Background and aim: The aim of this research is to determine the social factors affecting the level of scientific production in the field of social sciences in the Middle East using panel data analysis. This study attempts to analyze the role of variables such as women's education, equal educational opportunities, social justice, access to digital governance, population, and life expectancy in enhancing scientific production. Materials and methods: This is a quantitative and applied research that uses library and documentary methods to collect the required data from reputable international sources. The statistical population includes 12 selected Middle East countries with full access to data between 2011 and 2021. Data related to social variables were extracted from the Social Progress Index and the World Bank, and scientific production data were extracted from the Scimago database. The panel data econometric method was used to analyze the data with statistical tests such as Hadri unit root, F-limer test, Hausman, and LR variance heterogeneity, and the final model was estimated using EViews 12 software based on fixed effects model. Findings: The research findings showed that increasing the number of women with higher education has a positive and significant impact on scientific production. Furthermore, equal educational opportunities, social justice, access to digital governance, population growth, and life expectancy were also identified as effective and significant variables in increasing scientific production. Among them, women's higher education played the most significant role with the highest impact coefficient (7.554). Conclusion: The results of the present study showed that various social and structural factors have a significant impact on the level of scientific production in the studied countries. In particular, the increase in scientific participation of women with higher education and equal educational opportunities have been significantly associated with the growth of scientific production.
Background and aim: This study examines the applications and challenges of artificial intelligence, particularly language models like ChatGPT, in various scientific and educational fields. The primary aim of this research is to analyze the positive and negative impacts of this technology on teaching and learning processes and to identify the challenges associated with its use. Materials and methods: This study is based on the data collected from studies conducted between 2021 and 2024. To gather data, the researchers reviewed scientific articles, conferences, and research reports published in reputable databases. The data includes research papers, systematic reviews, and meta-analyses in the field of artificial intelligence and its applications in education and learning. For data analysis, bibliometric methods and the VOSviewer software were utilized. Findings: The results indicate that artificial intelligence, as a powerful tool, has significant capabilities in facilitating learning processes and providing diverse responses. However, this technology also faces serious limitations and challenges. The performance of ChatGPT in question-answer tests and algebra learning is significantly lower than human scores, indicating a need for further improvements in this area. Additionally, in subjects such as physics and medicine, these models encounter challenges in connecting concepts and understanding new knowledge. Other challenges, such as high energy consumption, risks from malicious misuse, bias and discrimination, as well as concerns regarding privacy and data security, are also addressed in this research. This study emphasizes the necessity of developing ethical standards and regulations that will help maintain the credibility and effectiveness of artificial intelligence technologies. Conclusion: Although artificial intelligence offers numerous opportunities in education, realizing its full potential requires investment in research and development, technological improvements, and attention to its ethical and social dimensions.
Background and aim: This study was conducted to analyze the scientometrics of agricultural land use changes between 2000 and 2024 and aims to identify the main drivers of these changes. Materials and methods: To draw the scientific map, a total of 1801 publications from the Scopus database, covering the years 2006 to 2024, were analyzed using bibliometric techniques, including co-authorship networks, keyword co-occurrence mapping, citation impact analysis, and trend evaluation. Statistical analyses were conducted using VOSviewer, and correlation testing and exploratory factor analysis were performed using IBM SPSS version 28. Findings: The results of the study showed that attention to the field of agricultural land use change has increased sharply in recent years, especially since 2015, and countries such as China and the United States have the most published articles in this field. Keyword network analysis identified key terms related to agricultural land use change, including environmental factors, human impacts, and technological methodologies. Based on the results of the correlation test, a positive and significant relationship was observed between the number of published articles and the year of publication at one percent level (P<0.01). Factor analysis identified five critical drivers—economic, social, environmental, spatial, and legal—impacting agricultural land use changes, with economic and environmental factors exerting the most influence. Conclusion: Economic, social, legal, environmental, and physical drivers influence land use change, and the role of economic and environmental drivers is particularly prominent. Research has moved toward advanced techniques such as remote sensing and artificial intelligence algorithms that can help policymakers identify and predict land use change patterns.
Background and aim: Scientific journals play a crucial role in the dissemination of scientific and technical information. Given the key role of the Iranian Journal of Medical Ethics and History of Medicine as a specialized publication in the field of history of medicine in Iran, and the lack of a comprehensive study analyzing its content, this research aims to examine articles in the field of history of medicine in this journal. Materials and methods: This research was conducted based on survey method and content analysis (quantitative approach). The statistical population of this study includes all indexed articles in the Iranian Journal of Medical Ethics and History of Medicine in the field of the history of medicine between 2008 and 2022. Findings: The research findings indicate that out of 751 published articles, 134 were related to the history of medicine, authored by 307 writers. Tehran University of Medical Sciences, Isfahan University, and Tabriz University of Medical Sciences were the most productive academic centers. In terms of article type, review articles (61.94%), research articles (29.85%), and viewpoints (4.47%) had the highest representation, respectively. The most frequently recurring keywords were 'medical ethics, medicine, traditional medicine, Islam, and history of medicine'. A review of the thematic orientation of the articles showed that the largest number of articles were related to the topics of "medical ethics", "medicine in religions", and "biographies of doctors and scientists". Conclusion: Considering the aim of the present study, the results showed that this journal plays a significant role in the publication and promotion of research in this field. However, in order to improve the quality of medical history research, more attention should be paid to thematic diversity and the strengthening of international collaborations.
Background and aim: Given the fundamental role of public law in regulating the relationship between the state and citizens and safeguarding fundamental rights, examining the intellectual structure and scientific trends in this field is essential for the advancement of governance and policymaking. This study aims to map the intellectual structure of scientific outputs in the field of public law in the Web of Science database, illustrating the scientific growth trends, author collaboration networks, keywords, and the thematic structure of the field. Materials and methods: This descriptive-applied research adopts a scientometric approach. Data were collected from articles related to public law indexed in the Web of Science database between 1985 and 2024. The inclusion criteria comprised publication within this period, relevance to public law, and being in the format of research article or systematic review. Findings: Keyword co-occurrence analysis in the thematic domain of public law, considering a threshold of one, identified six clusters containing 150 keywords. The terms “public law”, “law”, “public-law litigation”, and “rights” had the highest frequencies in studies related to this field. These findings highlight the importance of keywords and the thematic research structure in public law, indicating a focus on related key concepts. Conclusion: The thematic analysis of keywords extracted from science mapping revealed that public law, rights, and litigation are the main points of interest in the scientific outputs of this domain.
Background and aim: Artificial intelligence has been used since 1950 in the areas of personalized health services and analyzing patient data, such as medical history and lifestyle factors. The aim of the present study is to model the thematic content of scientific products in the field of artificial intelligence in the healthcare sector based on data from the PubMed database. Materials and methods: This study is descriptive-exploratory in nature. The statistical population includes all scientific publications (16,011 articles) related to artificial intelligence in medical treatment, indexed in the PubMed biomedical literature database from the beginning to the end of 2023. For modeling and analysis, abstracts and titles are used by combining LDA and TF-IDF algorithms. Findings: The clustering findings led to the formation of eight thematic clusters: “Robotic-Assisted Laparoscopy”, “Deep Learning Models for Disease Prediction”, “Robotic Surgery”, “Clinical Applications of Artificial Intelligence”, “Robotic Rehabilitation”, “Medical Imaging with Deep Learning”, “Robotic Radical Prostatectomy”, and “Social Robotics”. This diversity indicates the wide-ranging scope of research within AI applications in medical treatment. Heat map analysis revealed a strong correlation (0.91) between the clusters “Robotic-Assisted Laparoscopy” and “Disease Prediction Models”, highlighting the interdisciplinary nature of this field. The most frequently weighted keywords in the literature were “robotics”, “surgery”, “patients”, “model”, and “prostatectomy”. Conclusion: The “robotics” is the most important keyword in the field of artificial intelligence and treatment. The results also show that the extracted clusters not only have thematic coherence, but also a logical and meaningful connection is seen between them.
Background and aim: Sports media are considered as one of the most important factors in the formation of social values. The main objective of the present study is to evaluate and draw a knowledge map of scientific products in the field of sports media in the Web of Science database during the years 2016-2023. Materials and methods: The present study is quantitative in terms of approach, applied in terms of objective, and descriptive-analytical in terms of data collection. The statistical population includes the scientific products in the field of sports media in the Web of Science database during the years 2016-2023. This study was conducted using scientometric method. VOSviewer was used to draw scientific maps, and Excel and SPSS were used to analyze data. Kolmogorov-Smirnov test was used to determine whether the data were normal or not, and the Spearman correlation coefficient test was used to answer the research hypotheses. Findings: Evaluations show that the map of scientific collaboration of authors of sports media articles is not coherent and is scattered in different clusters and colors, which indicates that the authors of each cluster probably collaborated in a subject area and the subject field of each cluster is different from other clusters. There is also a significant relationship between the number of documents and the number of citations of universities/organizations participating in the production of documents in the field of sports media in the Web of Science database (r=0.771, p<0.001). Conclusion: There is a significant relationship between the number of documents and the number of citations of authors in the field of sports media.
Background and aim: Information-seeking behavior refers to a set of activities individuals perform to meet their information needs. The need for information serves as the fundamental pillar of information-seeking behavior. This research aims to investigate the information-seeking behavior of medical assistants at Tabriz University of Medical Sciences during the COVID-19 pandemic. Materials and methods: This descriptive-survey study was conducted from November to January 2022. The statistical population consisted of 600 medical assistants from Tabriz University of Medical Sciences, and a sample size of 234 assistants was determined using the Krejcie & Morgan table. Data were collected using a questionnaire designed based on studies by Huang et al. and Nelson and Tugwell. SPSS version 21 was used to analyze the data. Findings: The results revealed that assistants had the greatest informational needs regarding "virus prevention methods," "recognizing symptoms of infection," and "susceptible populations," with average scores of 4.12, 3.70, and 3.65, respectively. These needs differed significantly between men and women and among various age groups. The primary motivations for searching for information were "personal protection," "finding information for family and friends," and "obtaining the latest information," with average scores of 4.12, 3.99, and 3.81, respectively. Additionally, a significant relationship was observed between gender and the need for virus-related information. Conclusion: The study results indicated that during the COVID-19 pandemic, medical assistants at Tabriz University of Medical Sciences had a critical need for reliable and up-to-date information regarding the prevention and treatment of the COVID-19 virus. Their demand for practical information to safeguard themselves and their families along with concerns about the economic impacts of the pandemic reflect a complex and multidimensional pattern of information-seeking behavior during a crisis.
Background and aim: Payame Noor University of Iran plays an important role in the production of Iranian science in various scientific fields by taking advantage of the existing capacities and conducting various studies. Therefore, the present study deals with scientific productions related to the medical sciences of Payame Noor University. Materials and methods: This descriptive study was conducted with a bibliometric approach. The statistical population of the study included all the scientific documents produced by Payame Noor University in the PubMed medical database until March 27, 2024. To analyze the data and draw scientific maps, the bibliometrics package was used in the R programming language. Findings: A total of 1,947 relevant papers published since 2001 were retrieved. The words "Humans", "Animals", and "Female" are the most important keywords in scientific productions related to medical sciences at Payam Noor University. Chemistry, biology and biochemistry departments of Payam Noor University had the highest number of scientific productions. With 60 articles, betweenness centrality 45.22, closeness centrality 0.0057 and page rank 0.0488, Vesali has been the most prolific author in this field. Statistical analysis has shown that there is a weak correlation between the number of articles and betweenness centrality (p=0.195). Also, there was no significant correlation between the number of articles and closeness centrality (p=0.050). However, there is a significant correlation between the number of articles and page rank (p=0.472). The subject areas of the scientific productions of this university are classified into two main subjects of biomedical studies and studies related to the fields of chemistry and associated factors. Conclusion: Focusing on the fields of chemistry, biology, and biochemistry, Payame Noor University has had the most scientific productions related to medical sciences. Furthermore, the topics of detection limit, spectroscopy, Fourier transform infrared spectroscopy, and hydrogen ion concentration are among the leading topics in the scientific productions of medical sciences at Payam Noor University.
Background and aim: Given the increasing number of studies on Drought Vulnerability Assessment (DVA), conducting a comprehensive scientometric analysis of scientific results in this field can aid in understanding the current status, trends, and impacts of research. Materials and methods: To create a scientific map of this domain, a total of 1,131 articles from the Scopus database, published from 1990 to 2023, were collected. Scientometric techniques, such as co-authorship networks and co-occurrence networks of keywords, were employed for data analysis. Key indicators, including h-index, citation counts, and journal impact factors, were calculated to assess the visibility and influence of studies. Statistical analyses were performed using R software and VOSviewer. Findings: Results indicated that the growth rate of publications in DVA is approximately 16.5%, with notable increases in both the quality and citation rates of articles over the years. The scientific mapping analysis identified a six-cluster pattern, with the keyword "adaptation and vulnerability management" being the most frequently mentioned. The thematic evolution of studies also showed that in recent years, attention to adaptation issues in drought vulnerability assessment has increased, and a significant relationship was observed between the number of documents and citations (r=0.89) and between the number of authors and citations (r=0.17). Conclusion: Global attention to DVA has significantly risen in recent years, with countries such as the United States, China, and Australia leading the efforts. Furthermore, adaptation management has emerged as the most important research area, while emerging methods and techniques in vulnerability assessment are expected to lead to greater diversity and consensus in this field.
Background and aim: Considering the increasing demand and costs of health care, it is necessary to know the practical aspects of digital health as a new field in service provision and doctor-patient interaction. The aim of the present study was to analyze the applications of digital health in Iran with a scientometric approach. Materials and methods: The current study is an applied research in terms of objectives, descriptive in terms of data collection method, and was carried out with an scientometric approach. All publications in the field of digital health in PubMed, Web of Science, Scopus and IEEE Xplore databases were retrieved by searching and extracting words according to medical subject headings and authoritative texts within target years. The VOSviewer and HistCite softwares were used to draw the word co-occurrence map. Findings: The results of this study showed that the annual increase in digital health studies has occurred from 2012 to 2022. The highest frequency of vocabulary was observed in machine learning (33 cases), and mobile health (24 cases), and the lowest was observed in gamification and robotics (2 cases). In addition, the scientific map showed that out of 198 nodes, the four main clusters in the field of digital health in Iran, including deep learning, mobile-based programs, humans, virtual reality and artificial intelligence, have been considered more, and in areas such as COVID-19, pregnancy and other subcategories, mobile phone-based programs have been developed. Conclusion: Analysis of the applications of digital health in Iran showed that although some topics such as deep learning and virtual reality have emerged, providing appropriate infrastructure, training different groups of users, and making a favorable transformation in the field of health and treatment are highly significant, which should be taken into account by managers and policymakers.
Background and aim: Explanation, as one of the most basic goals of science, is an important part of every scientific article that seeks to find the basic causes of any phenomenon or fact, and reports the relationship between various aspects of that phenomenon or fact, and helps readers to gain a deeper and more scholarly understanding about the topic. In spite of this, the introduction of its nature and functions has not been sufficiently considered. Therefore, the present study was conducted to identify and introduce the criteria and indicators for measuring the quality of explanation in medical science articles through a systematic review of scientific documents. Materials and methods: The data were collected through a systematic search in Iranian databases, including IranDoc, Scientific Information Database (SID), and Civilica, as well as international databases such as PubMed, ProQuest, Scopus, Web of Science, and Google Scholar search engine. During this process, 52 articles published between 2020 and 2024 were retrieved, and 13 documents were selected for study and analysis using the PRISMA checklist. Data analysis was performed using Altheide's method. Findings: The research identified 14 basic indicators and categorized them in the form of three criteria for measuring the quality of explanation: "pivotal relationship" with two indicators of causality and reason exploration; "evidence-oriented" with four indicators of validity and correctness of evidence, access to evidence, efficiency of evidence and adequacy in quantity and quality, and "theory-oriented" with eight indicators of testability, reproducibility, simplification and being economical, experimental adaptability, theoretical adaptability, adaptability and conformity, comprehensiveness, and predictability. Among the criteria identified, the theory-oriented criterion had the highest number of indicators among the criteria mentioned in the review articles. Conclusion: By using the identified criteria and indicators, researchers can improve the quality of their scientific explanations and significantly increase the impact of research results.
Background and aim: Open Government Data is essential for today's civil society. The aim of this article is scientometric analysis of political documents based on open government data in Overton database. Materials and methods: This applied research was conducted based on scientometric indices and content analysis. Data from 2007 to 2023 were extracted from the Overton database. The research community includes 2493 documents related to open government data. The data were analyzed using Chi-square, Spearman's correlation coefficient, and Mann–Whitney U tests. Data analysis was conducted using SPSS Statistics 24. Findings: The Organization for Economic Cooperation and Development (OECD), with 514 citations, and the Guardian News Agency, with 291 citations, stand out as the most effective organizations and news agencies in the present research. Furthermore, a notable positive correlation exists between GDP and the quantity of government documents concerning open government data at the national level. Additionally, a significant positive yet weak correlation exists between SJR and the number of citations obtained from government documents. Conclusion: In recent years, there has been a significant increase in government publications on open government data. This is in line with the global open government paradigm. The results showed that human activities, economy, technology, innovation, and governance have had the most significant impact on issues related to government documents published as open government data.
Background and aim: The internet has provided marketers with a new path for greater creativity, resulting in increased transparency in marketing. The expansion of digital media platforms and the commercial use of the internet have transformed the business landscape. The present study aims to conduct a scientometric analysis of scholarly publications in the field of digital marketing from Web of Science database. Materials and methods: The present study is a descriptive-analytical and applied research conducted using a scientometric approach. The study population includes studies conducted in the field of digital marketing in the Web of Science database (1980-2024). Excel and RStudio software were used to analyze data and draw scientific maps. Findings: The content analysis roadmap of studies on digital marketing reveals the following: In the first quartile, the topics "Digital Marketing, Social Media, and COVID-19" and "Social Media Marketing, Consumer Behavior, and Credit" show the highest levels of development and relevance. The second quartile includes "Social Media", indicating subjects exclusive to this domain. Additionally, the cluster "Marketing and E-commerce" overlaps with the fourth quartile. In the third quartile, the cluster "Artificial Intelligence and Machine Learning" is found, exhibiting the lowest levels of development and relevance, thus considered underdeveloped and immature. Moreover, the cluster "Tourism and Technology" shares commonalities with the fourth quartile. Finally, in the fourth quartile, the cluster "Online Marketing" represents fundamental topics in the field. Conclusion: The studies primarily focus on thematic areas such as social media, social networks, digital marketing, e-commerce, business intelligence, customer relationship management, machine learning, digital strategy, influencer marketing, social media engagement, interactive advertising, and communication networks.
Background and aim: Nowadays, secondary school libraries have many deficiencies and one of the solutions to this problem is the partnership of public libraries with schools. This study was conducted with aim of assessing feasibility of cooperation between Libraries, Museums and Documentation Center of Astan Quds Razavi and school libraries in meeting information needs of secondary schools for boys in Mashhad. Materials and methods: This study was applied in terms of purpose and survey in terms of type of data collection. Data collection tool included a researcher-made questionnaire. Reliability of questionnaire was evaluated using Cronbach's alpha. The alpha coefficient obtained was higher than 0.8. The statistical population includes employees who are engaged in the librarianship profession in central library of Astan Quds Razavi and 16 libraries affiliated with this organization in Mashhad. Sampling was carried out using a stratified random method and 194 people were selected as sample population. In descriptive statistics section, mean and standard deviation were used, and in inferential statistics section, Kolmogorov-Smirnov tests, one-sample t-test, and analysis of variance tests were used. Data obtained from questionnaire were analyzed using SPSS 16 statistical software with significance level of less than 0.05. Findings: From librarians' perspective, most important obstacles to cooperation between secondary school libraries and libraries of Astan Quds Razavi are lack of familiarity with how to use library and incompatibility of library collection with information needs of students with a mean of 3.13. Also, considering the mean value (3.13±0.38), it can be concluded that the organization's situation is a favorable position in terms of confronting barriers to participation. Conclusion: The organization's situation is in a favorable position in terms of prerequisites for cooperation, confronting barriers to cooperation, and responding to students' needs.
Background and aim: The main objective of the present study is to draw a scientific map of audiovisual sports media based on scientific articles indexed in the Web of Science database during the years 2016-2023. Materials and methods: The present research is an applied study which uses scientometric techniques and indicators. The statistical population of this study includes all articles published in the Web of Science database in the 8-year period from 2016 to 2023 in the field of audiovisual sports media. Independent t-test was used to determine significance or non-significance, and VOS viewer software was used to draw a map of co-authorship of organizations, a map of country density, as well as word cooccurrence. Findings: The results showed that from 2016 to 2023, the number of studies conducted in the field of audiovisual sports media has relatively increased. The largest share of articles published in the field of audiovisual sports media belongs to Lecture Notes in Computer Science, which has published 5 studies. Japan has the largest share of articles produced in the field of visual sports media compared to other countries by a large margin, with 238 articles and participation in 26 percent of the published articles. Words such as "classification", "audio", and "perception" were the most frequent in the field of visual sports media. Words such as "Sport" and "Social media" have the highest frequency and repetition in the titles and abstracts of published articles in the field of visual sports media. Conclusion: Given their educational and informative role, sports media can contribute to the development of sports in countries by raising awareness, providing information, training, and guidance.
Background and aim: In co-word analysis, it is assumed that the most frequent words have a greater impact on a subject area compared to the less frequent words. The purpose of the current research is co-word analysis of review articles on the subject of "cloud computing" indexed in the PubMed database in 2009-2022 time period. Materials and methods: The current research is applied in terms of nature which utilized co-word analysis to analyze the data. The statistical population included 169 review articles on the topic of "cloud computing" indexed in the PubMed database in 2009 to 2022 period. The total of 57 articles lacked keywords which were excluded from the study. The required data was retrieved from the mentioned database by entering the word "cloud computing" in the subject field which were subsequently added to the Excel software. Voyant Tools software was used for co-word analysis. Findings: Based on the maps obtained from co-word analysis, keywords fog computing, data computing, cloud database, Internet of Things, cloud data, cloud challenge, cloud technology, cloud systems, health systems and cloud overlapped the most with the term cloud computing. Drawing maps of co-word at different time periods under investigation illustrates changes and stability in the concepts and words related to the field of informatics. New concepts emerged as a recombination of existing words interacting with developments and new technologies. Conclusion: The most frequent word in cloud computing review articles in all the texts indexed in PubMed among the words cloud computing, data computing, cloud database, Internet of Things, cloud data, cloud challenge, cloud technology, cloud systems , has been health and cloud systems in which the terms "data computing" and "fog computing" overlaped the most with cloud computing.
Background and aim: Bibliographic analysis by describing the status of publications and identifying emerging issues plays an important role in research evaluation. The aim of the present research is to draw the scientific collaboration networks of researchers, organizations, and scientific centers and the co-occurrence of scientific terms in articles related to the local history of Azerbaijan in Iranian Scientific Journals from 2011 to 2021. Materials and methods: This descriptive-analytical research is of bibliometric type. The samples include 111 scientific articles about the local history of Azerbaijan from 2011 to 2021, published in the country's scientific publications. The drawing of the scientific collaboration network of researchers, organizations, and scientific centers, as well as co-occurrence network analysis of scientific terms were done using VOSviewer. Findings: The scientific centers of the Northwest had the most participation in publishing articles. There is a significant relationship between the scientific rank of researchers and their scientific participation (P-value=0.021). In terms of historical periods, the Qajar period and, in terms of subject matter, political history attracted the most attention from researchers. Moreover, the universities of Tabriz, Azerbaijan Shahid Madani, and the Institute for Humanities and Cultural Studies produced the most articles. The words "Azerbaijan" and "Tabriz" had the highest frequency of repetitions in the articles on the history of Azerbaijan. In terms of the co-occurrence of terms, the focus has been mostly on the Qajar period and especially the Nasrid period. Conclusion: The trend of publishing articles about the local history of Azerbaijan has quadrupled in the studied period. Despite this upward trend, some historical periods and important topics have not been given much attention due to the lack of resources and certain challenges. It seems that the reason why professors and researchers paid more attention to the subject, in addition to local tendencies, was a better understanding of regional issues.
Background and aim: Word co-occurrence is a method for studying the intellectual structure of knowledge in various subjects. Experts in science assessment studies use it to map the relationship between concepts and ideas in basic and social sciences. The main goal of the present research is to draw the intellectual structure of library and information science books based on book citation index. Materials and methods: The present study is an applied research based on word co-occurrence and social network analysis. The statistical population of this research includes 16499 books indexed in the field of librarianship and information in Web of Science. BibExcel, UCINET, and NetDraw were used in this study to homogenize and analyze the data. Findings: The most frequent co-word pairs were "ISO 9001-Quality Management Systems with a frequency of 12" and "Librarian-Web 2 with a frequency of 10." Cluster analysis showed six clusters of "scientific communication and digital publications," "library management and social participation," "information policy and technology management," "education and leadership in information services," "management and governance," and "digital network and development of the library and information science profession" in this study. Also, the keywords participation, library and information literacy had the highest degree centrality with 68, 55 and 47. The keywords research case, information and politics had the highest close centrality with 254, 253 and 252. Finally, the keywords participation, information literacy and library had the highest centrality index with 826/582, 518/835 and 512/802. The findings also indicate that about 16% of the books published in this subject area aligned with the fourth goal of sustainable development, quality education. Conclusion: The keywords "participation," "library," "information literacy," "university library," and "librarian" play a significant and decisive role in social network of librarianship and information books in drawing the map of science.
Background and aim: Engaging in research and familiarizing oneself with the research field are integral aspects of student development programs, particularly at postgraduate level. This study aims to analyze and map the co-authorship network within publications produced by the student research committee of Iran's Ministry of Health and Medical Education. Materials and methods: This is an applied research that utilizes scientometric techniques. The research community includes 2178 documents with the organizational affiliation of the Student Research Committee of Medical Sciences Universities of the Ministry of Health and Medical Education, which were retrieved from the Scopus database from 1985 to 2023. After data cleaning in Excel software and data homogenization, the data were transferred to BibExcel for frequency analysis. Subsequently, UCINET software was employed to calculate the correlation and centrality matrix. Furthermore, VosViewer software was used to visualize the data through network maps. Findings: An analysis of student research committee publications revealed 900 co-authored articles. Salari and Mohammadi exhibited the highest co-authorship frequency, with 10 publications. The findings showed that 38 countries participated in the scientific productions of the student research committee. America and England have cooperated the most with authors of student research committees with 58 and 14 scientific publications, respectively. Yousefi, Nouri, and Mohammadi emerged as the most prolific research committee authors. Sadeghi got the highest score in terms of centrality index and Karimi got the highest score in terms of closeness and intermediateness index. Furthermore, the five-author co-authorship pattern represented the most prevalent format (19.04%), with the single-author format accounting for less than 1% of publications. Conclusion: In studies by student research committee, the five-author co-authorship pattern has been the dominant pattern among the scientific documents of the student research committees, which indicates proper scientific cooperation among students.
