scholarly journals Mapping theme trends and knowledge structure of labor analgesia: a quantitative, co-word biclustering analysis of data in 2000-2020

2021 ◽  
Keyword(s):  
Social Network ◽  
High Frequency ◽  
Numerical Data ◽  
Knowledge Structure ◽  
Labor Analgesia ◽  
Routes Of Administration ◽  
Mesh Terms ◽  
Scientific Papers ◽  
Drug Doses ◽  
Occurrence Matrix

Background: The distribution knowledge structure and pattern of the literature on labor analgesia in PubMed were examined. Methods: Scientific papers on labor analgesia published from 1 January, 2000 to 31 June, 2020 were retrieved. The extracted MeSH items were quantitatively analyzed by the Bibliographic Item Co-Occurrence Matrix Builder (BICOMB), and the high frequency MeSH items were identified. In gCLUTO software, repeated bisection method was used to Mountain visualisation, and the visual matrix was established. By constructing high-frequency MeSH terms co-occurrence matrix, strategic diagram and social network are further completed. Results: The search strategy yielded 2870 papers, and the number of papers published annually had changed slightly during the study period. Among all extracted MeSH terms, 42 high-frequency MeSH terms were identified by consensus, and were divided into six categories by diclustering analysis. In the strategic diagram, the methods of labor analgesia, drug doses, and routes of administration were properly presented. In contrast, statistical and numerical data on obstetric analgesia were relatively underdeveloped, and management of pain during labor was undeveloped. In the social network analysis, the position status of each component was determined by the centrality values. Conclusions: The findings on labor analgesia are relatively divergent, and the six research categories outlined in this study reflect the publication trends in the field of labor analgesia to some extent. Our quantitative bibliometric research across a 20-year span depicts the overall direction of the latest topics and provides some hints for researchers when launching new projects.

scholarly journals Research on China’s Green Finance Policies Based on Text Mining

2020 ◽  
Vol 185 ◽  
pp. 02024
Author(s):  
Yuqing Liao ◽  
Jingliang Chen
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
High Frequency ◽  
Policy Documents ◽  
Analysis Techniques ◽  
The Past ◽  
Word Cloud ◽  
Green Finance ◽  
Occurrence Matrix

Based on the green finance policies in China from 2017 to 2019, this paper extracts feature and high-frequency words from policy documents, uses word cloud diagram, co-occurrence matrix and social network analysis techniques to quantitatively analyse the information contained in the green finance policies over the past three years and highlights the hot issues in question, thus providing a multi-layered and wideranging pathway for facilitating the orderly development of green finance industries across China.

scholarly journals Theme trends in research related to retinal vein occlusion: a quantitative and co-word analysis

2019 ◽  
Author(s):  
Fei Liu ◽  
Ximei Chen ◽  
Miao Zhao
Keyword(s):  
Retinal Vein Occlusion ◽  
Research Output ◽  
Knowledge Structure ◽  
Mesh Term ◽  
Diagnostic Methods ◽  
Vein Occlusion ◽  
Mesh Terms ◽  
Occurrence Matrix ◽  
Surgical Treatments ◽  
Node Position

Abstract Background. This study focused on plotting knowledge structure and exploring research hotspots of retinal vein occlusion (RVO). Methods. In this study, research articles, with subject of RVO, were acquired from PubMed. Bibliographic Item Co-Occurrence Matrix Builder (BICOMB) was used for MeSH terms acquisition, evaluation and high-frequency MeSH term determination. Biclustering analysis and knowledge structure were conducted based on the MeSH term-source article matrix. RVO theme trends were illustrated with social network analysis (SNA), along with strategic diagrams. Results. A total of 3179 articles on RVO were retrieved, and the annual research output increased with time. USA ranked first with the most publications, with Retina as the most prolific journal in RVO research. MeSH terms were characterized into five different genres. As shown by the strategic diagram, the complications of RVO, the etiology of macular edema, as well as the therapeutic use of anti-VEGF, steroids and anti-inflammatory agents were well developed (Quadrant I). In contrast, epidemiology, metabolism and genetics related research on RVO were relatively immature (Quadrant III). Research on surgical treatments of vitrectomy, diagnostic methods and pathology of RVO were centralized but undeveloped (Quadrant IV). The SNA results was exhibited by the centrality chart, on which the node position was represented by the centrality values. Conclusions. By providing a bibliometric research, the overall RVO research trends could be revealed based on the five categories identified by this study. The mathematical bibliometric study could shed light on new perspectives for researchers.

scholarly journals Current Trends in Research on Bone Regeneration: A Bibliometric Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xin Huang ◽  
Xu Liu ◽  
Yuli Shang ◽  
Feng Qiao ◽  
Gang Chen
Keyword(s):  
Social Network ◽  
Bone Regeneration ◽  
Dental Implants ◽  
Bibliometric Analysis ◽  
Clinical Application ◽  
High Frequency ◽  
Tissue Loss ◽  
Mesh Terms ◽  
The Matrix ◽  
Research Hotspots

Background. Bone regeneration is a frequent research topic in clinical studies, but macroscopic studies on the clinical application of bone regeneration are rare. We conducted a bibliometric analysis, using international databases, to explore the clinical application and mechanism of bone regeneration, to highlight the relevant research hotspots and prospects. Material and Methods. Scientific reports on bone regeneration published during 2009–2019 were retrieved from PubMed. VOSviewer for cooccurrence keywords and authorship analysis. BICOMB software was used to retrieve high-frequency words and construct a text/coword matrix. The matrix was inputted into gCLUTO software, managed by biclustering analysis, in order to identify hotspots, which could achieve mountain and matrix visualizations. The matrix was also analyzed by using Ucinet 6 software for social network analysis. A strategic diagram was used for further analysis of the research hotspots of bone regeneration by “SCIMAT” software. We searched the Web of Science for relevant articles. Results. Eighty-nine high-frequency major MeSH terms were obtained from 10237 articles and were divided into 5 clusters. We generated a network visualization map, an overlay visualization mountain map, and a social network diagram. Then, the MeSH terms were subdivided into 7 categories according to each diagram; current research hotspots were identified as scaffold, drug effect, osseointegration in dental implant, guided bone regeneration, factors impacting bone regeneration, treatment of bone and tissue loss, and bone regeneration in dental implants. Conclusion. BICOMB, VOSviewer, and other bibliometric tools revealed that dental implants, scaffolds, and factors impacting bone regeneration are hot research topics, while scaffolds also hold promise from the perspective of bone tissue regeneration.

scholarly journals Identification of research trends concerning application of stent implantation in the treatment of pancreatic diseases by quantitative and biclustering analysis: a bibliometric analysis

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7674 ◽  
Author(s):  
Xuan Zhu ◽  
Xing Niu ◽  
Tao Li ◽  
Chang Liu ◽  
Lijie Chen ◽  
...  
Keyword(s):  
Stent Implantation ◽  
High Frequency ◽  
Clinical Applications ◽  
Future Research ◽  
Fourth Quadrant ◽  
Medical Subject Headings ◽  
Pancreatic Diseases ◽  
Mesh Terms ◽  
Cluster Strategy ◽  
Occurrence Matrix

Objectives In recent years, with the development of biological materials, the types and clinical applications of stents have been increasing in pancreatic diseases. However, relevant problems are also constantly emerging. Our purpose was to summarize current hotspots and explore potential topics in the fields of the application of stent implantation in the treatment of pancreatic diseases for future scientific research. Methods Publications on the application of stents in pancreatic diseases were retrieved from PubMed without language limits. High-frequency Medical Subject Headings (MeSH) terms were identified through Bibliographic Item Co-Occurrence Matrix Builder (BICOMB). Biclustering analysis results were visualized utilizing the gCLUTO software. Finally, we plotted a strategic diagram. Results A total of 4,087 relevant publications were obtained from PubMed until May 15th, 2018. Eighty-three high-frequency MeSH terms were identified. Biclustering analysis revealed that these high-frequency MeSH terms were classified into eight clusters. After calculating the density and concentricity of each cluster, strategy diagram was presented. The cluster 5 “complications such as pancreatitis associated with stent implantation” was located at the fourth quadrant with high centricity and low density. Conclusions In our study, we found eight topics concerning the application of stent implantation in the treatment of pancreatic diseases. How to reduce the incidence of postoperative complications and improve the prognosis of patients with pancreatic diseases by stent implantation could become potential hotspots in the future research.

The theme trends and knowledge structure of H19 gene in cancer research: a scientometric analysis (Preprint)

2019 ◽  
Author(s):  
Zhigang Cui ◽  
Zhihua Yin ◽  
Lei Cui
Keyword(s):  
Cancer Research ◽  
Social Network ◽  
Citation Analysis ◽  
High Frequency ◽  
Cancer Metastasis ◽  
Intellectual Structure ◽  
Scientometric Analysis ◽  
Research Areas ◽  
Pivotal Study ◽  
Matrix Construction

BACKGROUND Background:H19 gene is maternally expressed imprinted oncofetal gene. This study aimed to explore distribution pattern and intellectual structure of H19 in cancer. OBJECTIVE Published scientific 826 papers related to H19 from Jan 1st, 2000 to March 22st, 2019 were obtained from the Web of Science core collection. METHODS We performed extraction of keywords and co-word matrix construction using BICOMB software. Then gCLUTO software, ucinet, excel software, Citespace, Vosviewer were successfully used for double -cluster analysis, social network analysis, Strategic coordinate analysis, co-citation analysis, and journal analysis. RESULTS We analyzed the distributions of included article of H19, identified 34 high-frequency keywords and classified them into 6 categories. Through co-word analysis and co-citation analysis for these categories, we identified the hotspot areas and intellectual basis about H19 in cancer research. Then the prospects of hotspots and their associations were accesssed by strategic coordinate diagrams and social network diagrams. CONCLUSIONS 6 research categories of 34 high-frequency keywords could represent the theme trends on H19 to some extent. Mir-675, cancer metastasis and risk, Wnt/β-catenin signaling pathway, SNP, and ceRNA network were core and mature research areas in this field. There is a lack of promising areas of H19 research. Matouk(2006) article play a key role in H19 research, and Murphy SK(2006)and Luo M(2013) articles serve knowledge transmission as pivotal study.

scholarly journals Living on the streets: An integrative review about the care for homeless people

2019 ◽  
Vol 72 (1) ◽  
pp. 211-220
Author(s):  
Fabiana Ferreira Koopmans ◽  
Donizete Vago Daher ◽  
Sonia Acioli ◽  
Vera Maria Sabóia ◽  
Crystiane Ribas Batista Ribeiro ◽  
...  
Keyword(s):  
Homeless People ◽  
Homeless Persons ◽  
Essential Elements ◽  
Support Network ◽  
Health Decision Making ◽  
Mesh Terms ◽  
Scientific Papers ◽  
Health Decision ◽  
The Subject ◽  
Care Practices

ABSTRACT Objective: To identify essential elements in care practices for the Homeless Persons in the context of Primary Health Care and verify evidence and strength of recommendation for health decision-making. Method: Integrative literature review, using Health Descriptors, keywords and "MeSH terms" in the databases: LILACS, PubMed Centre and Web of Science. Results: Twenty-two scientific papers were selected and grouped into three categories: Understanding of the Other, Support Network and Emancipatory Care. The study identified important elements for the development of care, such as understanding Homeless Persons, valuing network care and Emancipatory Care. Conclusion: There was a need for further studies and research on the subject, which would make it possible to construct more equitable and inclusive health policies and actions for this population that needs very unique elements in care practices.

Mapping knowledge structure by keyword co-occurrence and social network analysis

2018 ◽  
Vol 36 (4) ◽  
pp. 636-650 ◽  
Author(s):  
Fei-Fei Cheng ◽  
Yu-Wen Huang ◽  
Hsin-Chun Yu ◽  
Chin-Shan Wu
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Academic Library ◽  
Knowledge Structure ◽  
Visual Exploration ◽  
Bibliographic Databases ◽  
Research Issues ◽  
Content Type ◽  
The Usa

Purpose The purpose of this paper is to present the knowledge structure based on the articles published in Library Hi Tech. The research hotspots are expected to be revealed through the keyword co-occurrence and social network analysis. Design/methodology/approach Data sets based on publications from Library Hi Tech covering the time period from 2006 to 2017 were extracted from Web of Science and developed as testbeds for evaluation of the CiteSpace system. Highly cited keywords were analyzed by CiteSpace which supports visual exploration with knowledge discovery in bibliographic databases. Findings The findings suggested that the percentage of publications in the USA, Germany, China, and Canada are high. Further, the most popular keywords identified in Library Hi Tech were: “service,” “technology,” “digital library,” “university library,” and “academic library.” Finally, four research issues were identified based on the most-cited articles in Library Hi Tech. Originality/value While keyword plays an important role in scientific research, limited studies paid attention to the keyword analysis in librarian research. The contribution of this study is to systematically explore the knowledge structure constructed by the keywords in Library Hi Tech.

Numerical Investigation of Mechanisms Underlying Oceanic Internal Gravity Wave Power-Law Spectra

2020 ◽  
Vol 50 (9) ◽  
pp. 2713-2733
Author(s):  
Yulin Pan ◽  
Brian K. Arbic ◽  
Arin D. Nelson ◽  
Dimitris Menemenlis ◽  
W. R. Peltier ◽  
...  
Keyword(s):  
Power Law ◽  
Gravity Waves ◽  
High Frequency ◽  
Internal Gravity Wave ◽  
Numerical Data ◽  
Field Measurements ◽  
Internal Gravity Waves ◽  
Collision Integral ◽  
Turbulence Theory ◽  
Nonlinear Interactions

AbstractWe consider the power-law spectra of internal gravity waves in a rotating and stratified ocean. Field measurements have shown considerable variability of spectral slopes compared to the high-wavenumber, high-frequency portion of the Garrett–Munk (GM) spectrum. Theoretical explanations have been developed through wave turbulence theory (WTT), where different power-law solutions of the kinetic equation can be found depending on the mechanisms underlying the nonlinear interactions. Mathematically, these are reflected by the convergence properties of the so-called collision integral (CL) at low- and high-frequency limits. In this work, we study the mechanisms in the formation of the power-law spectra of internal gravity waves, utilizing numerical data from the high-resolution modeling of internal waves (HRMIW) in a region northwest of Hawaii. The model captures the power-law spectra in broad ranges of space and time scales, with scalings ω−2.05±0.2 in frequency and m−2.58±0.4 in vertical wavenumber. The latter clearly deviates from the GM76 spectrum but is closer to a family of induced-diffusion-dominated solutions predicted by WTT. Our analysis of nonlinear interactions is performed directly on these model outputs, which is fundamentally different from previous work assuming a GM76 spectrum. By applying a bicoherence analysis and evaluations of modal energy transfer, we show that the CL is dominated by nonlocal interactions between modes in the power-law range and low-frequency inertial motions. We further identify induced diffusion and the near-resonances at its spectral vicinity as dominating the formation of power-law spectrum.

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