Profiling COVID-19 research in the social sciences from Indonesia based on Scopus database

This study provides insights into the pattern of COVID-19 research publications in Indonesia and aims to map out the contributions of social science scholars in the country during the pandemic, using bibliometric analysis. The analysis was conducted through desk research using the scientometric method from the Scopus database, with a total of 1,037 articles analysed. The research found that social sciences scholars in Indonesia made significant contributions to the fields of online learning, economics, business and management, public health and administration, and communication and media studies. The study also identified the influences of research areas, funding, open access, female first author, female co-authors, and international collaborative research on quartile and the number of citations. The implications of the study suggest that efforts should be made to promote gender diversity in research, allocate research funding appropriately, and encourage international collaboration. Authors should prioritize publishing in high quartile journals and opt for open access publication. Additionally, academic institutions and funding agencies should provide guidance on selecting reputable journals to maintain a culture of quality research.

Bibliometric analysis of treating COVID-19 with combined traditional Chinese and western medicine based on citespace

Objective: This study focused on the systematic literature measurement and visual analysis of treating COVID-19 with combined Chinese and Western medicine to explore the development status, research hot spots and trends, and cutting-edge dynamics. It provides data, information support, and development references for treating COVID-19with combined Chinese and Western medicine. Methods: Three major databases of China National Knowledge Infrastructure(CNKI), Wanfang Data, and China Science and Technology Journal Database were used as data sources to retrieve the relevant literature on the combined Chinese and Western medicine for the treatment of COVID-19 from March2019 to March 2022. Statistical analysis was performed using bibliometric methods and CiteSpace software. Visual analysis was performed on publishing trends, research institution cooperation, author cooperation, keyword co-occurrence and clustering, and research hotspots. Results: A total of 476 articles were included in this study, with the largest number published in 2020. Statistical analysis of published units showed that the cooperative relationship between institutions was discrete, indicating that the research on treating novel coronavirus with combined Chinese and western medicine was extensive. Hot spots in the research were mainly reflected in four aspects:coronavirus, diagnosis and treatment plan, combined Chinese and Western medicine, and epidemic prevention and control. Conclusion: The research theme of treating COVID-19 with combined Chinese and Western medicine dynamically changes with the epidemic development, which is guided by clinical efficacy. It mainly focuses on the formulation of diagnosis and treatment plans. The cooperation between authors and institutions is insufficient, and communication needs to be further strengthened.

Analyzing the research trends of COVID-19 using topic modeling approach

PurposeThe COVID-19 pandemic has impacted 222 countries across the globe, with millions of people losing their lives. The threat from the virus may be assessed from the fact that most countries across the world have been forced to order partial or complete shutdown of their economies for a period of time to contain the spread of the virus. The fallout of this action manifested in loss of livelihood, migration of the labor force and severe impact on mental health due to the long duration of confinement to homes or residences.Design/methodology/approachThe current study identifies the focus areas of the research conducted on the COVID-19 pandemic. s of papers on the subject were collated from the SCOPUS database for the period December 2019 to June 2020. The collected sample data (after preprocessing) was analyzed using Topic Modeling with Latent Dirichlet Allocation.FindingsBased on the research papers published within the mentioned timeframe, the study identifies the 10 most prominent topics that formed the area of interest for the COVID-19 pandemic research.Originality/valueWhile similar studies exist, no other work has used topic modeling to comprehensively analyze the COVID-19 literature by considering diverse fields and domains.

"Research exceptionalism" in the COVID-19 pandemic: an analysis of scientific retractions in Scopus

This study aimed to outline the profile of retractions of scientific articles on COVID-19 published in journals indexed in the Scopus database between 2020 and 2021. To analyze the data, we used a bibliometric technique, with the Bibliometrix package in the R-Studio software, and descriptive statistics. Twenty-nine retractions were analyzed, and we found that the most common reasons for retraction were related to ethical issues and that 68.97% of authors have previously retracted articles. We concluded that there appears to have been a change in the publication policies of journals, which resulted in an increase in scientific retractions related to COVID-19 during the study period.

The Role of Technology in Physical Education Teaching in the Wake of the Pandemic

Physical education is seen as an essential subject for the development of healthy habits and well-being, in line with Sustainable Development Goal 3. Furthermore, the impact of technology on all aspects of life is now an undeniable reality. The field of education is no exception, and digitalisation has undoubtedly been accelerated by the emergency situation resulting from the COVID-19 pandemic. This paper aims to analyse the scientific production related to the field of physical education, technology, and the pandemic from a double perspective. From a search in Scopus, 86 articles were selected for analysis. A bibliometric approach was used to identify the variables of impact, collaboration, production, and dissemination. While the content analysis allowed us to delve deeper into the topics most frequently chosen by researchers, we found that the articles focused both on the circumstances experienced by practising teachers and on the adaptations made in the teaching/learning process with trainee teachers and students at different stages of education. Thus, technology has emerged as a fundamental tool in physical education during the pandemic, making it possible to develop or maintain better health and learning.

Current status and hotspot of Lonicera Japonica Flos research based on bibliometrics.

In order to comprehensively understand the research hotspots and development trends of Lonicera Japonica Flos in the past 20 years, and to provide intuitive data reference and objective opinions and suggestions for subsequent related research in this field, this study collected 8 871 Chinese literature and 311 English literature related to Lonicera Japonica Flos research in the core collection databases of Wanfang Data), CNKI and Web of Science (WOS) from 2002 to 2021, and conducted bibliometric and visual analysis using vosviewer. The results showed that the research on the active components of Lonicera Japonica Flos based on phenolic acid components, the research on the mechanism of novel coronavirus pneumonia based on data mining and molecular docking technology, and the pharmacological research on the anti-inflammatory and antiviral properties of Lonicera Japonica Flos are the three hot research directions in the may become the future research direction. In this paper, we analyze the research on Lonicera Japonica Flos from five aspects: active ingredients, research methods, formulation and preparation, pharmacological effects and clinical applications, aiming to reveal the research hotspots, frontiers and development trends in this field and provide predictions and references for future research.Copyright © Drug Evaluation Research 2022.

Research progress and future agenda of COVID-19 in tourism and hospitality: a timely bibliometric review

PurposeA proliferation of articles surrounding the COVID-19 pandemic is calling for new insights through review. This paper aims to bibliometrically analyze the current progress of research around hospitality and tourism to define the research directions on herd immunity and the prevention of disease under the "new normal.”Design/methodology/approachThis paper analyzed 326 articles regarding COVID-19 published in SSCI hospitality, leisure and tourism journals in 2020 and 2021 by combining manual analysis and bibliometrics to reveal research topics and to gain insight into research structures.FindingsThe results of this paper summarized topics related to stakeholders' mentality and behavior, responses of travel suppliers to the COVID-19 pandemic, economic impact and demand forecasting, social issues of human rights and racism and reflection on tourism and transformation of the industry. More research is called for in the future to focus on a better response to the crisis, including crisis management education and training and the improving the resilience of small- and medium-sized enterprises.Research limitations/implicationsA three-dimensional consideration was proposed to promote the sustainable development of hospitality and tourism.Originality/valueIn the "new normal” phase of herd immunity and disease prevention, to the best of the authors' knowledge, this is the first paper that provides an up-to-date systematic overview of the evolution of COVID-19 research in tourism and hospitality and encourages more conceptual, practical and futuristic studies.

A Bibliometric Analysis of Sustainable Food Consumption: Historical Evolution, Dominant Topics and Trends

The major goal of this study is to trace the emergence of SFC-related research across time, using a thematic map and a list of corresponding publications. In addition, this study aims to determine the author who has made the most significant contribution to this particular field. This study provides a comprehensive bibliometric analysis of the historical development and current trends in sustainable food consumption research, examining 2265 articles published between 1990 and 2023. Using the bibliometrics package of R Studio software version 4.2.1 and its Biblioshiny package, articles from the Scopus and Web of Science databases are examined. In the field of sustainable food consumption, we identify five distinct research phases: initial stagnation, infant growth, post-economic crisis, expanding phase and COVID-19 and post-pandemic. While research on broader sustainability topics can be traced back to the early 20th century, a very limited number of articles on sustainable food consumption was published in the 1990s. However, the number of publications increased incrementally over time, with a notable uptick in interest around 2015, and the subject was still being discussed in 2022. The emergence of the COVID-19 pandemic marked the beginning of the most recent phase of research, which analyzed the consumption patterns of consumers before and after the pandemic. Our study highlights key authors, documents and sources related to sustainable food consumption. The United States, Italy and the United Kingdom emerged as the most active contributors to the research on sustainable food consumption and were additionally the countries with the largest global market shares for organic products. Major sub-themes including organic food, food waste, sustainable development and food security, together with consumer behavior and organic products appeared as being the most researched sub-themes of recent times. The results of this study suggest that more research is related to sustainable food consumption in countries with a low organic food market share. In addition, the investigation of actual data on food waste, carbon footprints and greenhouse gas emissions resulting from food production and consumption is essential to gain holistic insights.

A twenty years bibliometric analysis (2002 – 2021) of business economics research in ASEAN

ASEAN is predicted to be the world's largest single market by 2030, after the US, China, and the EU. This study aims to discover research performance in all ASEAN countries, including identifying output levels, research focus, and influential authors in the region. The approach used in this study is a bibliometric analysis of publications indexed in the WoS database for the past two decades (2002–2021). Of the more than 20,000 documents analyzed, it was indicated that each ASEAN country has exclusive and non-exclusive keywords. Singapore has the highest number of citations among the other ASEAN countries.

VUCA bibliometric and content analysis

VUCA is an acronym for volatility, uncertainty, complexity, and ambiguity, used to describe an environment that defies confident predictions. An example of this environment is the Covid-19 pandemic, which has created uncer-tainty worldwide because it is an unknown and highly contagious disease that neither society nor institutions were pre-pared to face. This article aims to describe the scientific production of VUCA to understand its main research focus. This research analyzes 105 documents from the Web of Science (WoS) database using Bibliometrics and Content Analysis. The bibliometric analysis reported several production indexes: annual, personal, national, institutional, and journal productiv-ity. The content analysis analyzed 95 article s in nineteen clusters selected by comparing two clustering methods, Latent Dirichlet Allocation and K-Means, using the coherence and silhouette indices, respectively. VUCA is an emerging topic with increased scientific production in the last four years. However, there are no major producers to date. The most frequent topics are management, leadership, and change, where several works emphasize the role of the leader in deal-ing with change. The literature has focused on understanding the skills needed to cope with a VUCA environment and how to teach them. In addition, the use of two methods based on machine learning techniques to estimate the number of clusters of scientific papers is highlighted as an alternative to splitting articles into topics when the dataset is small. © 2023 CSIC. Este es un artículo de acceso abierto distribuido bajo los términos de la licencia de uso y distribución Creative Commons Reconocimiento 4.0 Internacional (CC BY 4.0).

Analisis bibliometrico y de contenido sobre VUCA

analysis : VUCA is an acronym for volatility, uncertainty, complexity, and ambiguity, used to describe an environment that defies confident predictions. An example of this environment is the Covid-19 pandemic, which has created uncer-tainty worldwide because it is an unknown and highly contagious disease that neither society nor institutions were pre-pared to face. This article aims to describe the scientific production of VUCA to understand its main research focus. This research analyzes 105 documents from the Web of Science (WoS) database using Bibliometrics and Content Analysis. The bibliometric analysis reported several production indexes: annual, personal, national, institutional, and journal productiv-ity. The content analysis analyzed 95 article s in nineteen clusters selected by comparing two clustering methods, Latent Dirichlet Allocation and K-Means, using the coherence and silhouette indices, respectively. VUCA is an emerging topic with increased scientific production in the last four years. However, there are no major producers to date. The most frequent topics are management, leadership, and change, where several works emphasize the role of the leader in deal-ing with change. The literature has focused on understanding the skills needed to cope with a VUCA environment and how to teach them. In addition, the use of two methods based on machine learning techniques to estimate the number of clusters of scientific papers is highlighted as an alternative to splitting articles into topics when the dataset is small.

Antecedents of digital supply chains for a circular economy: a sustainability perspective

PurposeA digital supply chain (DSC) positively enhances circular economy (CE) practices. However, what factors and conditions lead to the implementation of DSC for transitioning toward CE is not yet clear. Therefore, this study aims at identifying and subsequently analyzing the antecedents of DSC for CE.Design/methodology/approachThe study identifies major antecedents of DSC for CE to achieve sustainability objectives through literature review and expert opinions. In this study, 19 potential antecedents of DSCs for CE are established from the literature and suggestions from industry professionals. A trapezoidal fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach is applied quantitatively to investigate the antecedents identified.FindingsConducted in the context of Indian automobile manufacturing industry, the findings of the study reflect that advanced information sharing arrangement, effective government policies for DSC and CE implementation and digitalizing the supply chains are the top three potential antecedents of DSC for a CE.Originality/valueIn the existing literature, few studies are specific to investigating the DSC and CE paradigm. The present study will help organizations develop a practical and integrated strategic approach that will foster DSC through improved knowledge of CE.

Physical exercise and COVID-19: a bibliometric analysis

INTRODUCTION: To carry out a retrospective bibliometric analysis of articles, published since the beginning of the pandemic, which addressed the topic of physical exercise and COVID-19, in order to provide a reference of origin for research on the topic. EVIDENCE ACQUISITION: This is a bibliometric study, which addressed the production / dissemination, through information recorded in the PubMed database, about physical exercise and COVID-19, published since the beginning of the pandemic. EVIDENCE SYNTHESIS: 111 publications in total were retrieved from PubMed in the first round of research and 93 publications were identified after reviewing the study titles and s. Eligibility was assessed for these 93 publications throughout the text and 76 were entered after removing duplicates and irrelevant records. According to Bradford's Law, we identified 76 publications in 53 journals from seven different countries. The countries of the journals that published the most were the United States (20, 37.7%) and the United Kingdom (15, 28.3%). The journals that most published on the subject were: European Journal of Physical and Rehabilitation Medicine, Obesity, Encephale and Progress in Cardiovascular Diseases, each with 03 studies. According to Lotka's Law, the most productive authors: Lavie CJ Smith I, with 4 articles published. When evaluating the word frequencies by Zipf's Law, it was observed that 16 words had at least 10 occurrences, with the words Covid-19, Exercise and Pandemic with 80, 39 and 38 occurrences respectively. CONCLUSION(S): According to our analysis, this research provides a current scenario of how studies related to physical exercise and COVID-19 are going on in the world, serving as a reference for researchers on this topic.Copyright © 2020 EDIZIONI MINERVA MEDICA.

A comparison study of topic modeling based literature analysis by using full texts and abstracts of scientific articles: a case of COVID-19 research

PurposeHow to extract useful information from a very large volume of literature is a great challenge for librarians. Topic modeling technique, which is a machine learning algorithm to uncover latent thematic structures from large collections of documents, is a widespread approach in literature analysis, especially with the rapid growth of academic literature. In this paper, a comparison of topic modeling based literature analysis has been done using full texts and s of articles.Design/methodology/approachThe authors conduct a comparison study of topic modeling on full-text paper and corresponding to assess the influence of the different types of documents been used as input for topic modeling. In particular, the authors use the large volumes of COVID-19 research literature as a case study for topic modeling based literature analysis. The authors illustrate the research topics, research trends and topic similarity of COVID-19 research by using Latent Dirichlet allocation (LDA) and topic visualization method.FindingsThe authors found 14 research topics for COVID-19 research. The authors also found that the topic similarity between using full-text paper and corresponding is higher when more documents are analyzed.Originality/valueFirst, this study contributes to the literature analysis approach. The comparison study can help us understand the influence of the different types of documents on the results of topic modeling analysis. Second, the authors present an overview of COVID-19 research by summarizing 14 research topics for it. This automated literature analysis can help specialists in the health and medical domain or other people to quickly grasp the structured morphology of the current studies for COVID-19.

Side Effects of COVID-19 Vaccine in Pregnant Women: A Bibliometric Study

Introduction: Side effects related to COVID-19 vaccination are short-lived and disappear within a few days and can affect both pregnant and nonpregnant women. Aim(s): To evaluate the bibliometric profile of the worldwide scientific production on the side effects of COVID-19 vaccine in pregnant women, in Scopus. Material(s) and Method(s): A retrospective, cross-sectional, bibliometric study that analyzed metadata published in scientific journals indexed in Scopus during 2019 and 2021. The search and download of the papers were performed on May 13, 2022, and the SciVal program was used for the measurement of the bibliometric indicators. Result(s): The Lancet Infectious Diseases and International Journal of Gynecology and Obstetrics had the highest impact with 24.8 and 14.3 citations per publication, respectively. The institutions with the highest number of papers were Harvard University and National Institutes of Health, with 13 papers, respectively. Goldfarb Ilona Telefus, Kampmann Beate, and Khalil Asma were the authors with the highest number of papers, with 3 each. Only one publication on the side effects of COVID-19 vaccine in pregnant women was identified in 2019, whereas the highest scientific output was identified in 2021, with 127, of which 67 were from Q1. Conclusion(s): In Scopus, there is an increase in the production of papers on the side effects of the vaccine against COVID-19 in pregnant women, with the United States being the country with the most institutions with the highest scientific production. However, over the years, the quartile of the journals where these studies were published decreased.Copyright © The Author(s).

AC317 The Plant Phenome Journal editorial board

An initial quality control check was completed for the journal and magazine content and a check of the books content is currently under way. Authors make edits directly to the HTML article file, which cuts down time to publication and reduces errors introduced during typesetting. [...]far we've received positive response and hope to expand this program to additional titles. [...]the group reviewed mismatched guidelines and adopted a standardized Scientific Misconduct Statement for all 13 journals to create uniformity across the journal collection. The JIF is one tool used to evaluate a journal's relative importance when compared with other journals in the same study area.

COVID-19 knowledge deconstruction and retrieval: an intelligent bibliometric solution.

COVID-19 has been an unprecedented challenge that disruptively reshaped societies and brought a massive amount of novel knowledge to the scientific community. However, as this knowledge flood continues surging, researchers have been disadvantaged by not having access to a platform that can quickly synthesize emerging information and link the new knowledge to the latent knowledge foundation. Aiming to fill this gap, we propose a research framework and develop a dashboard that can assist scientists in identifying, retrieving, and understanding COVID-19 knowledge from the ocean of scholarly articles. Incorporating principal component decomposition (PCD), a knowledge mode-based search approach, and hierarchical topic tree (HTT) analysis, the proposed framework profiles the COVID-19 research landscape, retrieves topic-specific latent knowledge foundation, and visualizes knowledge structures. The regularly updated dashboard presents our research results. Addressing 127,971 COVID-19 research papers from PubMed, the PCD topic analysis identifies 35 research hotspots, along with their inner correlations and fluctuating trends. The HTT result segments the global knowledge landscape of COVID-19 into clinical and public health branches and reveals the deeper exploration of those studies. To supplement this analysis, we additionally built a knowledge model from research papers on the topic of vaccination and fetched 92,286 pre-Covid publications as the latent knowledge foundation for reference. The HTT analysis results on the retrieved papers show multiple relevant biomedical disciplines and four future research topics: monoclonal antibody treatments, vaccinations in diabetic patients, vaccine immunity effectiveness and durability, and vaccination-related allergic sensitization.

Leadership and international collaboration on COVID-19 research: reducing the North-South divide?

The COVID-19 pandemic triggered unprecedented scientific efforts worldwide and launched several initiatives to promote international cooperation. Because international scientific collaborations between high-income countries (HICs) and low- and middle-income countries (LMICs) are not always balanced, analyzing research leadership helps to understand the global dynamics of knowledge production during COVID-19. In this study, we focused on HIC-LMIC collaborations on COVID-19 research in 469,937 scientific publications during the first 2 years of the pandemic (2020-2021). Co-authorship and authors' affiliation were used to identify international collaborations, according to country income level. The leadership analysis considered the countries of the first and last authors of publications. The results show that (i) most publications with international collaborations (49.3%) involved researchers from HICs and LMICs; (ii) collaborative research between HICs and LMICs addressed relevant public health needs; (iii) HIC-LMIC collaborations were primarily led by researchers from the United States, China, the United Kingdom, and India; (iv) most HIC-LMIC publications (44%) had shared leadership, with research interests linked to national expertise and global interests. This study contributes to the analysis of research collaborations on COVID-19 and sheds light on North-South relations in the production and dissemination of scientific knowledge.

Trends Analysis of Virtual Reality Research between 1987 and 2021

The COVID-19 pandemic has dramatically altered the way how we communicate with others. From ZOOM to Meta-verse, an increasing number of people are shifting to the virtual world for work and personal life. However, as a technology, virtual reality is still considered merely a device for immersive gaming for the young generation. Thus, despite itspotential, virtual reality is hardly discussed as acore technology enabling Metaverse, which provides a virtual world for everyone. Therefore, it is necessary to examine prior studies for an understanding full spectrum of virtual reality research. There are three primary aims of this study: 1. To trace the history of virtual reality research for providing a holisticview oftheresearch trajectory. 2. Todiscover prevalent topics during the last 34 years as well as highly cited papers and authors. 3. To find hub topics for identifying the direction of interdisciplinary research. © 2022, Tamkang University. All rights reserved.

Academic Framing of Computational Representations in the Virtual Classroom during Covid-19

Keywords: Agenda;Framing;Social representations;Expectations;Computer Introduction The development of research projects often requires the competition of computers, software and data analysis techniques, but the acceptance, appropriation and intensive use of them presents limitations in terms of utility and risk expectations [1]. Some explanatory models of human capital formation suggest that the formation of talent or intellectual capital in intangible assets of organizations is due to habitus [3]. [...]the predictive models of the social representations of these determinants have not been observed in the explanation of the relations with the intensive use of technologies, devices and electronic networks. [...]the objective of the present work was to establish the academic link relative to the social representations of computer computers, considering the dimensions of the organizational, educational and cognitive models. Methodology A documentary, retrospective and exploratory study was carried out with a selection of sources indexed to international repositories Table 1, considering the indexing period from 2019 to 2021, as well as the search by allusive keywords for negative (stigma, risk, rejection) and positive (utility, acceptance, appropriation) (Table 1) Content analysis and opinion matrices were used, considering the inclusion of findings, ratings and comparisons of coded data such as;-1 for negative dimensions (stigma, risk and rejection) and +1 for positive dimensions (utility, acceptance and appropriation) The qualitative data analysis package was used, considering equation (1) in which the contingency relations and the proportions of probabilities of taking risks in permissible thresholds of human capital formation stand out The contrast of the null hypotheses was made from the estimation of these parameters.