Discovering temporal scientometric knowledge in COVID-19 scholarly production

Co-Occurrence Analysis of COVID-19 Publications with an Emphasis on the Global Health Governance (GHG)

Background

Analyzing co-occurrence is an effective way to monitor the overview of topic spreading. The present study aimed to conduct a co-occurrence analysis of scientific publications related to COVID-19, emphasizing Global Health Governance (GHG).

Materials and Methods

This applied research with an analytical approach was carried out on all the scientific publications related to COVID-19, emphasizing GHG (51056 records), extracted from PubMed Central on 26/01/2022. The research population consisted of all the scientific publications related to COVID-19, emphasizing GHG (51056 records), extracted from PubMed Central on 26/01/2022. The data were analyzed using BibExcel, UCINET, Excel, and SPSS software, and Spearman's test was used to confirm correlations.

Results

The co-word network of the thematic area of COVID-19 includes 226 nodes and 7292 edges. COVID-19 and the pandemic formed the most co-word pairs with 2224 connections. The COVID-19* mental health and COVID-19* anxiety, with 1019 and 925 connections, are ranked next, respectively. The term COVID-19 is ranked first with a centrality index of 225. The keywords of pandemic and public health are ranked second and third with the centrality index of 217 and 206, respectively.

Conclusion

The global approach of studies related to COVID-19 is more inclined to the epidemiological and public health fields. Assuming the GHG, detailed and comprehensive planning should be performed to strengthen these studies and pave the way for international cooperation, determining research requisites, and developing applied research studies.

Citation advantage of COVID-19-related publications

With the global spread of the COVID-19 pandemic, scientists from various disciplines responded quickly to this historical public health emergency. The sudden boom of COVID-19-related papers in a short period of time may bring unexpected influence to some commonly used bibliometric indicators. By a large-scale investigation using Science Citation Index Expanded and Social Sciences Citation Index, this brief communication confirms the citation advantage of COVID-19-related papers empirically through the lens of Essential Science Indicators’ highly cited paper. More than 8% of COVID-19-related papers published during 2020 and 2021 were selected as Essential Science Indicators highly cited papers, which was much higher than the set global benchmark value of 1%. The citation advantage of COVID-19-related papers for different Web of Science categories/countries/journal impact factor quartiles was also demonstrated. The distortions of COVID-19-related papers’ citation advantage to some bibliometric indicators such as journal impact factor were discussed at the end of this brief communication.

Symmetry in Scientific Collaboration Networks: A Study Using Temporal Graph Data Science and Scientometrics

This article proposes a novel approach that leverages graph theory, machine learning, and graph embedding to evaluate research groups comprehensively. Assessing the performance and impact of research groups is crucial for funding agencies and research institutions, but many traditional methods often fail to capture the complex relationships between the evaluated elements. In this sense, our methodology transforms publication data into graph structures, allowing the visualization and quantification of relationships between researchers, publications, and institutions. By incorporating symmetry properties, we offer a more in-depth evaluation of research groups cohesiveness and structure over time. This temporal evaluation methodology bridges the gap between unstructured scientometrics networks and the evaluation process, making it a valuable tool for decision-making procedures. A case study is defined to demonstrate the potential to provide valuable insights into the dynamics and limitations of research groups, which ultimately reinforces the feasibility of the proposed approach when supporting decision making for funding agencies and research institutions.

A scientometric approach to psychological research during the COVID-19 pandemic

During the COVID-19 pandemic, modern science demonstrated its ability to respond well to the health crisis by publishing useful and reliable information. This disease has also led to an increase in psychological publications in this field. However, most scientometric studies have focused on medical aspects, and social science research has been neglected. Therefore, to fill this research gap, we analyzed the research on COVID-19 in the field of psychology to provide an insight into the perspective, research fields, and international collaborations. Data were collected from the Web of Science database and analyzed using Citespace and Bibliometrix (Biblioshiny). The overall performance of the documents was described, and then keyword co-occurrence and co-authorship networks were visualized. Fifteen main clusters were formed by drawing document co-citation network. The result indicates that Anxiety, mental health, delirium, loneliness, and suicide were important topics for researchers. Considering the special conditions that COVID-19 created for human societies, perhaps one of the most important subjects in the field of health is psychological studies. Using the results of this study, psychology researchers can identify their potential colleagues and research gaps in the subject of Covid-19.

Mapping the global research landscape on nutrition and the gut microbiota: Visualization and bibliometric analysis

BACKGROUND

Nutrition is a significant modifiable element that influences the composition of the gastrointestinal microbiota, implying the possibility of therapeutic diet methods that manipulate the composition and diversity of the microbial.

AIM

To overview research papers on nutrition and gut microbiota and determines the hotspots in this field at the global level.

METHODS

Scopus and Reference Citation Analysis were used to construct a bibliometric technique. It was decided to create bibliometric indicators and mapping as in most previous studies. 2012 through 2021 served as the study's timeframe.

RESULTS

A total of 5378 documents from the Scopus database were selected for analysis. Of all retrieved studies, 78.52% were research papers (n = 4223), followed by reviews (n = 820; 15.25%). China ranked first with a total number of articles of 1634 (30.38%), followed by the United States in second place with a total number of articles of 1307 (24.3%). In the last decade, emerging hotspots for gut microbiota and nutrition research included "gut microbiota metabolism and interaction with dietary components", "connection between the gut microbiota and weight gain", and "the influence of high-fat diet and gut microbiota on metabolic disorders".

CONCLUSION

This is the first thorough bibliometric analysis of nutrition and gut microbiota publications conducted on a global level. Investigation of the association between nutrition/diet and the gut microbiota is still in its infancy and will be expanded in the future. However, according to recent trends, the “effect of gut microbiota and high-fat diet on metabolic disorders" will be an increasing concern in the future.