پژوهشنامه علم سنجی
پیاپی 17 (بهار و تابستان 1402)

Quantitative citation analysis fails to take into account different citation motivations which may be neutral, confirmative, or negational. It necessitates devising new methods or techniques to evaluate cited documents based on the attitudes of their citing articles, to increase the accuracy of the results of the quantitative approach. The challenge is believed to be partially answered by content analysis of citations, including citation opinion mining. It is based on extracting and analyzing the sentiment words occurring in citations, or citation contexts, i.e., a word window surrounding any given citation within a citing paper. However, there exist few pieces of evidence on the degree of divergence or convergence of the results of the quantitative and content-based approaches. To provide further research evidence, the present study investigated the correlation between the results of these two citation-analysis approaches.

Using a citation analysis method with the quantitative and opinion-mining approaches, this communication explored a sample consisting of 524 medical papers. Their bibliographic information and citations were extracted from PubMed and CoLil, respectively. 3663 citations were identified, of which 3639 contexts were available through CoLil. The citations were processed using the KNIME data mining platform. The opinion scores of the words were extracted from SentiWords. The citations opinions were measured in terms of the polarity and strength of the average opinion scores of their words. The data were then analyzed by Spearman Correlation.

The citations were revealed to carry numerous sentiment words. They were mostly positive in their polarity, however, the number of citations with negative polarity was also considerable. The citation counts were found to be directly and strongly correlated to the absolute count of the opinionated citations. However, they were revealed to be indirectly and weakly correlated to the relative count of opinionated citations, i.e., the number of opinionated citations normalized by the total count of the citations. Furthermore, the citation counts had an insignificant correlation with the relative frequency of positive citations, while displaying significant direct relationships with negative and neutral ones. Moreover, they were indirectly associated with the average opinion scores.

In general, the findings of this research showed that as the number of citations increases, the relative number of opinionated contexts decreases. They were dominated by a positive polarity which is in line with previous studies revealing a confirmative motivation in citation behavior. The predominance of positive opinions implied explicit and implicit confirmation motives of researchers reflected in the citing works: the citer may explicitly express her opinion about the cited article and its features, or implicitly express her approval by citing it (i.e., using algorithms, methods, tools, findings and etc.).According to the findings, as citation counts increase, the cited papers witness a reduction in their opinionated contexts’ relative numbers, while experiencing an increase in their negative and neutral ones. Consequently, the content-based citation analysis with an opinion-mining approach may be able to adjust the results of the quantitative approach. However, this finding and its generalizability should be treated with caution. Because the sample of the current research was not selected randomly. Given the differences between disciplines and scientific communities in their citation behavior, it is necessary to replicate the research in various contexts to support the results. Moreover, in the dictionary-based opinion mining method applied in the present study, the big challenge is precisely detecting negative opinions. As in negative citations, the negative opinions of citers may be mingled with their reports of negative objective findings. In other words, the method cannot precisely distinguish these two types of opinion contexts, i.e., the negative attitudes of the citers and their narration of negative findings. Moreover, citations are of social nature. Therefore, negative citations are mostly hidden and indirect, and their lexical identification is hence quite difficult. Thus, advanced methods using, for example, machine learning algorithms, are required to detect and analyze any possible implicit and indirect negative opinions which the direct natural language method may fail to capture.

Promulgating the new instructions on how to grant incentive base to faculty members (Appendix of Article 53 of the Employment Regulations of Faculty Members, approved by the Board of Trustees of the Ministry of Science, Research, and Technology (MSRT)) by the honorable Minister of MSRT and directly emphasizing the need to employ scientometric experts for its implementation was an excuse to dedicate this issue to a review of the position of scientometrics graduates in the field of higher education. In paragraph 10-38-7 of the new notification instruction that has been implemented since spring 2023, universities and higher education institutions are requested to "appoint at least one special expert (with mastery of scientometrics and Technometrics) working in the institution to implement this instruction. This is a valuable indication of the positive view of the country's scientific and executive circles of higher education towards the position of scientometrics and promises a more promising career future for the graduates of this field. Years ago, in the preface of the book "Introduction to Scientometrics: Foundations, Concepts, Relations and Origins" I declared the need for scientometric specialists to obtain the demands and evidence in the country's upstream documents such as the comprehensive scientific map of the country, I was aware of the fact that the use of scientometric experts as one of the most significant areas supporting science policy requires more serious support, and I had demanded a firmer determination for the training of scientometric experts; Because the increasing changes facing the higher education system, I did not doubt that the increasing demand in scientometric experts will be inevitable. In the same years and based on this fundamental need, the Ministry of Health, and Medical Education, as one of the pioneers in the use of scientometric experts in Iran, had correctly declared the establishment of scientometric units in all its universities and research centers, as well as the employment of scientometric experts in these units. After years of continuous efforts, this ministry profits from the countless advantages of science and technologyunits in line with its research and technology policies and planners, both at the Ministry's Research and Technology deputy level and in its affiliated universities and research centers level. In fact, applying the knowledge of scientometric professionals in various fields of higher education has become a necessity; and scientometric experts are an integral part of the higher education system, which previously I have mentioned some of these necessities in the editor-in-chief's Note, No. 6, entitled "Taking advantage of Scientometrics’ graduates in universities, a necessity to release from quasi=research"; and I have also noted some of these necessities in the editor -in -chief's Note, No. 9, entitled "A thought-provoking semi-perspective on the research, educational, and professional backgrounds of the scientometrics discipline at the universities of the world". Currently, despite the existing large volumes of upstream documents, laws, guidelines, and formal notifications that indirectly or even directly apply the scientometrics professionals to meet the needs of the higher education system, it is expected to be more decisive to employ and apply experts and specialists. In this regard, it is not unexpected that the State Administrative and Employment Organization will quickly coordinate, approve and communicate the requirements of MSRT, the Ministry of Health and Medical Education, and other relevant institutions to facilitate the recruitment of these experts. Along with it, universities and research centers also launch their scientometric units based on the new proclamation of the Minister of MSRT, relying on existing upstream approvals and documents. Upstream units such as the Department of Research and Technology, the Department of Education, and the Secretariat of the Board of Directors and Secretariat observe the implementation of the processes of the use of experts and professionals in universities. Certainly, it is only if the universities and higher education systems of the country will benefit more than ever before from the services and support of the experts and specialists to advance science and technology policy goals. On the other hand, as I mentioned in the editor-in-chief's Note, No 4, entitled "The Responsibility of the Scientometrics Graduates", it should not be overlooked that this kind of view of higher education system toward scientometrics from another approach must also be taken to the good; Because it doubles the responsibility of scientometrics graduates in strengthening its scientific and technological powers in order to respond more effectively to the needs of higher education. Currently, with the announcement of the new Employment Regulations of the faculty and its attachment to Article 53 by the Ministry, the opportunity to take advantage of the knowledge of experts and graduates of scientometrics has been provided for universities and research centers in the country, which should be utilized as best as possible. By smoothing the path of recruitment, hiring, and employing scholars and graduates, and also the launch of scientometrics units in universities and research institutes that have not yet done so, the higher education system benefits more than ever before the knowledge of these scholars. However, there will also be questions that should be addressed in this direction; such as: What are the mechanisms needed to guide the universities based in universities and research centers, as well as to observe their activities? What other mechanisms will be needed to enable the higher education system from the studies and activities of universities and research centers in the country? And what other steps should be taken to facilitate the use, recruitment, and employment of scholarship graduates in the country's higher education system and remove barriers in this regard?

This study aims to investigate the relationship between international scientific collaboration and highly-cited and hot papers of Iranian researchers in the Web of Science during 2010-2019. This research refers to the highly cited or hot articles in the Web of Science database.

The present study is an applied descriptive, including a scientometric approach. The research population includes 2747 highly-cited and hot papers of Iranian researchers indexed in Essential Scientific Indicators (ESI) and Web of Science (WoS) databases during 2010-2019.The research tool is an “advanced search” tool of the Web of Science database. For this purpose, first, articles related to Iran during 2010-2019 were extracted from the Web of Science database. By searching Iran, all the articles were retrieved. By limiting the search to highly cited articles and hot papers science scholars during  2010-2019 were extracted. Data was collected by Microsoft Excel software and analyzed by correlation and regression tests using SPSS (version 22) software.

The largest number of scientific collaborations included the United States (534), China (449), and the United Kingdom (338). Findings showed the most collaborations in highly cited and hot articles published in 2018 and 2019. Also, the most collaborations in writing highly cited articles in the subject areas were engineering with 374 (33710 citations), Physics with 155 (26158), and clinical medicine with 154 (60397 citations); Furthermore, the most cooperation in writing hot articles in the subject areas of engineering with 18 (983 citations), materials science with 14 (253 citations), and clinical medicine with  12 (1686 citations). Findings showed that the number of highly cited articles with the cooperation of two countries was 566 (50266), for three countries it was 274 (24351), for more than 15 countries it was 226 (86575), and the number of hot papers with the cooperation of two countries was 22 (713), for more than 15 Country it was 19 (1914), for three countries it was 12 (339). Findings showed that a positive and significant relationship was observed between the number of international collaborations and the number of citations received (without self-citation) of highly cited and hot papers. Whenever the coefficient becomes significant in the regression model, it means that in the regression model, the predictor variable has an effect on the dependent variable. If the value of P is less than a, the coefficient is significant. The regression model on the research variables with the presence of the predictor variable (the number of highly cited articles). In general, the number of collaborations is presented as the most suitable model that explains the variance of the criterion variable (number of citations) and the test is positive and significant. The findings show that the relationship between countries' researchers' cooperation and the number of citations received by highly cited articles is a strong, positive, and significant predictor.

Based on this, with the increase in cooperation, we see an increase in the number of cited articles by Iranian researchers. The results showed that there is a positive and significant relationship between the number of international collaborations of article researchers and the number of citations received. International scientific collaborations have increased the quality of research outputs (hot and highly cited papers) of Iranian researchers. According to the findings of the current research as well as the findings of the investigated backgrounds and confirmation of the impact of coauthorship and international scientific cooperation on increasing visibility and receiving citations, encouraging more international scientific cooperation, and allocating suitable funds and facilities. For this type of activities, the researchers of universities and research centers in Iran should be put on the agenda. With this action, the expansion of the research field of this research considering various aspects of international scientific cooperation in universities and research centers of the country can be considered.

In this research, it is tried to identify and present the basic capabilities and capacities of the University of Tabriz as one of the leading universities in the country in science and technology based on the intellectual, social and cognitive structure extracted from the scientific outputs of this university. This research In addition to being used in the effective management of research and technology at the University of Tabriz, can provide a model for other universities and higher education institutions in terms of methodology.

Regarding its nature, the current research is scientometric, and its approach is quantitative. The population of this research includes all the publications of researchers affiliated with the University of Tabriz (under various names such as University of Tabriz, Tabriz University, and Azarabadegan University) in the journals indexed in the Web of Science (Clarivate Analytics database) in the period from 1973 to the last days of 2016. The time of collecting information was 12/20/2016. Of course, to access some additional information, InCites database was also used. All the references and citations of works published by the researchers of the University of Tabriz are considered the population of this research. Considering the massive amount of references, citations, and bibliographic information in the articles, it was tried in all the networks created to identify the social, cognitive, and intellectual structure, 50 top nodes (author, journal, university, country, term, subject category, cited work, cited author, and the cited journal) are purposefully selected as samples. To further conceptualize the projected social, intellectual, and cognitive maps and structures, it was tried to examine the period from 1967 to 2016 in the form of 5 ten-year intervals to provide the possibility of comparing and separating them from each other.

 The findings of this research consisted of drawing, identifying, and analyzing the intellectual, social, and cognitive structure of the scientific outputs of Tabriz University to identify the human, intellectual and scientific capital of this university, to take action for the development based on internal capacities in line with investment based on competitive advantages. Studying the social structure of scientific outputs of this university showed that the structure can be shown with a network with a density of 0.009 and 60 working teams. The best-identified research teams are analytical chemistry, applied chemistry, electrical engineering, physics, and Polymers. Examining the influence of researchers in the creation and management of work teams shows that researchers such as Entezami, Hosseini, Daneshvar, Khanmohammadi, Khandar, and Khatai have been evaluated as the most influential in this regard. Examining the social structure based on partner universities also showed that the Institute of Theoretical Physics had the greatest influence on the researchers of the University of Tabriz. The investigations of this research showed that all the universities collaborating with the University of Tabriz in the production of joint works can be categorized in the form of 22 independent clusters. Also, examining the University of Tabriz's cognitive structure based on the scientific outputs of the university showed 19 identified scientific specialties and qualifications. The cognitive structure based on the keywords of researchers published in JCR indexed Journals is the representation of the top 150 keywords discovered among the keywords used by researchers and 163 links between them. Examining these words in terms of citation effect showed that keywords such as System, Model, Optimization, Behavior, Water, Design, Performance, and Iran are the most influential words.  Finally, the findings from the perspective of intellectual structure also showed that this structure can be shown based on a network with 61 independent specialties. The prominent specializations identified in this structure belong to fields such as Electromagnetism, Decolorization, and Thermodynamics, respectively. The intellectual structure obtained using this technique yielded a network that included the top 244 cited authors and 375 intellectual relationships between them. In general, based on this technique, in this research, 61 specializations into which the researchers of the University of Tabriz have entered were identified, introduced, and evaluated, and the most influential, central, and well-known author of each of these specializations was introduced, and the relative novelty of the works of the basic authors was presented. 

The University of Tabriz has potential competitive advantages in social and scientific terms that can make it a powerful and effective university. It seems that by looking at the university from this point of view, it is possible to identify effective working, intellectual, and social relationships in national, international, disciplinary, and interdisciplinary scientific communication, and take steps in the direction of effective research and technology policy-making and management.

University, industry, and government are well-known for their critical roles in business flourishing and other innovation-related processes for developing a knowledge-based economy. The synergy between these three units will facilitate innovation and knowledge development as well as maintain the dynamics of innovation. In this regard, the bilateral and trilateral relation between these units is a pertinent factors for developing innovation and a knowledge-based economy. Triple helix matrix (THM) is one the most endeavored method for studying these relations. In this model, university, industry, and government have other tasks different from their old-style tasks, e.g. universities will develop local innovation clusters with key roles in economic development. Also, research groups in universities will help develop a ‘firms network’ which is a critical factor for having entrepreneurial universities. Scientific production is an indicator of the growth and development of any country and is one of the indicators of scientometrics. The university is known as the center of knowledge production, and most of the scientific publications of a country are written by academics. The difference between a country like Iran and many developed and even developing countries is the distance between the level of cooperation of the three sectors of THM (university, industry, and government) in scientific publications.

In this research, we have focused on two technological universities in Iran (Malek Ashtar University of Technology and Amirkabir University of Technology) to compare the status of science production, and their interactions with industry and government. This research, as a case study of scientometrics based on ISI articles published by Malek Ashtar University of Technology and Amirkabir University of Technology, tries to examine and compare the interactions of these two universities with industry and government. Data were extracted from the WoS database in the period 2014-2019.

Based on the obtained results, Amirkabir University published more articles (total number of 12323 versus 1996), while the growth rate of publication for Malek Ashtar University of Technology was higher in the studied range (224% growth rate). The bilateral and trilateral relations showed dynamic interactions in the case of Amirkabir University. Besides, the university-government interaction was more profound (roughly four times) than the university-industry bilateral interaction. Amirkabir University also showed better trilateral relations (total number of 98) than Malek Ashtar University of Technology in the studied range.

Reasons for the better synergy of Amirkabir University are establishing growth centers, university-based knowledge-based companies, and the existence of a long-term plan. Also, The results of the present study showed that the level of scientific production in the two universities of Amirkabir and the Malek Ashtar University of Technology has increased. As can be seen, for five years, academics were responsible for the main production of scientific publications and confirmed that the university is the main institution for the production of science. When the center of research and production of science is in the university, there will be a large gap between the industrial needs of the country and scientific production, and the process of scientific production is linear and will not meet the problems and demands of society. Findings show that more efforts are needed to improve the interactions between the three sectors because more interaction between these sectors is one of the criteria for development. In this regard, it is suggested that universities turn from basic research to applied research needed by the industry to be able to meet industrial needs and play an active role in development. The role of policy-making in improving interactions is also critical, and the results of scientometric studies are useful in this area. The government, as a connector, must first gain the mutual trust of industry and university and then bring universities and industry closer together by making appropriate policies. Also, to draw a scientific map, the government can use scientometric studies in various fields of science; it helps make policy and identify strengths and weaknesses.

This study aims to analyze the retracted publications of Middle Eastern countries through citation analysis, lag-time between publication and retraction, and exploring the reasons for retraction.

Data was gathered by the document method and analyzing data was done by bibliometric analysis. Data were collected from the core collection of the Web of Science.

The research findings suggest an increasing trend in the number of retracted papers from Middle Eastern countries. Also, the results of Kendall's τ coefficient showed that the total number of publications is significantly related to the number of retracted papers. The results of the Kruskal-Wallis test showed a significant difference between the total number of citations and the four quartiles (i.e. Q1-Q4), and according to the average ranks, the journals of the first (Q1) and second (Q2) quartiles had received the highest number of total citations. Furthermore, the results of this test between quartiles and citations before and after retraction showed that there was a significant difference between different quartiles in citations after retraction, and the journals of the first (Q1) and second (Q2) quartiles received the most citations. In addition, there was a significant difference in the number of citations before retraction between different quartiles, and the highest average rank was related to the journals of the second quartile (Q2) and the first quartile (Q1), respectively. The highest number of retracted papers has been published in Bahrain. Based on the proportion of citations to each document, the highest proportion belonged to Israel. Also, the countries of Cyprus, Kuwait, Israel, and Iraq have the highest average time between publication and retraction, and Iran ranks ninth. In addition, it should be noted that the two countries of Oman and Jordan, which are ranked 14th and 15th respectively, each had only one retracted paper. In addition, the highest number of retracted papers and research misconduct was related to the field of biological sciences and biomedicine. The countries of Cyprus, Kuwait, and Israel had the longest time interval between publication and retraction. In all Middle Eastern countries, most papers were retracted due to research misconduct such as plagiarism and Redundant publication.

The results show that in the present era, it should be noted that citation is not a sufficient reason for the quality of the work while using previous studies, because many citations received by the works are not valid enough. Journal editors and database administrators should take measures to prevent authoritative citations to these works. Also, examining the status of retracted papers based on citations, the time interval between publication and retraction in different subject areas showed that the highest numbers of retracted papers were related to the field of biological sciences and biomedicine. Furthermore, the longest distance between publication and retraction, the largest number of citations, and the most citations received after retraction belonged to this field. It can be seen that there are three very effective factors in spreading the negative impact of retraction papers in the field of biological sciences and biomedicine. This result means that the required time for retraction in this area is longer than in other areas, and this can have damaging consequences. The longer the lifespan of flawed research, the higher the price the scientific community must pay. It is very important to carry out detailed judgments and demand raw data and files related to data analysis in a mandatory manner, especially on issues related to public health. Using retracted papers and citing them has many adverse effects. These effects are doubled when the citations are made after retraction and the citation is made in one of the medical fields. In this regard, arrangements should be made to properly inform others about the retraction status of paper in sensitive scientific fields such as the medical field. Correspondingly, all original versions of the paper that may have been published on the journal's website, the author's resume, or social networks will be completely removed.

The current research was conducted to investigate open-access articles written by Iranian researchers. This study examines the amount of scientific impact (citation indices) and social impact (altmetrics indices) of Iranian open-access scientific outputs. The results of this research can provide information about the effectiveness of open-access scientific publications to managers and policymakers in the field of science and technology so that, while being aware of the current situation, they can make the necessary decisions and policies to improve the quality of scientific outputs.

The present research is a descriptive study that has been conducted using scientometrics and altmetrics indicators. The research population comprised of 119168 scientific outputs published by Iranian researchers in open-access journals and indexed by the Web of Science. Data were collected using two products of Clarivate Analytics, namely Web of Science and InCites. Also, the Altmetrics Explorer, a service provided by Altmetric Institute was used for altmetric data collection. Finally, SPSS software was used to perform the correlation test, and because the values of the variables were not normal (the significance of the Kolmogorov-Smirnov test, p0.01), Spearman's correlation test was used (significance level 0.01). Other research data were analyzed using Excel software (descriptive statistics).

Open-access articles by Iranian researchers grew by 99.9% and the largest number of open-access articles by Iranian researchers have been published in journals with the gold open-access model. Islamic Azad University, Tehran University of Medical Sciences, and Shahid Beheshti University of Medical Sciences had the highest number of articles in open-access journals. Also, the largest number of articles by Iranian researchers have been published in medicine general internal journals (9342), chemistry multidisciplinary (6409), pharmacology pharmacy (5714), and mathematics (5235). The least number of open-access articles have been published in the subject areas of music (1), folklore (1), film, radio, and television (1).While the study of the received citations and the citation rate of the open access outputs of Iranian researchers indicated that the articles published in quality journals are of higher citation, about %40.05 of scientific output has been published in journals without quartile, %15.98 in Q4, %15.5in Q2, %14.34 in Q3, and % 14.11in Q1 journals.The findings showed that Iranian open-access scientific productions have been mentioned a total of 1,364,087 times in different media. The highest amount of attention and mention happened on Twitter (194,463), news (18,483), and Facebook (10,670). The results of correlation tests revealed statistically significant, positive, and poor relationships between the number of citations, altmetric score, mentions on Twitter, mentions on Facebook, and Mendeley readers.

Medical sciences universities of the country have contributed more to the publication of open-access scientific outputs, among the top 20 universities in the country in terms of the number of articles, the names of 10 medical sciences universities are visible. One of the reasons for this is the very important role of open access to medical articles and findings in increasing public awareness and health. With the publication of open access, the speed of access to the latest research and awareness of diseases will increase, and it will increase the level of health, and longevity in all countries of the world.On the other hand, the publication of a significant part of scientific outputs in Non-JCR indexed journals is very worth considering. Most of these journals are indexed in the Emerging Sources Citation Index. Gold open-access journals often receive very high fees for publishing articles, it is highly necessary to plan to inform researchers about the quality of these journals.

A book review is significant because besides being used by librarians in libraries and information centers to select books. It also helps readers and researchers inform about new books that its least advantage is saving time and careful selection. The effectiveness of new knowledge requires an application— generating knowledge alone and without using previous knowledge cannot achieve its objective, which is to increase awareness. The book review is a way to make the works known and provide proper awareness for society.Regarding the importance of book reviews and the applications of scientometrics in identifying the subject of research and considering that the initial studies of researchers show that there are few studies on analyzing book reviews on the WoS at the global level and specifically in Iran, this research was done to review and analyze “book reviews” indexed in the WoS databases, focusing on the activities of Iranian researchers, and through a comparative study of the situation in Iran with other countries in the world. 

The research adopted a descriptive-analytical survey method and a scientometrics approach. The population consists of all book reviews in 10 years (2010-2019) indexed in the Web of Science databases. To limit publications to book reviews, the book review option was selected. Based on this, 766,100 records were retrieved, which formed the current research population. To analyze the research data, Excel and VOSViewer were employed to draw the map to achieve coherent and clear networks.

The research showed that in the ten years from 2010 to 2019, book reviews covered approximately 3% of the total scientific production in the world and about 0.1% of Iranian documents. The results on Iran’s position in book review demonstrated the rank 47th in the world: in Iran, the book reviews growth rate is 0.07. The study of book reviews by subject in the world based on the 22 subjects of the ESI database showed that the interdisciplinary field is in the first rank, the field of psychiatry and psychology is in the second rank, and the social/general sciences are ranked the third. The findings showed that management, libraries, information retrieval, and librarians, which are part of the interdisciplinary fields, are hot and widely used topics. But in Iran, topics of gender, identity, evolution, capitalism, and ethics are the hot topics of book reviews. In the international arena and management, libraries, information retrieval, and librarians are the hot topics of a book review. This shows that the more specific issues of book review in the world and Iran have different directions and the trend in Iran is not in line with the global trend.

Book review publications have a lower growth rate than entire publications. Based on the subject map, the book review topics are different in the world and Iran. The collaborative coefficient of Iranian authors shows that co-authorship in book reviews is not favorable. According to the pattern of co-authorship of book reviews by Iranian researchers, the coefficient of participation of authors in these articles is 0.092, which shows that a person individually has mostly written book reviews in Iran and there is less the researchers’ willingness to participate.

The purpose of the present research is to investigate and identify semantic relationships, map the development of knowledge, and create a network of thematic documents produced in the field of moral education indexed in the Web of Science database between 2000 and 2018.

It is an applied-descriptive research method that was carried out using scientometric techniques and the method of vocabulary co-occurrence analysis and network analysis. The keywords of the articles were used as research data. It will be the statistical population of the research was collected from the Web of Science database and by using the keyword "moral education" in the advanced search strategy with the command code TI=moral education** NOT**TS=morality education**NOT TI=ethics education, which includes 991 articles. was that the word "moral education" is used in the title. The data was cleaned, normalized, standardized, and structured in the next step. To extract keywords from Bibexcel software, to edit data and draw a strategic diagram from Excel software, to create a matrix from Ravar PreMap software, to draw a tree diagram from SPSS 22 software, to calculate centrality, correlation matrix and draw a multi-dimensional scaling map from the software UCINet 6 and VOSviewer software was used to illustrate the maps.

This research has shown that out of a total of 1982 words identified during the study period in the field of moral education, 1213 words were used jointly or exclusively in the documents found. The keyword "university education" has the highest frequency with 55 repetitions. The words "education" and "values" had the highest co-occurrence with a frequency of 5. After these two words, "students' ideology", "education** moral development", "university education** moral development" and "university education** humanization" have the highest co-occurrences of 5, 4, 3, and 3 respectively. Are. The results of the cluster analysis showed that the field of moral education consists of 10 clusters: "Care and Justice", "Business Ethics", "School and Children's Maturity", "Behavior of Minors in Kindergarten", "Sex Education", and "Ethical Education". - Medicine", "Challenges of Physical Education", "Citizenship Education and Training", "Social Values" and "Human Virtues-Mythology" with the highest concentration related to cluster 2 "Business Ethics" and the highest concentration related to Cluster 5 "Education" It has been sexual. The drawing of the strategic diagram showed that cluster 5 "sex education" is located in dimension 1 due to its high density and internal connection, which are very well developed. Cluster 3 "school and children's maturity" and cluster 8 "citizenship education" are located in dimension 2 of the strategic diagram, they are not central, but they have the possibility of development. Also, cluster 1 "care and justice", cluster 2 "business ethics", cluster 4 "behavior of minors in kindergarten", cluster 6 "moral-medical education", cluster 7 "challenges of physical education" and cluster 9 "social values" Next, there are 3 strategic charts that are emerging.

In this research, the field of moral education was investigated using the methods of synonym analysis and social network analysis using articles indexed in the web-science database between 2000 and 2018. The results of the cluster analysis showed that the researches in the field of moral education in the desired period are from 10 clusters, which are "care and justice", "business ethics", "school and children's maturity", "behavior of minors in kindergarten", "Sex education", "Medical Ethics Education", "Challenges of Physical Education", "Citizenship Education", "Social Values" and "Human Characteristics-Mythology" were formed. Drawing the steering diagram based on the relationships between the words that make up the clusters revealed other hidden angles of it. In recent years, the field of moral education has focused on the topics that are applied in educational courses, but still, responsible organizations do not invest in this type of issue, which is consistent with past research. Therefore, the field of moral education emphasizes citizenship education in the education system for society to benefit from moral judgment and stability of human values and virtues. Therefore, based on the results of this research, experts in this field should pay attention to all the needs of the members of society and human society.

One of the requirements for organizations' human resources is the compilation of job competencies and professional skills for different ranks of employees. Job competencies are a set of provable characteristics and skills that enable and improve the efficiency or performance of a job. They are the examination of people's skills and abilities to make them hold different jobs and positions, and through its analysis, possible training needs of employees are also identified. Compilation of job competencies of various specialties is significant for organizations in the sense that the quality of employees' work is one of the factors for the continuity of the organization's success; Therefore, it is necessary to use a systematic way to select employees and identify and select the most suitable people for the desired position from domestic or foreign applicants. This study aims to identify the job competencies and skills required by scientometrics specialists to provide an effective performance in training, hiring, and evaluating specialists in this field, as well as reviewing the educational program and course title of scientometrics.

This research was conducted using qualitative and quantitative content analysis to identify categories and count the frequency of analysis units. Qualitative content analysis is a research method for the content interpretation of textual data through systematic classification, coding, and thematization or design of known patterns. The quantitative content analysis method was also used to count the analysis units (sentences). The research population consisted of 18 scientometrics specialists, including faculty members of knowledge and information science, managers, and experts of scientometrics units of the Ministry of Health, who were selected by purposeful sampling. The data collection tool was a semi-structured interview. The data were analyzed manually based on semantic units (sentences). In general, in the content analysis, the unit of analysis in this research was related sentences and concepts, which were analyzed and counted after careful examination. Then, in each sentence, the codes were determined manually and the main and subcategories were selected for each topic. The reliability of codes was checked by two researchers. The similarity percentage of the selected codes was 87%. The validity of the interview guide was also confirmed by two experts. The validity of the research was also controlled by selecting the sample with the maximum information richness and also the precise determination of the data analysis unit.

By analyzing the interviews, 184 unique codes were extracted, and 41 skills and nine job competencies were compiled by categorizing them. The professional competencies of scientific experts were classified into two categories: general competencies and specialized competencies. General competence includes four items of communication characteristics, independent learning, training and counseling, and knowledge management. Specialized competence was formulated, including 5 items of ability to use scientometric tools, scientometric data management, specialized knowledge, data mining techniques, statistical analysis tools, research policy-making, and strategy formulation.

With the expansion of the scientometrics field and its activities in Iranian organizations, the necessity of compiling the job competencies and professional skills of experts in this field was felt as an independent specialty. In addition to identifying the competencies and skills needed by scientometrics specialists, this article helps to know more about this field and shows the importance and necessity of this field in academic and scientific institutions. Scientometrics, as a job in the set of organizational jobs, has competencies and skills that can be the basis of integrated human resource science in training, hiring, and evaluating professionals in this job. The value of this research findings is in line with the actual activities of the job and global scientometrics trends. The identified competencies and skills showed that the curriculum and course titles of scientometrics do not cover all of these cases and need to be reviewed for this purpose. Furthermore, some general competencies and skills cannot be included in the curriculum and require in-service training provided by science centers.

This study aims to study the social and behavioral sciences research outputs at Shahid Beheshti University using indicators of Scientometrics and Altmetrics during 2010-2020. In the current world, where research is considered a factor for increasing power, countries try to raise the quantity and quality of their research outputs. Scientometrics is a field of research that uses statistical and measurement methods to determine the growth and development criteria of science and help determine the position of countries quantitatively.  On the other hand, the Web 2 revolution and the current advances in information technology have had a great impact on various scientific fields, and the possible benefits, and have changed the behavior of researchers. The wide level of access and widespread use of the web has made researchers use this space to share their works and increase the visibility of their research outputs, and tend to be more present in social networks and connect with the virtual world.

The indexed research outputs in Scopus in the field of social and behavioral sciences were studied.The current research was applied and was conducted with Scientometrics and Altmetrics approaches. Scopus, Scival, and Altmetric databases were used to gather data. The data were analyzed using descriptive and inferential statistics tests in Excel and SPSS software.The investigated community is all research outputs in the subject areas of social and behavioral sciences, including "subject areas of psychology", "economy, econometrics, and finance", "business, management and accounting", "social sciences", and "decision-making sciences", according to the category The subject of the Scopus database is Shahid Beheshti University in the years 2010 to 2020.

In terms of Field-weighted citation impact, the highly cited articles were in the top 10% threshold, the top journals were in the top 25% threshold, and the subject area of business, management, and accounting was located in the highest rank. The most used social media in all areas were Twitter and Mendeley. In terms of the number of tweets, the field of psychology with 599 tweets has the most mentions and 3079 mentions in Mendeley, in the first place, and economics, econometrics, and finance have the least mentions and signs with 14 tweets and 348 mentions. In the correlation section, the results of the Spearman test showed that the subject areas of psychology and decision-making sciences have a statistically significant relationship Between the number of citations index and the altmetric score.

The research outputs of Shahid Beheshti University in the subject areas of social sciences and behavior had an ascending process during 2010-2020. The reason for this can be the increase of students and researchers at different levels. It can be stated that by inserting a digital object identifier (DOI) for all the outputs, their effect will be investigable based on the Altmetrics indicators. Universities need to emphasize the quality of research outputs in addition to the quantity of these outputs and also considering the special research credit and credit for authors of articles in top journals can be a suitable solution to increase the quality of research outputs. The results of this research can be used for planning at the level of management, and various vice-chancellors in the university under review, and by knowing the priorities, abilities, and weaknesses, provide the necessary facilities to make scientific activities more targeted in the fields of social and behavioral sciences in the university under review. Finally, the findings of this research can help identify the scientific position of the desired university in the subject areas of social and behavioral sciences, as well as plan for the development of the university at the national and international levels.

Understanding the new opportunities and challenges in architecture and urban planning requires a holistic view of the scientific productions of this field. Evaluating scientific productions in neuro-architecture, which is one of the emerging interdisciplinary topics, has not been done so far. Accomplishing review research can help to achieve the mentioned ideal. The purpose of this study is to evaluate Iranian scientific productions in the neuro-architecture field based on a literature review.

The type of study is applied research based on scoping review, and descriptive analysis carried out with content analysis method and scientometrics approach. The research was performed by reviewing articles by Iranian researchers from 2003 to 2020. The search was completed in the 12th month of 2020 in scientific sources. The selection of articles was based on the PRISMA model, and finally, 27 articles were selected from among 480 studies, including 16 articles in the Persian language and 11 articles in the English language. In data analysis, descriptive and content analysis methods were used. Excel and UCINET software were used as tools.

The initial impression is that the number of articles in the neuro-architecture field has increased considerably from 2003 to 2020. The first study in neuro-architecture was published in 2012. The most considerable number of articles is 15, published in 2020. The evaluations showed that 37% of articles were written with quantitative research methods, 37% with qualitative research methods, and 26% with mixed research methods. "Iran University of Science and Technology", and "Shahid Rajaee teacher training University" have the most article production in neuro-architecture. The journals: "Soffeh" and "Urban Management" with 6 papers had the most remarkable number of articles in this field. Studies show that articles’ content can be categorized into four groups: "Aesthetic and Visual preference, Environmental Health and Well-being, Wayfinding and Navigation, and Phenomenology and Sensual perception". The topic of "Environmental Health and Well-being" with 10 articles has the most significant numbers and the topic of "Wayfinding and Navigation" with 5 articles has the fewest ones. Drawing the co-occurrence keywords network showed that 5 keywords with at least 3 repetitions had the highest number of repetitions among the keywords. These keywords included: "Aesthetical preference, Electroencephalography (EEG), Sensory perception, Facade design, and Cognitive features". Among buildings, façades with 29%, and educational and cultural buildings with 4% have the highest and the lowest amount of study, respectively. "Questionnaires and interviews" were the most crucial research tools with 29%, and "Sketch" was the least frequent tool in extracting data from articles with 3%.

The investigation of the findings shows that the research about neuro-architecture has been introduced in Iran with a decade delay compared to the rest of the world. One of the substantial reasons for this time gap is the lack of scientific and, laboratory equipment related to neurological research in Iran, which has been provided in recent years with the establishment of the National Brain Mapping Laboratory and similar research centers. As mentioned, the topic of "Environmental health and Well-being" has the most extensive number of articles in the scientific productions of neuro-architecture in Iran. It seems that the World Health Organization's emphasis on mental and environmental health in 2016 affected the increase in the number of studies in this field. The three keywords "Color and Light, Aesthetic preferences, and Façade design" have the most co-occurrence with each other and other keywords. Based on this, most of the studies performed in the field of aesthetics have examined the effect of color and lighting on viewer preference, which is often evaluated on the façade. In general, the approach to Iranian scientific productions has changed from a descriptive approach to an experimental approach, and brain mapping studies are expected to increase in the future.

This research aims to analyze the functional and structural approaches of scientific communication in knowledge production by researchers in the field of scientometrics in Iran to show how knowledge production by researchers in a context is affected by the functional and structural approach-oriented.

This research has been done by a mixed method, However, content analysis has been used. The research sample was the scientometric experts who were working in the universities. We had five phases for complementing this research. In the first phase, we tried to identify the scientometricians and extract the required information from the universities websites. In the 2nd phase, we designed a questionnaire to answer the research questions and in the third phase we used semi-structured interviews for the qualitative part of the research. In the fourth phase, the data gathered from the previous phases, are categorized separately. To analyze the data from interviews we used content analysis techniques and finally began to analyze them with the appropriate software such as SPSS.

The finding has shown that researchers in this field tend to use specialized tools to establish their scientific communication and the most common reason for participating in this type of tools are factors such as understanding specific issues, knowing the scientific community around them, etc. Furthermore, it was determined that scientometric studies to produce knowledge used two main tools which are social networks such as Email, Linkedin, ResearchGate, Whatsapp, and Weblogs and scientific search engines like Microsofacademia, Google Scholar, and Semantic Scholar. Besides, for maintaining precedence in proposing ideas and theories, they prefer to share their knowledge in academic environments through formal channels such as bringing them up in scientific forums. According to the structural approach, most of the facilities provided to researchers by Iran’s scientific institutions were technological facilities and they wanted to increase government support. Creating virtual scientific communication centers and making scientific workgroups in different scientific fields was another finding. Researchers emphasized research development factors such as international and national university cooperation, Open Access to scientific and educational resources, management based on expertise and knowledge, and material and spiritual encouragement of researchers.

Scientometric Researchers tend to use two-way and specialized tools such as databases and believe that this type of communication has improved their communication process in response to their needs. It has also affected the quality of their products and scientific activities. The results showed that virtual communication environments have a high capacity for the production and transfer of science as well as the formation of strong scientific relationships due to their interactive capabilities. It was also found that scientometrics researchers in using such databases more than others to generate knowledge and communicate because of the two-way and specialized nature of communication channels such as Google Scholar. The results showed that the most motivation and reasons for the presence of researchers in social media are factors such as finding out the specific issues of their field, searching and obtaining scientific and educational information, sharing scientific information, obtaining general information and news, and in the second place, things such as Getting to know the scientific community around you, consulting and thinking with other researchers, promoting and developing professional activity, and chatting online are the least used by researchers. Scientometric researchers believe that both official channels (such as databases) and unofficial channels (such as conferences) are suitable for presenting their ideas and theories, but most researchers share their scientific achievements in Formal environments are considered more reliable than informal environments. However, for various reasons, including the filtering of some official channels, some researchers believe that these conditions make it difficult to share their scientific achievements. The most important factors for the strengthening and development of research in society from the perspective of researchers are factors such as: creating a virtual center for scientific and research communication, determining suitable scientific communication patterns and making it coherent, appropriate scientific policy making concerning interdisciplinary approaches, determining scientific topics that can be researched with Interdisciplinary approaches in scientific centers are the formation of appropriate scientific working groups using experts from different fields. From the point of view of researchers in the field of scientometrics, the facilities, and facilities that society should provide to this group of researchers include government support for interdisciplinary research, material support for researchers, and setting up a research and development unit.

The increasing growth of Ontology Studies in the world has created the need to target scientific research in this field; By using various scientometrics techniques, the status of these studies should be investigated and studied from different points of view. This study aimed to analyze bibliometrics and co-authorship networks, and thematic clusters of ontology studies in the Scopus database during 1996-2020.

This study in terms of purpose is an applied and descriptive scientometrics, which has been done methodologically with co-word analysis and network analysis. The collected data (on December 10, 2020) were analyzed using Excel software. To analyze the data, VOSviewer, Pajek, and UCINet Software were used.

The bibliometric study and analysis of the co-authorship network and thematic clusters of ontology studies in the Scopus database indicates that 0.91% of the articles in this field are written in English and Since 2002, the scientific productions of this field have started their growth period and in 2012, they have reached their growth period. "Expert Systems with Applications" Journal with the publication of 101 articles, the “Journal of Web Semantics” with 80 articles, and “Semantic Web” with 74 articles, are considered the core Journals for the researchers of the Ontology field.  The field of computer science with 3941 articles has the largest share in scientific productions. Zhejiang University with the production of 69 articles (1.32%), Academy of Sciences Research Center and Universidad de Murcia with the production of 68 (1.30%) and 66 articles (1.26%), respectively, are among the most productive research centers in the field of ontology.  R. Valencia-García with 27 articles (0.51%) J.T. Fernández-Breis with 26 articles (0.49%) and M. Dumontier with 23 articles (0.44%) are among the most productive researchers in the field of ontology in the world. the most cooperation in the production of ontology research has been done by the countries of China, the United States, and the United Kingdom. In the study of the co-occurrence network of the Ontology field in the Scopus database, 5 topic clusters were identified which include the semantic web, ontology infrastructure, machine learning, linked data in the data web, and semantic description framework the semantic web cluster is the largest. In terms of the centrality index, Zhang, Y. with a centrality score of 74, Li, J. with a centrality score of 62, and Wang, Y. with a centrality score of 54 are in the first to third ranks. Also, in terms of the closeness centrality index, Stellato, A. with a centrality score of 5640 had the highest degree of closeness. According to the centrality index, Decker, S. with a centrality score of 7037.317, Horrocks, I. with a centrality score of 6686.898, and Wang, Z. with a centrality score of 6217.040 are in a good position in the network. In terms of the centrality index of the special vector, Valencia-García, R. with a centrality score of 1, Garcia Sanchez, F. with a centrality score of 0.868, and Colomo-Palacios, R. with a centrality score of 0.798 were ranked first to third.

Drawing maps of the scientific structure of different disciplines, including ontology, can be useful from different points of view. The analysis of the field of ontology can help researchers to know the scientific limits and boundaries, the general understanding of the scientific structure for beginners, and the choice of the research field, and it can also serve as a guide map for researchers and decision-makers in the field of existence. Science should be used to identify the priorities of research and adapt it to the future needs of society.

Brucellosis zoonotic infectious disease is caused by the dangerous bacterium Brucella and is one of the common infections in many countries of the world. In addition to pathogenic, clinical and clinical cases, Brucella as a dangerous bacterium can be considered a potential biological weapon and weapon in Biowarfare and Passive Defense. Therefore, brucellosis, as a serious threat to public health, health and human life, is always under special attention. Its emergence and re-emergence can be considered a serious threat to public health and human health. The purpose of the current research is to study the productivity and efficiency of Brucella and Brucellosis researchers in their scientific collaboration network.

The present research is considered to be a type of scientometric applied research, which uses the co-authorship analysis technique as well as the social network analysis method to study the productivity and efficiency of researchers in a 100-year period with centrality index methods, examining the co-authorship and co-citation network based on the documents indexed in the database. Web of Science Core Collection (WOSCC) has been done. In this research, keywords were selected from Medical Subject Headings (MeSH) 2020 and Bibexcel, Net draw, UCINET 6.528.0.0, VOSVIEWER, SPSS 16, Ravar PreMap and Excell software were used.

A researcher like "Cloeckaert, A.," was the most productive (most productive) and most efficient (most cited) researcher in the field of Brucella and Brucellosis and had the highest rank in degree centrality. Also, there is a significant relationship between the centrality scores (degree centrality and betweenness) of researchers and the level of productivity (number of articles) and the level of efficiency (number of citations) of researchers. The existence of a significant relationship between productivity and intermediate indicators, which shows the social influence of individuals, also indicates that researchers who have a high intermediate index have a mediating position in the information flow of the co-authorship network in the territory of Brucella and Brucellosis, as a result, more articles are also Interaction with other writers will produce. On the other hand, no significant relationship was observed between the closeness centrality score and researchers' productivity. In the present study, "Cloeckaert, A.**Zygmunt, M.S.," the best co-author couple were identified, who had scientific and expert cooperation with each other in the field of Brucella and Brucellosis with 63 contributions. As a result, the most participating researchers in the field of Brucella and Brucellosis are in WOSCC (1920-2020), which shows the superiority of these two authors in the mentioned research field. Examining the components of the researchers' co-authorship network shows that this network, like many other social networks, consists of one main component and 3 small components. The results related to the density of the co-authorship network show that in this period only 0.086 of the total possible and potential relationships have been actualized in this network, the tendency of the researchers to form different clusters through co-authorship was low. The citations received by researchers had a positive relationship with the amount of publications of their articles. The higher centrality score of researchers has a high impact on their position in the co-authorship social network. According to centrality indices, "Cloeckaert, A." and "Kim, S." have the highest degree centrality. These people have played an active role in the co-authorship network of the studied area and have co-authored more than other researchers. "Letesson, J.J." and "Cloeckaert, A.," have the highest closeness centrality. This means that their placement in the center of proximity and having the shortest distance with other researchers in a network is of strategic importance for that researcher, and this proximity to other authors will allow him to access all the researchers in the network faster than any other author. "O'Callaghan, D." and "Jiang, H." have the highest betweenness centrality, so they have a favorable and powerful position in the co-authorship network in the investigated area and influence the research process and activities in this area. A total of 145 authors with a minimum number of 20 articles have had scientific participation at a favorable level.

The main existential philosophy of scientometrics is to help scientific policy making. In this regard, many techniques and methods for quantitative and qualitative monitoring and evaluation of various scientific and specialized fields have always been introduced in various fields of study. On the other hand, the presence of researchers in the field of scientific publications is considered one of the ways to strengthen the scientific capital of the country for the purpose of sustainable scientific development, so the application of the results of the present research will provide an objective and real insight to specialists and planners in determining implementation strategies in the field of health and Health and policy making in medical science organizations.

Considering that the volume of publications is growing at an increasing speed, forecasting the research trend and identifying emerging issues is of particular importance. It should be noted that choosing the right method for accurately predicting the research trend is very important, which has been the focus of many researchers in recent years. In this regard, the present research aims to present the findings of research conducted in Iran and the world regarding the most important approaches and proposed methods for predicting the trend of scientific outputs in the future.

The present study was conducted using the scoping review method. The implementation of the current research includes 5 stages: 1) Identifying research objectives, 2) Identifying related research, 3) Selecting research, 4) Data extraction, and 5) Summarizing, discussing, and reporting the results. To identify relevant research, international databases in English (ScienceDirect, Emerald, Scopus, Web of Science, and ProQuest) and Iranian databases in Persian (Magiran, Noormags, Civilica, SID, and Irandoc) were searched without considering the time limit. In this research, the PRISMA diagram was used for the sampling and data selection process, and the JBI evaluation tool was used to check the quality of selected sources. Finally, 117 effects were analyzed.

An overview of the studies carried out in forecasting research trends shows that these studies have attracted the most attention of researchers in the world and in Iran during the last two decades (especially from 2012 onwards), and the increasing trend in conducting these researches is evident. The most important studies conducted concerning the future of studies were the studies that identified trends and emerging research topics to determine the future direction of studies. In different periods, various approaches have been used to determine emerging issues and predict future research trends, which can be divided into 5 main categories: scientometric, quantitative and statistical, qualitative, mixed method, text mining, and machine learning. A review of studies showed that the most common approach used to identify emerging topics and predict future research trends was the scientometric approach. However, in recent years, due to the limitations of quantitative analysis and scientometric methods to determine the direction of future research, and with the increase in the volume of scientific production and the problems resulting from the analysis of large volumes of data, advances in computer technology and word processing tools. Text mining and machine learning approaches have been used to identify emerging areas and predict future research trends due to their high power in big data analysis along with traditional scientometric methods. The most important disciplines that have paid attention to the problem of predicting the trend of scientific outputs are related to sciences and engineering. It seems that paying attention to this issue in the mentioned fields can be because the speed of developments in these fields is higher and as a result of the necessity of conducting studies to predict the future developments of studies to synchronize and deal with them correctly before other fields and more has been The most important sources to be analyzed to achieve the future path of researches are the articles published in journals. The reason for the focus of these studies on journal articles can be that in any scientific field, articles are usually the result of research projects, theses, and other research experiences, which due to the limited access to these sources, can allow researchers to quickly access the results of these studies. and provide more convenience. On the other hand, scientific publications publish the latest scientific achievements and research findings in the shortest time, and this causes researchers and those engaged in scientific activities to be aware of the latest and most reliable scientific and research achievements. Therefore, to study the future trend of scientific outputs, articles have been considered more than other sources.

Different models and approaches have been proposed by researchers to follow the evolution of scientific products in the future. But it seems that a combination of quantitative and qualitative approaches is needed to make accurate and reliable predictions and overcome the limitations of each of these methods. Be used simultaneously. In addition, utilizing expert opinions can be considered as a complement to scientometric analysis to predict the future. Having a future research approach in scientific policy-making and research management can play an effective role in charting the prospects of scientific development and provide the possibility of policy-making and planning for the future for researchers and stakeholders in various fields.

Co-word analysis is a tool to depict the intellectual structure of scientific productions. So the purpose of this study is to map the intellectual structure of research status in the field of educational management in Iran.

This applied research has been done by co-word analysis. The research population includes all original Persian scientific articles indexed in databases, named Normagz, SID, and Magiran. Examples with the four main keywords "educational management", "educational leadership", "school management" and "school leadership" along with their sub-topics and their plural and singular states based on searching for the same phrase and without applying a time limit, during the years 1988 to 2020, between 2nd and 20th of July 2020 were searched.  These keywords were selected according to "Eric Online Thesaurus", "Persian subject headings", "Congress library subject headings", "Educational management culture book" and "consensus of three professors of educational management". To collect data, first, 1066 articles were retrieved by an advanced search of selected keywords, and 891 articles remained after removing duplicate and unrelated items. In the next step, all the keywords of the articles that were under each title of the article were placed in the Excel file in one column, and the keywords in the titles of the articles were examined one by one by the researcher and after getting the final opinion from the experts in the field and they were given in the continuation of keyword column. At first, 3688 keywords including their repetitions (2221 words excluding repetitions) were obtained from the titles and keywords of the articles. After correcting the typographical and space errors that were too much due to the entry of relatively inappropriate information in Persian databases, the phase of assimilation of words began. In the next step, while checking the keywords one by one, referring to the accepted and common keywords (including 56 keywords) with the opinion of experts in the subject area of the research. Finally, a list of keywords was obtained in which all the words with semantic connections were replaced with the general keyword. A number of keywords completely unrelated to the subject area were also removed based on the opinion of subject experts in the field of educational management. Finally, the number of 2203 keywords, including their repetition, remained for further analysis. Afterwards, the researcher replaced the selected and referred keywords in the entire research data. Excel, RavaR Matrix, and UciNet software were used for data analysis and NetDraw was used to visualize the co-word network.

"Educational Management", "Educational Leadership" and "School Management" have been the most common themes in terms of co-word. In fact, these words form the main discussions related to this field. Hierarchical clustering resulted in the formation of 3 clusters in that the educational management cluster has a central and important position as a mature and developed cluster. Educational Leadership and School Management were identified as underdeveloped and emerging or declining clusters and compared to the educational management cluster, they have attracted less attention in the studies of the educational management field.

The study of the knowledge structure in the field of educational management identified the research status that can be a roadmap for future research. In the field of educational management, the issues surrounding learning leadership and school management as immature and underdeveloped clusters need more attention in future research. Therefore, if attention to these issues is placed on the agenda of the country's educational system, we will see more prosperity in the field of educational management in the future. Therefore, pushing the scientific community toward these issues and conducting research in this direction will be practical and fruitful.

 The purpose of the present study is to compare the thematic trends of scientific productions related to Covid 19 in the fields of humanities and social sciences in Iran and the leading countries of the five continents based on the studies of Web of Science. 

 The present scientometric research has a descriptive-analytical interdisciplinary approach through social network and co-word analysis techniques which is one of the methods of content analysis. Bibexecl, Gephi, and SPSS software were used to analyze the data, and VosViewer software was used to draw thematic clusters.

 The United States, England, China, Australia, and South Africa are the leading countries. Iran ranks 37th in the world and 13th in Asia. Co-word clustering in US studies consisted of 6 clusters, in Chinese and South African studies, 7 clusters, in British studies, 8 clusters, in Australian and Iranian studies 10 clusters. The clusters of "China and Australia", "The UK, and the United States" have thematic overlap, however, there are more clusters in the studies of Australia and Iran. There is a positive and significant relationship between the amounts of scientific production related to Covid 19 in humanities and social sciences and the prevalence of the disease (number of patients) in Iran and the leading countries. There was no significant difference between countries in terms of the number of citations received; The number of scientific productions of countries in the fields of humanities and social sciences and health is not significantly different from each other; There is a positive and significant relationship between the rate of scientific production of Covid 19 in the fields of humanities and social sciences and the prevalence of the disease (number of patients) in Iran and leading countries.

 Based on the results, the emergence of Covid-19 as an important health and social issue has made the management of various economic, social, cultural, and political complications inevitable. It is in this direction that in the results of this research, the repetition of concepts such as empowerment, participation, governance, management, and crisis management, etc. can be seen. This shows the existence of new thinking and policies in the post-coronavirus era to control and contain such a crisis. Also, according to the results of the research, "depression, mental health, risk, social media, crisis management, influence" are frequent in Chinese studies from the Asian continent. The most centrality of degree, closeness, and betweenness is related to the concept of "resilience". In England, from the European continent, "higher education, online learning, management, innovation, mental health, depression, society, engagement, motivation, knowledge" are the most important trends of researchers. The most centrality of the degree, closeness, and betweenness is related to the keywords "crisis and motivation". In the United States of America, "depression, stress, social support, education, participation, influence, management, leadership, employment, self-education, distance education, and science" are more common and the most important subject tendencies of researchers in this field. The most centrality of the degree, closeness, and intermediateness is related to the keyword "distance education". The most centrality of the degree, closeness, and intermediation is "distance education". "Social media, education, literacy, society, satisfaction, influence, mental health, poverty, governance, and humanities" are frequent in South African studies from the African continent and constitute the most important intellectual tendencies of researchers in this field; The most centrality of degree, closeness, and intermediateness is "higher education and poverty". In the studies of Australia from the Oceania continent, "education, technology, tourism, management, science, culture, social work, mental health, depression, anxiety, neoliberalism" are frequent and important and are the most important trends of researchers; The most centrality of degree, closeness and intermediateness is related to "crisis and gender". In Iranian studies, "depression, influence, behavior, perception of risk" have a central place among the most important tendencies of researchers; In the studies of this country, the most centrality of degree, closeness, and intermediateness is related to the keyword "simulation". In this way, in the subject area under discussion, there are also differences in the subject tendencies between countries. However, in a general look at the results of the cluster analysis of the studied countries, it can be said that the clusters of the countries of China and Australia with topics such as "technology and media, management and mental health" and the clusters of the countries of England and the United States with topics such as "depression, society, education, participation, management, online learning, and science and knowledge" have thematic overlap.

Diabetes, as one of the most common metabolic diseases, causes the death of a large number of people every year. It is predicted that the prevalence of this disease in the Middle East region will increase significantly by 2030. For this reason, this study has been conducted to compare the results of research conducted in the field of diabetes by researchers from the Middle East countries in the Web of Science database during 2010-2019 with indicators of intellectual and social influence.Intellectual influence, in the sense of the use of research results, is determined by calculating contemporary H, G, and H indices. Social influence is also calculated in terms of identifying authors and collaborations between them. This concept is identified through the calculation of co-authorship and also the indicators of degree, betweenness, and closeness centrality.

The current study is applied research. The indicators of intellectual influence and social influence of the Middle East countries and institutions in the field of diabetes were investigated using social network analysis. The community of this research includes articles indexed in the Web of Science database related to the authors of the Middle East countries in the field of diabetes from 2010 to 2019. Excel, BibExcel, and Pajek software have been used to calculate the indicators of intellectual influence and social influence.

The findings showed that Turkey was the most prolific country in the field of diabetes in the Middle East, with 6701 articles. Iran was in second place, with 5746 articles. Therefore, only two countries from the Middle East have more than 5000 articles during this period. Saudi Arabia, Israel, and Egypt were also in the third to fifth positions with 3327, 3062, and 2950 articles, respectively.Based on the total score of indicators of intellectual and social influences, Israel, Saudi Arabia, Turkey, Iran, and Egypt have been ranked first to fifth. Active countries in the field of diabetes in the Middle East are Turkey, Iran, Saudi Arabia, and Israel, respectively. Iran had the largest share (40%) of organizations with 8 institutions among the top 20 institutions in the Middle East in terms of the number of publications. Israel had 4 institutions (20%), Saudi Arabia 2 institutions (10%), Turkey 3 institutions (15%), and Egypt 3 institutions (15%). With 1470 articles, the Tehran University of Medical Sciences was ranked first among the top 20 institutions in the Middle East in terms of the number of articles in the field of diabetes between 2010 and 2019.However, based on the analysis, it was found that Israel has the first rank in the total scores of the three indicators H, G, and contemporary H. Saudi Arabia, Turkey, and Iran were ranked second to fourth among the Middle East countries in the field of diabetes, with the total intellectual influence score of 215, 205, and 203 respectively.The total score of the social influence indicators (the total score of degree, closeness, and betweenness centrality) of 20 top institutions and universities in the Middle East in terms of the number of articles in the field of diabetes indicates that the universities of Hajat Tepe, Mansoura and Tehran University of Medical Sciences ranked first to third with total social influence index of 296, 275 and 267 respectively.According to what was said, the existence of four countries, Iran, Turkey, Israel, and Saudi Arabia, in the top position of the major indicators examined, has made them among the prominent countries of the Middle East region in the field of investigation.

In conclusion, it can be said that influential researchers, establishing scientific cooperation, the existence of infrastructure and advanced research centers, a more favorable economic situation, and the focus of some countries, including Iran, to achieve self-sufficiency and scientific improvement compared to other countries in the region can be considered influential factors in this field.

Due to the importance of artificial intelligence, the increasing growth, and the high penetration rate of this technology in other sciences, the necessity of conducting scientometric studies is fully felt. The literature review on the research topic shows that very few studies have been conducted in this case or with not enough comprehensiveness. Considering rapid and significant progress in this field, it needs to be clarified to reveal the current situation and future trends based on scientometric techniques.To fill this existing gap, the present study seeks to answer the question that how is the scientific map of the published studies in the field of artificial intelligence by Iranian researchers in the Scopus database, and based on this map, what are the noteworthy fields of researchers?

The current research is a quantitative and practical study using scientific methods, including co-word analysis and social network analysis. The research population includes all documents in the field of artificial intelligence with at least one author who is affiliated with an Iranian organization and indexed in the Scopus database from the beginning to January 2022. VOSviewer and Gephi are the software used to analyze data and extract maps. The reason for choosing the Scopus database is that this database contains 70 million research articles reviewed by more than 5000 international publishers (Zhang et. al, 2021), and also the database has relative uniformity in all fields (Batooli et al. 2019).

The results of the analysis show that Iranian researchers have published the most documents in 2021, and also the best position of Iran in the field of artificial intelligence was the 20th rank, which was achieved in 2021. Overall, Iran ranks 31 in thisdatabase and third among Middle Eastern countries after Israel and Turkey.Among the types of published documents, articles with number of 3124 are in the first place and notes are in the last place with a number of two published items.19.9% of the published documents of Iranian papers have not received any citations. The greatest number of published documents have between 1 and 5 citations. The highest number of citations belongs to an article with 824 citations.Also, findings show the most frequent keywords are "artificial intelligence", "algorithm" and "optimization".The network structure of high-frequency keywords with a repetition threshold of at least 15, consists of five clusters. In the first cluster, the keyword"neural network" has the highest link weight. In the next "artificial intelligence", "machine learning" and "learning systems" have the highest link weights and the only word in the fifth cluster is "mathematical model" and keywords are placed in five clusters: “inference and prediction”, “intelligent algorithms”, “diagnosis and learning”, “data analysis”, and “mathematical models”.In the coauthor network of 80 countries collaborating with Iranian writers, the most collaboration is between Iranian and American researchers. This network has classified collaborating countries into eight clusters based on direct relations.

The findings showed that the most frequent keywords are artificial intelligence, algorithm, optimization, and neural network. Optimizing is common between this study and GhaviDel, Nezamdost, & Riahinia's (2020). Also, the neural network is common between the present study and the study of Feng & Law (2021) and the study of Darko et al. (2020).The comparison of the most frequent keywords in Iranian and non-Iranian documents shows that Iranian researchers in choosing their research topics were aligned to the general trend of scientific development in most years, and in some years, they have progressed with a step delay.The results of the cluster analysis show that the studies were divided into five thematic clusters. This is even though the study of GhaviDel, Nezamdost, & Riahinia (2020) identified 12 clusters. Also, the difference between the results of the clustering of the present study and the study of Taherian & Assareh (2012) is that in the present study, clustering was done on the documents published by Iranian researchers, but in that study, the clustering was done on all the published documents in the field of artificial intelligence.According to the findings of the research, at the beginning of 2022, Iran was in the 31st rank.Meanwhile, Iran's rank in the study of FarzinYazdi and RezaeiSharifabadi (2017) in the same Scopus database was 17.Iranian researchers do not observe standard affiliations of education institutes and it leads to inaccuracy in the search results.Also, the results show that the process of Iranian documents has been generally upward. However, this growth rate is lower compared to other countries. In the following research topics, Iranian researchers have been in line with the general direction for most of the years, and in some years they have been one step behind.