain with the IoT, (7) the design and development of industrial BIoT, (8) establishing trust through BIoT and (9) the BIoT ecosystem.

Originality/value

We use the CPASR method to examine the intellectual core of BIoT, which is an under-researched and topical area. The paper also provides a structural framework for investigating BIoT research that may be applicable to other knowledge domains.

An exploratory study of the all-author bibliographic coupling analysis: Taking scientometrics for example

All-author bibliographic coupling analyses (AABCA) take all authors of the article into account when constructing author coupling relationships. Taking scientometrics as an example, this article takes the papers from 2010 to 2019 as data sample and divides them into two periods (limited to 5 years) to discuss the performance of AABCA in discovering potential academic communities and intellectual structure of this discipline. It is found that when all authors of the paper are considered, the relationship between the bibliographic coupling authors presents a certain regularity and the bibliographic coupling is likely to be passed between different pairs of authors. With the transitivity of the coupling relationship, AABCA can effectively identify and discover the potential academic groups of this discipline, and more fully reflect the degree of cooperation among authors. AABCA is an effective method to reveal the intellectual structure in the field of scientometrics, and it is easier to find some small research topics with weak correlation. In addition, AABCA is also an ideal way to explore the author’s research interests over time.

Mining author relationship in scholarly networks based on tripartite citation analysis

Following scholars in Scientometrics as examples, we develop five author relationship networks, namely, co-authorship, author co-citation (AC), author bibliographic coupling (ABC), author direct citation (ADC), and author keyword coupling (AKC). The time frame of data sets is divided into two periods: before 2011 (i.e., T1) and after 2011 (i.e., T2). Through quadratic assignment procedure analysis, we found that some authors have ABC or AC relationships (i.e., potential communication relationship, PCR) but do not have actual collaborations or direct citations (i.e., actual communication relationship, ACR) among them. In addition, we noticed that PCR and AKC are highly correlated and that the old PCR and the new ACR are correlated and consistent. Such facts indicate that PCR tends to produce academic exchanges based on similar themes, and ABC bears more advantages in predicting potential relations. Based on tripartite citation analysis, including AC, ABC, and ADC, we also present an author-relation mining process. Such process can be used to detect deep and potential author relationships. We analyze the prediction capacity by comparing between the T1 and T2 periods, which demonstrate that relation mining can be complementary in identifying authors based on similar themes and discovering more potential collaborations and academic communities.