scholarly journals Why IEEE Xplore Matters for Research Trend Analysis in the Energy Sector

2021 ◽  
pp. 44-58
Author(s):  
B. Chigarev
Keyword(s):  
Growth Rate ◽  
Conference Proceedings ◽  
Association Rules ◽  
Web Of Science ◽  
Research Trends ◽  
Research Trend ◽  
Bibliometric Data ◽  
Author Keywords ◽  
Key Terms ◽  
Over Time

The paper aims to briefly compare and analyze the results of queries to IEEE Xplore and the leading abstract databases Scopus and Web of Science to identify research trends. Some errors were revealed in the Author Keywords in Web of Science. Therefore, a more detailed analysis that involved comparing various types of key terms was made only for IEEE Xplore and Scopus platforms. The study employed IEEE Access journal metadata as indexed on both platforms. Sample matching for IEEE Xplore and Scopus was achieved by comparing DOI. The IEEE Xplore metadata contains more key term types, which provides an advantage in analyzing research trends. Using NSPEC Controlled Terms from expert-compiled vocabulary provides more stable data, which gives an advantage when considering the change of terms over time. Apriori, an algorithm for finding association rules, was used to compare the co-occurrence of the terms for a more detailed description of sample subjects on both platforms. VOSviewer was used to analyze trends in scientific research based on IEEE Xplore data. The 2011-2021 ten-year period was divided into two sub-intervals for comparing the occurrence of Author Keywords, IEEE Terms, and NSPEC Controlled Terms. Bibliometric data of the IEEE conference proceedings was used to illustrate the importance of context in estimating the growth rate of publishing activity on a topic of interest.

scholarly journals Why IEEE Xplore Matters for Research Trend Analysis in the Energy Sector

2021 ◽  
Author(s):  
Boris Chigarev
Keyword(s):  
Conference Proceedings ◽  
Web Of Science ◽  
Research Trends ◽  
Research Trend ◽  
Bibliometric Data ◽  
Different Types ◽  
Author Keywords ◽  
Comparison And Analysis ◽  
Key Terms ◽  
Over Time

The article is aimed at a brief comparison and analysis of the results of queries to IEEE Xplore and the leading abstract databases Scopus and Web of Science to identify research trends. Some errors in the Author Keywords in Web of Science have been revealed. Therefore, a more detailed analysis was conducted by comparing different types of key terms for IEEE Xplore and Scopus platforms only. I used IEEE Access journal metadata as indexed on both platforms. The sample match for IEEE Xplore and Scopus was achieved by comparing DOI. The IEEE Xplore metadata contains more types of key terms, which provides an advantage in analyzing research trends. Using NSPEC Controlled Terms from expert-compiled vocabulary provides a more stable data, which gives an advantage when considering the change of terms over time. Apriori, an algorithm for finding association rules, has been used to compare co-occurrence of terms for a more detailed description of sample subjects on both platforms. VOSviewer was used to analyze trends in scientific research based on IEEE Xplore data. The 2011-2021 ten-year period was divided into two sub-intervals for comparing the occurrence of Author Keywords, IEEE Terms, and NSPEC Controlled Terms. Using the IEEE conference proceedings bibliometric data, I illustrated the importance of context in estimating the rate of growth of publishing activity on a topic of interest.

scholarly journals Bibliometric Analysis of Microtia-Related Publications From 2006 to 2020

2021 ◽  
pp. 014556132110376
Author(s):  
Wei Wang ◽  
Xinxin Dong ◽  
Jianwen Qu ◽  
Yangyang Lin ◽  
Lei Liu
Keyword(s):  
Core Collection ◽  
Web Of Science ◽  
The United States ◽  
Research Trends ◽  
External Ear ◽  
Future Directions ◽  
Occurrence Matrix ◽  
Author Citations ◽  
Over Time

Objective: Microtia is a congenital auricular malformation with a hypoplastic external ear that ranges in severity from a slightly smaller auricle to complete the absence of the auricle. The present study was conducted to identify and analyze the characteristics of microtia-related articles published from 2006 to 2020 by using bibliometric analyses. Method: Microtia-related studies published from 2006 to 2020 were retrieved from the Web of Science Core Collection database. Keywords, first author, citations, date of publication, and publication journal were extracted and quantitatively analyzed using Bibliographic Item Co-Occurrence Matrix Builder software and the Bibliometric ( https://bibliometric.com/app ). VOSviewer was used to visualize research and form a network map on keywords and citations. Results: A total of 1031 articles from 2006 to 2020 were included. The number of articles showed an overall trend of growth over time. The United States and China are the top 2 countries in terms of the number of microtia-related articles. From the analysis of keyword clustering, keywords could be mainly divided into 4 clusters in the field of microtia research: surgery, tissue engineering, epidemiology, and rehabilitation including hearing-related treatments, evaluation of effects, and quality of life after surgery. The top 10 most frequently cited papers from 2006 to 2020 were also extracted and analyzed. Conclusion: A bibliometric research of microtia-related articles from 2006 to 2020 was conducted. This study may be helpful to understand the current research status of microtia and find the research trends in this field, thus proposing future directions for microtia research.

scholarly journals 30 years of parasitology research analysed by text mining

Parasitology ◽  
2020 ◽  
Vol 147 (14) ◽  
pp. 1643-1657
Author(s):  
John T. Ellis ◽  
Bethany Ellis ◽  
Antonio Velez-Estevez ◽  
Michael P. Reichel ◽  
Manuel J. Cobo
Keyword(s):  
Text Mining ◽  
Research Productivity ◽  
Web Of Science ◽  
Research Trends ◽  
Major Research ◽  
Research Themes ◽  
Antiparasitic Drugs ◽  
Over Time

AbstractBibliometric methods were used to analyse the major research trends, themes and topics over the last 30 years in the parasitology discipline. The tools used were SciMAT, VOSviewer and SWIFT-Review in conjunction with the parasitology literature contained in the MEDLINE, Web of Science, Scopus and Dimensions databases. The analyses show that the major research themes are dynamic and continually changing with time, although some themes identified based on keywords such as malaria, nematode, epidemiology and phylogeny are consistently referenced over time. We note the major impact of countries like Brazil has had on the literature of parasitology research. The increase in recent times of research productivity on ‘antiparasitics’ is discussed, as well as the change in emphasis on different antiparasitic drugs and insecticides over time. In summary, innovation in parasitology is global, extensive, multidisciplinary, constantly evolving and closely aligned with the availability of technology.

Sustainable Innovation: worldwide trends in the scientific production through a bibliometric study

2021 ◽  
pp. 49-54
Author(s):  
Rosanna Cataldo ◽  
Corrado Crocetta ◽  
Maria Gabriella Grassia ◽  
Paolo Mazzocchi ◽  
Antonella Rocca ◽  
...  
Keyword(s):  
Bibliometric Analysis ◽  
Web Of Science ◽  
Scientific Production ◽  
Research Trends ◽  
Bibliometric Study ◽  
Business Practices ◽  
Innovation Research ◽  
Sustainable Innovation ◽  
The Status ◽  
Over Time

The scientific production on the Innovation, especially on Sustainable Innovation, has grown in recent years. Various expressions and definitions for sustainability and innovation have been reported in the literature. Sometimes the two concepts are combined and described with one term, Sustainable Innovation. Research on sustainable innovation has grown in popularity due to the need to incorporate sustainability within business practices. The purpose of this study is to investigate the status and the evolution of the scientific studies on this topic and identify the worldwide trends in scientific production over time through a research conducted on the metadata of Web of Science, a database commonly used by researchers. A bibliometric analysis has been developed to analyse a total of 1,511 documents published between 2000 and 2021 in order to discover the research trends in this field and the main dimensions and words related to the term “Sustainable Innovation”.

scholarly journals Past Themes and Tracking Research Trends in Entrepreneurship: A Co-Word, Cites and Usage Count Analysis

2019 ◽  
Vol 11 (11) ◽  
pp. 3121 ◽  
Author(s):  
Luis Javier Cabeza Ramírez ◽  
Sandra M. Sánchez-Cañizares ◽  
Fernando J. Fuentes-García
Keyword(s):  
Longitudinal Study ◽  
Web Of Science ◽  
Research Trends ◽  
Future Research ◽  
Reference Database ◽  
Research Topics ◽  
Main Research ◽  
The Core ◽  
Conceptual Evolution ◽  
Over Time

This paper examines the evolution of research in Entrepreneurship published in Web of Science, a reference database. A bibliometric content analysis has been carried out as part of this investigation, allowing for a longitudinal study of the main research topics dealt with over time, ranging from classic topics such as its conception to more recent realities that include Social and Sustainable Entrepreneurship. This paper locates research trends by studying the evolution of citations and by incorporating use metrics. The results point to the existence of seven cognitive fronts that have marked the field’s growth and conceptual evolution. Furthermore, evidence is presented that shows how innovation has historically been the thread that links all the core themes. The topics and trends detected contribute specially to advancing the current discussion on entrepreneurship and coordinating future research efforts.

scholarly journals Review of Research Trends in Learning and the Internet in Higher Education

2020 ◽  
Vol 9 (6) ◽  
pp. 101 ◽  
Author(s):  
Adrián Segura-Robles ◽  
Antonio-José Moreno-Guerrero ◽  
María-Elena Parra-González ◽  
Jesús López-Belmonte
Keyword(s):  
Web Of Science ◽  
Scientific Literature ◽  
The United States ◽  
Research Trends ◽  
University Teaching ◽  
The Internet ◽  
E Learning ◽  
Use Of The Internet ◽  
Over Time ◽  
The Web

Within the scientific literature, there has been much debate about the use of the Internet in teaching in university contexts. The potential of this tool and its educational possibilities is well documented. The main purpose of this study is to analyze the use of the Internet in university teaching from a bibliometric perspective. To analyze scientific works, scientific mapping strategies have been used; for example, exploring the co-words and co-authors in works on this topic. We have worked with an analysis unit of 5118 documents which are indexed in the Web of Science database. Among the findings of this research, it can be highlighted that most publications are in English—the topic has been thoroughly studied and works have been published in this language over time. Moreover, the United States is the country which is most productive in relation to educational and computing fields. The most relevant topics themes are “e-learning”, “systems” and “Internet of Things”.

Research output, intellectual structures and contributors of digital humanities research: a longitudinal analysis 2005–2020

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fangli Su ◽  
Yin Zhang
Keyword(s):  
Digital Humanities ◽  
Web Of Science ◽  
Research Output ◽  
Content Type ◽  
Major Development ◽  
The Status ◽  
Author Keywords ◽  
Visualization Tools ◽  
Key Terms ◽  
Longitudinal Examination

PurposeThis study aims to update and extend previous efforts gauging the status of the quickly evolving field of digital humanities (DH). Based on a sample of directly relevant DH literature during 2005–2020 from Web of Science, the study conducts a longitudinal examination of the research output, intellectual structures and contributors.Design/methodology/approachThe study applies bibliometric methods, social network analysis and visualization tools to conduct a longitudinal examination.FindingsThe research output and scope of DH topics has grown over time with a widening and deepening field in four major development stages. Through both term frequency and term co-occurrence relationship networks, this study further identifies four major reoccurring topics and themes of DH research: (1) collections and contents; (2) technologies, techniques, theories and methods; (3) collaboration, interdisciplinarity and support and (4) DH evolution. Finally, leading DH research contributors (authors, institutions and nations) are also identified.Originality/valueThis study utilizes a greater number of and richer subject sources than previous efforts to identify the overall intellectual structures of DH research based on key terms from titles, abstracts and author keywords. It expands on previous efforts and furthers our understanding of DH research with more recent DH literature and richer subject sources from the literature.

scholarly journals Research trends of posttraumatic growth from 1996 to 2020: A bibliometric analysis based on Web of Science and CiteSpace

2021 ◽  
Vol 3 ◽  
pp. 100052
Author(s):  
Wen-Jing Kou ◽  
Xiao-Qin Wang ◽  
Yang Li ◽  
Xiao-Han Ren ◽  
Jia-Ru Sun ◽  
...  
Keyword(s):  
Posttraumatic Growth ◽  
Bibliometric Analysis ◽  
Web Of Science ◽  
Research Trends

scholarly journals A Bibliometric Network Analysis of Coronavirus during the First Eight Months of COVID-19 in 2020

2021 ◽  
Vol 18 (3) ◽  
pp. 952 ◽  
Author(s):  
Leonardo B. Furstenau ◽  
Bruna Rabaioli ◽  
Michele Kremer Sott ◽  
Danielli Cossul ◽  
Mariluza Sott Bender ◽  
...  
Keyword(s):  
Decision Making ◽  
Network Analysis ◽  
Web Of Science ◽  
Future Research ◽  
Future Trends ◽  
Damage Prevention ◽  
Over Time ◽  
The Web

The COVID-19 pandemic has affected all aspects of society. Researchers worldwide have been working to provide new solutions to and better understanding of this coronavirus. In this research, our goal was to perform a Bibliometric Network Analysis (BNA) to investigate the strategic themes, thematic evolution structure and trends of coronavirus during the first eight months of COVID-19 in the Web of Science (WoS) database in 2020. To do this, 14,802 articles were analyzed, with the support of the SciMAT software. This analysis highlights 24 themes, of which 11 of the more important ones were discussed in-depth. The thematic evolution structure shows how the themes are evolving over time, and the most developed and future trends of coronavirus with focus on COVID-19 were visually depicted. The results of the strategic diagram highlight ‘CHLOROQUINE’, ‘ANXIETY’, ‘PREGNANCY’ and ‘ACUTE-RESPIRATORY-SYNDROME’, among others, as the clusters with the highest number of associated citations. The thematic evolution. structure presented two thematic areas: “Damage prevention and containment of COVID-19” and “Comorbidities and diseases caused by COVID-19”, which provides new perspectives and futures trends of the field. These results will form the basis for future research and guide decision-making in coronavirus focused on COVID-19 research and treatments.

scholarly journals Cancer Research Trend Analysis Based on Fusion Feature Representation

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 338
Author(s):  
Jingqiao Wu ◽  
Xiaoyue Feng ◽  
Renchu Guan ◽  
Yanchun Liang
Keyword(s):  
Cancer Research ◽  
Trend Analysis ◽  
Research Trends ◽  
Feature Representation ◽  
Research Trend ◽  
Good Representation ◽  
Text Representation ◽  
Classical Text ◽  
Representation Model ◽  
Text Feature

Machine learning models can automatically discover biomedical research trends and promote the dissemination of information and knowledge. Text feature representation is a critical and challenging task in natural language processing. Most methods of text feature representation are based on word representation. A good representation can capture semantic and structural information. In this paper, two fusion algorithms are proposed, namely, the Tr-W2v and Ti-W2v algorithms. They are based on the classical text feature representation model and consider the importance of words. The results show that the effectiveness of the two fusion text representation models is better than the classical text representation model, and the results based on the Tr-W2v algorithm are the best. Furthermore, based on the Tr-W2v algorithm, trend analyses of cancer research are conducted, including correlation analysis, keyword trend analysis, and improved keyword trend analysis. The discovery of the research trends and the evolution of hotspots for cancers can help doctors and biological researchers collect information and provide guidance for further research.

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