Background: Scientometrics studies are one of the most efficient methods of quantitative evaluation of the scientific outputs of valuable information and citation databases for understanding and observing the status of scientific publications in different subject areas. The main aim of this article was to study the 50 years of Coronavirus scientific publications in the world. Materials & Methods: This applied research was carried out using scientometrics methods and an analytical approach. The statistical population of this article includes 5128 Coronavirus subject area documents indexed on the WoS from 1970 to 2019. The keywords were extracted from MeSH and analyzed using Excel 2016. Results: Data analysis showed that the highest science production was in 2005, and the highest citation number was in 2019. "Enjuanes L." is the most proliferated author, the United States, the most productive country, and the University of Hong Kong, the top organization in Coronavirus in the last half-century. Conclusion: The results showed, there is a direct relationship between the Coronavirus outbreaks and the amount of Scientific Publications in this area in the World. The quality of the researchers' productions in this area can be deliberated by scientific methods and researchers' self-citation has affected their h-index. For health care researchers, policymakers, and planners, it is necessary to be aware of the results of scientific studies of strategic and vital research areas, such as Coronavirus, to identify more appropriate therapeutic goals, make better decisions, and provide more effective solutions in the shortest time.

PurposeSynergy indicators and social network analysis (SNA), as practical tools, provide the possibility of explaining the pattern of scientific collaboration and visualization of network relations. Recognition of scientific capacities is the basis of synergy. The present study aims to measure and discover the synergistic networks of COVID-19’s top papers at the level of co-authorship, countries, journals, bibliographic couples and titles.Design/methodology/approachThe synergy indicator, co-authorship co-citation network analysis methods were applied. The research population comprises COVID-19’s top papers indexed in Essential Science Indicator and Web of Science Core Collection 2020 and 2021. Excel 2016, UCINET 6.528.0.0 2017, NetDraw, Ravar Matrix, VOSviewer version 1.6.14 and Python 3.9.5 were applied to analyze the data and visualize the networks.FindingsThe findings indicate that considering the three possible possibilities for authors, countries and journals, more redundancy and information are created and potential for further cooperation is observed. The synergy of scientific collaboration has revealed that “Wang, Y,” “USA” and “Science of the Total Environment” have the most effective capabilities and results. “Guan (2020b)” and “Zhou (2020)” are bibliographic couplings that have received the most citations. The keywords “CORONAVIRUS DISEASE 2019 (COVID-19)” were the most frequent in article titles.Originality/valueIn a circumstance that the world is suffering from a COVID-19 pandemic and all scientists are conducting various researches to discover vaccines, medicines and new treatment methods, scientometric studies, and analysis of social networks of COVID-19 publications to be able to specify the synergy rate and the scientific collaboration networks, are not only innovative and original but also of great importance and priority; SNA tools along with the synergy indicator is capable of visualizing the complicated and multifaceted pattern of scientific collaboration in COVID-19. As a result, analyses can help identify existing capacities and define a new space for using COVID-19 researchers’ capabilities.

Background: Acinetobacter baumannii is one of the most common challenging pathogens in causing serious infections in intensive care units of modern hospital systems around the world and poses a serious threat to public and patient health. This study aims to analyze the network of scientific and empirical collaborations of A. baumannii researchers in the last three decades.Materials & Methods: The present study was performed using the Co-citation analysis technique. All A. baumannii publications indexed in the Web of Science Core Collection for the period 1990-2019 are the statistical population of the study. After an advanced search, 4473 documents were retrieved. A total of 18343 authors contributed to the publication of the retrieved documents. Ravar PreMap 1.0.0.0, NetDraw, and UCINET 6.528.0.0 software were utilized for data analysis.Results: Data analysis showed that the global publication of A. baumannii has risen. "Clinical Infectious Diseases," was the best journal, and "Seifert, Harald," the most influential researcher, and "Seifert, Harald * Higgins, Paul G," were identified as the best co-citation pair. Top researchers in A. baumannii were "Beceiro," "Alejandro," "HSU Li Yang," and "Seifert, Harald," respectively, based on degree, betweenness and closeness centrality indicators. Conclusion:Analysis of social networks A. baumannii presents an objective and realistic view to experts and planners in Medical Sciences. Also, the structure of A. baumannii's internal relationships and researchers' connections is determined objectively. Finally, researchers get acquainted with journals, scientists and organizations that are proliferated and effective and plan to collaborate with them in the future

10.30699/jambs.28.130.253 Background & Objective: The present study aimed at exploring the structure of global knowledge, hidden patterns, and emerging Coronavirus events using co-word techniques. Co-word analysis is one of the most efficient scientific methods to analyze the structure and dynamics of knowledge and the general state of research. Materials & Methods: This applied research performed using Co-word analysis. The statistical population is 4102 keywords from Web of Science Core Collection indexed documents on Coronavirus retrieved through advanced search (1970-2019). To identify the keywords used to design a search strategy, the Medical Subject Heading browser was utilized. After the keyword editing process, the threshold identified, and UCINET, VOSviewe, and SPSS 16 were used to analyze the data. Results: The highest frequent keyword was "Severe Acute Respiratory Syndrome (SARS)" with a frequency of 276. Nineteen subject clusters were the result of a hierarchical clustering analysis by the Wards' method. Clusters 4 and 15 were the biggest ones with nine keywords. Strategic diagram analysis showed that the most prominent Coronavirus clusters' most prominent clusters are in Quadrant III of the strategic diagram. Conclusion: The results showed that Coronavirus research's intellectual structure in the form of 19-topic thematic clusters and determining the degree of cluster cohesion makes it possible to discover complex conceptual relationships of valid international Coronavirus research. The results of this paper could also be used to guide medical researchers, especially coronavirus scientists. Medical policymakers can also more effectively present strategic plans by becoming aware of the global knowledge structure, hidden patterns, and emerging international coronavirus events.

The objective of this study was to analyze the top papers from Organization of Islamic Cooperation (OIC) member countries covered in the Essential Science Indicators (ESI) database during 2010-2019. The findings of the study showed that 41 out of 57 OIC member states have published 7,369 highly cited papers and 249 hot papers. The leading countries based on the overall top papers produced were Saudi Arabia, followed by Iran, Turkey, Malaysia, Pakistan and Egypt. Iran was ranked first in terms of hot papers. When analysed by document type, all of the top papers were articles and published in the English language. The Lancet ranks among the top in terms of publishing OIC member countries’ top papers, showing that it has a great academic influence producing highly cited papers and hot papers. The top five organizations producing top papers are all top universities in their country and they are also ranked globally. King Abdulaziz University contributed the most for both highly cited papers and hot papers. NANOFLUID was the most common keyword and core subject in highly cited papers, and the keyword MECHANICAL-PROPERTIES was the core subject identified in hot papers. Cluster 1 is the largest subject cluster of highly cited papers with the topic Nanotechnology and it is also the largest cluster of hot papers.