پژوهشنامه علم سنجی
پیاپی 20 (پاییز و زمستان 1403)

In recent decades, higher education has increasingly faced pressures to address real-world challenges in social, economic, environmental, and technological domains. The literature indicates that universities have expanded the traditional notion of science to include new missions. Their responses to these demands varied based on their regulations and social contexts. Some universities demonstrated strong local or regional orientations, while others broadened their activities to become international players. Additionally, some institutions adapted their internal procedures to embrace new administrative methods or transformed into entrepreneurial universities. Consequently, the literature provides evidence of a positive response from universities, although this response is scattered and not uniform on a global scale.As strategic plans offer managerial insights and operational frameworks for achieving organizational goals and missions, their content can be analyzed to examine university responses to various demands. This study employed a quantitative content analysis method to investigate the strategic plans of universities worldwide, exploring their approaches to new academic missions, the emerging subjects recently included in these plans and their correlation with the development levels of their respective countries.

The research sample comprised the strategic plans of universities worldwide that are accessible on the web. The universities were initially identified using the list provided by the Scimago Institutions and University Rankings, which included 4,126 universities at the time of data collection in May 2022. By employing the following formula in the title field of documents indexed in Google, the strategic plan of each university was located, and its full text was downloaded:("strategic plan" OR "strategic plans" OR "strategic planning" OR "Strategic * plan" OR "action plan" OR "action plans" OR "action planning" OR strategy OR vision OR mission OR values) AND [University Name]852 strategic plans in both English and non-English languages were retrieved, available in either text or image formats. The non-English strategic plans were translated using Google Translate, while image files were converted into text with Google Docs. The complete texts of the strategic plans were then input as plain text into VoSViewer software, version 1.6.19, where their co-word maps were analyzed following linguistic pre-processing. A thesaurus was developed and utilized to standardize the terminology.To identify novel subjects that have recently emerged in the strategic plans, they were weighted according to the commencement year of their respective periods. Furthermore, to examine the relationship between these subjects and the development levels of their respective countries, the plans were weighted by the Human Development Index and Gross Domestic Expenditure on Research and Development, as reported by the United Nations Development Program and the World Bank, respectively. A whole counting method was employed to calculate term frequencies. Additionally, a threshold of occurrence in at least ten strategic plans was established for a term to be included in the map. A total of 1,158 words or phrases were identified. By applying a threshold of 60% of the most relevant terms, 695 terms were included in the final map.

Five clusters were identified including “society”, “students”, “systems”, “transformation”, and “graduate programs”. The largest cluster, i.e., “society”, included the concepts related to education, research, and innovation. The terms “society” and “world” were respectively the biggest nodes in this cluster, indicating the connection of these main missions with real-world challenges. In the “graduate cluster”, the “global rankings” node occurred linked to “sustainable development goals”, “international collaborations”, and “partnerships”. In the “student” cluster, “courses" was the second largest node. Along with the terms related to classic academic missions (i.e., “students”, “graduate programs”, and “courses”), the terms related to new academic missions were observed including “communities”, “world”, “economy”, “sustainable development”, “economic growth”, “social growth”, “excellence”, “solutions”, “diversity”, “climate”, and “climate change”. The terms’ occurrences showed dependence on the plans’ novelty and country development level. For example, the terms “communities”, “social enterprises”, “sustainability”, “global rankings”, “sustainable development goals”, “web applications”, and “circular economy” occurred for moderately to highly developed countries.

Universities worldwide have broadened their focus beyond traditional missions to encompass new objectives related to the economy, society, and the environment. The reliance on these terms varies according to each country's level of development, highlighting the necessity for pragmatic policymaking to establish achievable short- and long-term goals. Furthermore, this situation raises concerns about the potential to deepen divides among nations due to differing objectives set for higher education. Notably, the lack of terms associated with research output and traditional mission-oriented ranking systems poses a challenge to the for ranking's sake approach.

With the growing complexity of organizational environments in both the private and public sectors, the need for inter-organizational cooperation has become increasingly important. Consequently, in recent decades, the concept of an ecosystem has been introduced to facilitate connections between organizations across various fields of management science. With the rapid development of Industry 4.0, various ecosystem combinations—such as innovation ecosystems and entrepreneurship ecosystems—have emerged. Among these, digital ecosystems represent a newer and rapidly evolving field that has garnered significant attention from researchers in recent years. The purpose of this study is to conduct a scientometric analysis and visualize a map of the knowledge structure, co-authorship network, and thematic clusters related to digital ecosystems within the field of management, as indexed in the Web of Science database.

This research is an applied study that employs common techniques in scientometrics, specifically co-occurrence analysis methods. To obtain the primary data, the keyword "digital ecosystem" was searched in the Web of Science database for the years 2000 to 2023. A total of 4,496 articles published in this database were analyzed as the statistical population. The data were analyzed using VOS Viewer and BibExcel software to extract the knowledge map and co-occurrence network. In this research, the authors' fields and indexers' keywords were utilized for synonym analysis. After retrieving the records, a total of 14,140 keywords were obtained from the 4,496 examined records for co-occurrence analysis. Of these, 1,173 frequent words, identified based on Bradford's law with a frequency of 5 or higher, were selected for co-word analysis.

14,140 keywords were identified in this analysis, with 1,173 instances exhibiting the same timing in the co-occurrence analysis of five words. The results of this six-cluster analysis indicate that the most recent emerging topics in 2021 are associated with a range of innovative information technologies, intelligent relationships, entrepreneurial ecosystems, digitalization, digital servitization, ecosystem architecture, and their impacts. The co-occurrence of the keywords shows the highest frequency in research related to the digital ecosystem from a management perspective. The United States, the United Kingdom, and China have made the most significant contributions to research on this topic. The findings reveal that Parida V. is the most active author, and the fields of computer science and information systems are recognized as the most prolific areas of study. Additionally, terms such as identified as the most frequently used keywords, which were categorized into six clusters based on their co-occurrence. An analysis of international collaboration revealed eight clusters, with the highest level of collaboration occurring in the first cluster, which includes 20 countries, while the least collaboration is observed in cluster eight, which comprises only three members.

The scientometric study and analysis of the co-authorship network and thematic clusters related to the concept of the digital ecosystem from a management perspective, as sourced from the Web of Science database, revealed that 99.13% of the scientific documents in this field were published in English. The highest frequency of articles on this topic occurred in 2022, marking the peak of research in this area, particularly concerning the Fourth Industrial Revolution and emerging technologies. Based on the time series analysis, three distinct historical periods can be identified. The first period focuses on the design and initial planning of the ecosystem, while the second period encompasses themes such as management, innovation, dynamics, platforms, value creation, strategy, competition, and performance. In the third stage, the focus shifts to emerging information technologies, intelligent relationships, digitization, services, computer architecture, and the entrepreneurial ecosystem. The examination of the knowledge structure of the digital ecosystem from a managerial perspective indicates that it can serve as a roadmap for future research. Additionally, the analysis of the synonym network for the topic under investigation in the Web of Science database identified six thematic clusters: management of emerging technologies, innovation and entrepreneurship, co-creation, strategy, digital transformation, and networks. In countries' collaboration network, the United Kingdom has the highest number of collaborative links, followed by the United States, France, Spain, China, and Finland, which exhibit greater international collaboration than other nations. Meanwhile, the volume of documents published by Iran and its level of international collaboration warrant careful consideration. To enhance the country's development in the Fourth Industrial Revolution and leverage digital capabilities, Iran needs to reassess its international collaboration policies and actively participate in international scientific arenas to foster scientific growth and produce high-quality research publications.

Today, mental health is a critical issue worldwide that not only impacts individuals' quality of life but also leads to economic and social consequences for societies when there are deficiencies in this area. Despite the development of mental health infrastructure and services in recent years, significant funding has yet to be allocated to address these needs. To promote and enhance mental health, it is essential to not only identify weaknesses but also allocate an adequate budget for this area. This becomes feasible when there is a comprehensive understanding of the mental health status within local communities. To understand the mental health of a society, it is essential to examine the research conducted in this field. By evaluating scientific outputs, one can gain a comprehensive understanding of the mental health status of the local community. Additionally, by assessing the financial support for scientific articles, it is possible to gauge the efforts of organizations aimed at improving mental health within society. The current research aims to analyze the financial support of institutions concerning research outputs in the field of mental health in Iran, using a scientometric approach. The goal of this study is to conduct a scientometric analysis of research outputs that received financial support in the field of mental health in Iran, as indexed in the Web of Science database.

The current scientometric research consists of applied studies utilizing a quantitative approach. Data collection was conducted through documentary analysis, employing bibliometric techniques and co-occurrence of words. The research community comprises 3,833 sources, representing all research outputs with financial support in the field of mental health in Iran, which are indexed in the Web of Science database. In this research, no time limit was imposed, and all research outputs related to financial support in the field of mental health in Iran, as indexed in the Web of Science database, were considered. To extract data, a search strategy was employed. In exploring strategies within the field of mental health, concepts with the strongest semantic connections to mental health were taken into account. The analysis of the research questions was conducted using three software programs: Excel, BibExcel, and VOSviewer

The leading financial sponsors among university units in the country were Tehran University of Medical Sciences, with 628 cases; Isfahan University of Medical Sciences, with 231 cases; and Shiraz University of Medical Sciences, with 230 cases. Among non-academic organizations, the most financial support has been provided by the Iran National Science Foundation (INSF) with 156 cases, the Ministry of Health and Medical Education (MHME) of Iran with 67 cases, and the National Institute for Medical Research Development (NIMAD) with 59 cases. The British Medical Research Council (MRC) contributed 49 cases, followed by the US National Institutes of Health (NIH) with 40 cases, and the Australian National Health and Medical Research Council (NHMRC) with 38 cases, making them the top three foreign organizations, respectively. The studies identify nine subject clusters, with significant emphasis on issues such as depression, anxiety, stress, mental health, mental disorders, COVID-19, quality of life, and schizophrenia. The top three researchers receiving financial support in the field of mental health are Shahin Akhundzadeh, Mojgan Mirghforvand, and Vafa Rahimi Movaghar.

Most of the financial sponsors for mental health research in Iran are affiliated with organizations under the Ministry of Health, Treatment, and Medical Education, along with other entities that have not traditionally engaged as financial sponsors in this field. This lack of participation may stem from an improper division of responsibilities within the country's organizations; consequently, the Ministry of Health is recognized as the primary center of activity. Additionally, on an international level, financial support is restricted to a few specific institutions. Therefore, there is a pressing need to enhance collaboration and establish more connections with foreign organizations. Finally, it is anticipated that the results of this study will contribute to the development of an evidence-based information system regarding mental health research and its supporting infrastructure in the country. Scientometric analysis can be instrumental in evaluating the growth and application of knowledge, thereby aiding effective planning for scientific policymakers to enhance financial research support.

This study aimed to map and  analyze the knowledge structure of science, technology, and innovation policymaking studies using a co-occurrence network. Understanding the trends in the literature related to science, technology, and innovation policymaking enables policymakers to gain a broader perspective on significant global issues. Additionally, researchers can gain insights into the most prevalent topics in this field and navigate the boundaries of knowledge in science, technology, and innovation policymaking.

The current research is a descriptive study that employs scientometric indicators along with documentary and social network analysis methods. The research population consists of 3,868 articles and reviews published between 1969 and 2023 in the field of science, technology, and innovation policymaking. Data for the study was collected on June 3, 2023, by accessing the Web of Science database (a product of Clarivate Analytics). Microsoft Excel was utilized to analyze the research data and create a geographical distribution map. Additionally, Vosviewer software was employed to visualize the co-occurrence network of papers in the field of science, technology, and innovation policymaking, while Gephi was used to clean and remove unrelated keywords.

The number of published articles on the topic of science, technology, and innovation policymaking has been steadily increasing. Among the countries, the United States, England, China, the Netherlands, and Germany have produced the highest number of publications in this field. An analysis of journal publications revealed that the Sustainability Journal, with 89 articles; the Environmental Science and Policy Journal, with 74 articles; and the Journal of Cleaner Production, with 69 articles, have the most publications related to science, technology, and innovation policymaking. The co-occurrence network in this field consists of 221 nodes and 8035 unique links, and the most frequently occurring keywords among these nodes include science, policy, policy making, innovation, government, and technology. Furthermore, over the past five years, topics such as COVID-19, big data, sustainable development, data science, citizen science, circular economy, urbanization, energy transition, and CO2 emissions have been extensively discussed. The co-occurrence network in the field of science, technology, and innovation policymaking consists of five clusters: sustainable development, public health, climate change, government support, and public participation. These clusters represent different aspects of science, technology, and innovation policymaking.The findings indicate that the articles published by Iranian researchers on science, technology, and innovation policymaking have received 924 citations. In other words, each of them received an average of 7.7 citations, and 77.59 percent of them were cited at least once. In addition, these articles have performed less than the global expectation by obtaining a category-normalized citation impact equal to 0.92. Also, 79.38 percent of these scientific productions result from international collaborations and the highest amount of collaboration has been done with researchers from the USA, England, Australia, and Canada.

The policymaking process for science and technology is highly complex, and influenced by various factors, including global conditions, challenges, developments, trends, country of origin, and territorial considerations. To promote sustainable development goals, science and technology policies should prioritize innovation and entrepreneurship. Additionally, governments should focus on supporting activities that contribute to economic prosperity in this area. Health is a vital economic sector that not only directly impacts economic growth but also influences the development of other sectors. Policymakers in science and technology across various countries emphasize the significance of health research and the rapid deployment of new technologies, such as pharmaceuticals, diagnostic tools, remote treatments, and medical equipment. Science, technology, and innovation are crucial for sustainable development, as they aid in the formulation and implementation of policies and regulations concerning climate change. These policies may involve establishing standards, implementing energy regulations and taxes, utilizing tools to control pollution and greenhouse gas emissions, and protecting water resources and the environment. The government plays a crucial role in the formulation of science and technology policies, especially in developing countries, where it aligns with national priorities through various policy instruments. These instruments, often referred to as governance tools, are measures utilized by the government to accomplish specific policy objectives. Public participation in the science and technology policy-making process allows society to directly influence policies and decisions in this domain. This promotes transparency, trust, and the empowerment of society in matters related to science and technology, ultimately resulting in the adoption of improved policies, informed decisions, and positive outcomes for the community.

Science journalists can play a significant role in evaluating the social impact and "altmetric" score of research published in scientific journals through their coverage in news media. This requires the indexing of news articles in altmetric databases. The present study aims to investigate the performance of Iranian science journalists in the Altmetric.com database by analyzing indexed news articles from Iranian news media.

The data necessary for conducting this research were collected in two main stages from three databases: Altmetric.com, JCR, and Scopus. In the first stage, a dataset containing 2,972 news articles that mentioned research outputs from Iranian news media was downloaded from Altmetric.com. Next, the impact factors of the journals cited in the news articles were extracted from the JCR database. In the final stage, the list of DOIs for the research articles referenced in the news, available in the downloaded file from the previous stage, was combined using the OR operator, and a search was conducted in the advanced search section of Scopus.

The research results show that content published in eight Iranian news outlets—Fars News Agency, Iran Daily, ISNA, Tehran Times, Financial Tribune, Goya News, Tasnim, and IRNA—is indexed in the altmetrics.com database, accounting for approximately 0.1% of the media coverage on this platform. A total of 2,972 news articles from Iranian media are included in the altmetrics.com database. An examination of the types of sources reviewed reveals that Iranian news media have primarily extracted and published information from scientific journal articles, totaling 2,790 articles, or 93.88%. An analysis of the thematic coverage of these news sources indicates that out of 2,777 categorized publications, nearly one-third pertain to medical and health sciences, comprising 884 publications, or 31.83%. An analysis of the sources cited in Iranian news media reveals that science journalists in Iran tend to select topics from multidisciplinary sources. Prominent journals such as *Science* and *Nature* are among the leading references for Iranian news outlets. Furthermore, an examination of the organizational affiliations of the articles referenced in the news indicates that out of a total of 2,687 articles, only 198 (equivalent to 0.07%) were authored by researchers affiliated with Iranian universities. Science journalists in the country predominantly feature articles affiliated with the United States, with researchers from the University of Tehran receiving the most coverage among Iranian universities. An analysis of the publication dates of news articles recorded in the altmetrics.com database reveals that the highest number of indexed news articles—624 articles, accounting for 21%—was published in 2019. However, the trend of indexing news from Iranian media in the altmetrics.com database has declined since 2020.

The declining trend in the indexing of Iranian news media in the alt-metrics.com database over the past three years suggests that science journalists should place greater emphasis on research findings published in reputable scientific articles and journals when reporting on science news. Furthermore, the style of writing and coverage should be tailored to ensure that it can be easily identified and displayed in databases like altmetrics.com and other similar indexing platforms. The current performance of journalists and news media indicates that a substantial number of news articles reference research findings published in scientific journals (2,790 articles, or 93.88%). It is important to recognize that scientific articles are not confined to journals; they are also published in conference proceedings and various sections of books. Science journalists must be aware of these diverse sources. It is essential for science journalists to possess a comprehensive understanding of science, rather than confining their definition to specific fields such as medicine. Additionally, it is important to consider the interests of the public, as they are the readers of these news articles. Topics that resonate with the public should be prominently featured in scientific news coverage. Therefore, a science journalist must strike a balance between the credibility of the news source and the existing demand for it. The research findings in the section on the level of news coverage of domestic research indicate that, despite the high volume of scientific production in Iran, these publications have received minimal attention in the news media. The reasons for this phenomenon can be examined from two perspectives. Firstly, the findings suggest that scientific publications from the United States have received the most significant coverage in Iranian news media, which may indicate the dominance of translation in science journalism. In this manner, research findings from other countries, as reported by reputable news outlets such as CNN and BBC, are translated and published by Iranian science journalists. Additionally, the weak connection between universities and academics—who are the producers of scientific knowledge—and the news media results in a lack of awareness among science journalists regarding trends in domestic research.

Given that university-industry cooperation is associated with the transfer of knowledge and technology, one of the key indicators of a country's development is the effectiveness of collaboration between universities and industry. Due to the significance of this topic, the present article seeks to analyze the state of cooperation between Iranian universities and industry based on the co-publication of articles indexed in the Web of Science database from 2010 to 2022, particularly in terms of financial support. The findings of this research will inform national policymakers and planners about the current state of university-industry cooperation in Iran, enabling them to devise appropriate strategies to enhance this collaboration.

The research method employed in this study is both descriptive and quantitative, utilizing scientific techniques such as word co-occurrence analysis. The statistical population for this research comprises 2,891 articles. This study encompasses all articles that received financial support, focusing on the collaboration between universities and industry in Iran from 2010 to 2022; therefore, no sampling method was applied. Instead, a census sampling method was utilized. To examine the collaboration between universities and industry through scientific publications (articles), each article must include at least one author affiliated with an industrial organization and one author affiliated with an academic institution, both of whom must have a financial sponsor. Specific labels were used to identify the organizations involved. Data collection was conducted using the Web of Science database, and the data were analyzed and visualized using BibExcel and VOSviewer software.

According to the findings of the current research, the highest number of financial supports for cooperation between industries and universities in Iran was recorded in 2021, with 430 articles published. In contrast, the lowest number was recorded in 2010, with only 89 articles. On the international front, 78 countries have co-published with Iran, with the United States leading in the number of collaborative articles. Other countries that have engaged in significant cooperation with Iran include England, Canada, Australia, France, New Zealand, China, Germany, Italy, and Russia are other countries that have had a large number of cooperation cases in Iran. The data related to financial support institutions showed that the National Iranian Oil Company along its subsidiaries (9.79%); Iran National Petrochemical Company along its subsidiaries (4.74%); Support fund for researchers and technologists (4.08%); Islamic Azad University (3.22%); National Gas Company and its subsidiaries (3.18%); University of Tehran with (2.94%); and Tehran University of Medical Sciences (2.80%) have provided the most financial support. Out of a total of 251 subject areas of Web of Science, 151 areas have received financial support in cooperation between the university and the industry. Based on thematic analysis, chemical engineering fields (10.27%); environmental sciences and materials science (4.28%); energy and fuels (4.21%); and water resources (3.65%), are the most used topics in the articles.

The annual growth rate of articles receiving financial support indicates that the 13-year collaboration between universities and industry has experienced significant fluctuations, with some years witnessing a decline. Furthermore, the leading industries providing financial sponsorship include oil, petrochemicals, and gas. Most of these companies are supported by government organizations and are among the most profitable in the country. Consequently, a substantial portion of the investments in this collaboration is derived from the government budget. In terms of the subjects covered in the articles, the results reveal that, while the fields are diverse and extensive, there is a noticeable absence of certain topics, particularly in the humanities and social sciences.

The current research aims to comprehensively analyze the field of "resilience of start-up businesses" through co-citation analysis of authors and co-occurrence analysis of keywords, utilizing data from the Web of Science spanning the years 1995 to 2022. This study seeks to provide a foundation for future research in this area.

The current research employed a documentary method for data collection, while scientometric analysis was conducted using Vosviewer software to analyze the data.

This study examines the research trajectories of 876 articles across six areas: management, business, environmental studies, environmental sciences, green sustainable science and technology, and economics. These fields represent the most frequently explored topics related to resilience in the Web of Science database. A co-citation analysis of the documents cited in the context of "start-up business resilience" is presented. In this network, among the 28,298 cited references, authors with at least 30 citations were included, resulting in 46 articles represented as nodes. This review identifies three clusters: "resilience and global crises, "resilience and sustainability of the supply chain, and "resilience and economic effects. The first research path focuses on crises within the realm of resilience, highlighting that resilience is a crucial factor for start-up businesses operating under conditions of uncertainty and crisis.In the second area of research, most studies have focused on "supply chain resilience as a latent and path-dependent capability that cannot be measured directly. While few studies in the risk management literature have empirically distinguished between the concepts of resilience and sustainability, many suggest that supply chain connectivity and information-sharing resources contribute to enhanced resilience and sustainability within the business supply chain sector. The third path is related to research that addresses the key concept of "economic effects" in the resilience of start-up businesses. The construct of resilience in this context of entrepreneurship research has been used synonymously with preparedness, tenacity, persistence, or self-efficacy to explain why some entrepreneurs and their companies perform better than their non-resilient counterparts, and how the characteristics of cognitive entrepreneurship and distinctive forms of entrepreneurship, such as social entrepreneurs, They strengthen companies to adapt to new conditions and contribute to long-term sustainability through innovation. Also, 45 countries had international cooperation in this field in 7 clusters, among which the countries of America, England, and Australia have cooperated the most in producing documents in this field. In the Co-occurrence analysis of keywords, 5 clusters include: "Supply chain resilience with a view to the future" "Covid-19 crisis resilience and "economic vulnerability", "resilience success and sustainability factors", "resilience research and development", "infrastructure" Resilience" was determined. The first cluster includes skill, backgrounds, capabilities, conflicts, disruptions, system capability, company performance, future, effects, innovation, integration, knowledge management, logistics, organizations, supply chain management, supply chain resilience, technology, and uncertainty with the title: Supply chain resilience is introduced with a view to the future. The next cluster titled: "Covid-19 crisis resilience and economic vulnerability" includes keywords: start-up businesses, start-up business resilience, covid-19, crises, crisis management, crisis resilience, economic resilience, employment, companies, entrepreneurship, government, growth, knowledge, trend, epidemic disease, resilience, tourism, vulnerability. The third cluster also includes keywords: behavior, business continuity, social resilience, perception, performance, positive motivation, resource-oriented perspective, effectiveness, stress, success, sustainability, and progress, which is introduced as "resilience success and sustainability factors". The fourth cluster includes big data, design, disruption, resilience, framework, industry, management, mitigation, model, risk, strategic and supply chain, which is titled "resilience research and development", and the fifth cluster includes keywords: adaptation, capacity, Networks, risk management, dynamics, social investment, sustainability, transformation, trust, infrastructure. The title is: "Resilience Infrastructure".

The results indicate that scientific advancements in the field of resilience, prompted by the COVID-19 crisis and the necessity for electronic businesses, have led researchers to pursue a new research trajectory. The focus on artificial intelligence and resilience as emerging topics has garnered significant interest among scholars in this domain. Currently, a new wave of developments concerning the resilience of start-up businesses, influenced by artificial intelligence (AI), is impacting all sectors and has the potential to disrupt traditional strategies and operational models, thereby redefining resilience for the future. Consequently, identifying suitable platforms for research and the implementation of resilience globally, aided by scientometrics, can facilitate the adoption of effective measures that promote the growth and stability of businesses to the greatest extent possible.

In today's world, every society is struggling with the challenges of crime and its control. Committing a crime represents one of the most significant social harms, necessitating the involvement of police and judicial institutions for effective management. Assessing, evaluating, and identifying crime patterns, as well as detecting and preventing criminal activities, have been the focal points of judicial and law enforcement agencies since ancient times. Consequently, crime prevention is consistently prioritized over crime detection after it occurs. Various methods have been introduced for crime detection, including a wide range of innovative computer techniques. Data mining is regarded as one of the most effective tools for data and information analysis in the field of crime detection. Many effective parameters are available for analyzing crime through data mining methods. Data mining serves as a valuable tool for examining crime data warehouses, helping to extract hidden knowledge within them. The application of data mining techniques, along with various machine learning methods, can yield significant benefits in identifying, predicting, and preventing crime in any society. Diagnosing, predicting, and preventing crime through data mining represents a progressive approach supported by statistical methods, psychology, artificial intelligence, criminology, machine learning, and database technologies. Consequently, the primary objective of this research is to establish a framework for analyzing digital network data in the battle against social anomalies, particularly the crime of theft. In this research, materials related to the crime of theft have been categorized into three areas: crime identification, prediction, and prevention. Additionally, the application of data mining methods has been explored within these domains.

This research is applied in terms of its purpose and was conducted using documentary methods, content analysis, and data mining. The statistical population for this study consists of information related to theft crimes recorded by law enforcement and police organizations in 2019. Initially, the relevant data were collected in the form of documents and subsequently selected using the content analysis method to facilitate further analysis. Patterns of theft crimes were identified based on various factors, including the type of crime (such as home and car theft), entry location, entry method, search techniques, and residential area. This study utilized digital network data analysis tools and methods, specifically data mining, for classification and validation purposes. Additionally, clustering techniques, such as k-means, were employed to identify different forms of theft crimes. Classification algorithms, including neural networks, Bayesian rules, Bayesian navigation, and support vector machines, were used to predict theft crimes. The primary data analysis tool utilized in this research was Excel software.

The findings indicate that the season in which a theft occurs positively correlates with the month of the crime. Additionally, the method used to enter the crime scene shows a positive correlation with the method used to exit the scene. Furthermore, the accuracy of the Bayesian model in predicting and detecting the type of crime is 0.412. The model demonstrates the highest prediction accuracy for home thefts at 73%, while the lowest prediction accuracy for thefts from private locations is 27%. The results are expressed as a percentage. Additionally, the accuracy of each technique employed has been compared. The ROC findings indicate that the accuracy of the Bayesian methods and the Multilayer Perceptron (MLP) neural network, as well as the support vector machine, in predicting theft from public places is higher than for other types of theft. Conversely, in predicting home theft, these methods demonstrate lower accuracy compared to other thefts. Furthermore, the prediction accuracy of the support vector machine method, at approximately 91%, surpasses that of Bayesian methods (around 73%) and neural networks (about 90%) in predicting theft from public places. Moreover, the ROC chart for the support vector machine indicates that it is 7% less accurate in predicting pickpocketing compared to other thefts.

The results indicated that the Bayesian rules method is the most effective for detecting and predicting patterns of theft crimes. It demonstrates higher accuracy compared to other methods. Specifically, for predicting thefts from public places, the support vector method is recommended. As a result of the findings from data mining techniques, it is recommended that police and judicial organizations utilize a combination of data mining and artificial intelligence methods to enhance the detection and identification of thieves, particularly those with varying criminal histories related to theft. This approach aims to improve the accuracy of the information obtained about these individuals. Furthermore, based on the data mining techniques discussed in this research, an expert intelligent system can be developed to predict the likelihood of future criminal attempts by offenders.

One of the most important indicators of a country's development is its progress in scientific research across various fields and disciplines. Evaluating scientific output in different areas reveals the trajectory of scientific advancement within those fields. The analysis of co-occurring keywords and co-authorship, as key conceptual visualizations in scientometrics, is  widely used for mapping the network of scientific domains. Recent scientometric studies have extensively employed this approach to facilitate conceptual analysis. This study aimed to analyze and visualize the scientific landscape of Persian research in information technology (IT), as it is essential to understand the research profile of this significant scientific field. This analysis is based on articles indexed in the Iranian Science Citation Index (ISC) database over a decade, from 2010 to 2019.

Taking a bibliometric and scientometric approach, the present study is an applied research effort that utilizes both co-authorship and co-word analysis, along with social network analysis. This scientometric investigation identifies and analyzes key bibliometric features of research on information technology published in Persian journals. These features include, among others, highly productive authors, influential authors, the most cited and referenced papers, authorship patterns, authorship networks, author centralities, frequently used keywords, co-occurring keyword pairs, and subject clusters. The statistical population comprised 2,107 articles indexed in the field of information technology within the Iranian Science Citation Index (ISC). Data were extracted from nine specialized journals as the Persian sources that are well-known in the field and have been indexed in the ISC database. A keyword search for the phrase "IT" in the title field of the article search page yielded 287 articles. To analyze, visualize, and summarize the data, the software packages and "Excel" were utilized.

The results of the study indicated that the average number of authors per article among the papers was 2.61. "Hamid Hassanpour, with 20 published articles, and "Mohammad Javad Valdan Zoj, with 19 published articles, were the leading authors in terms of article count (considered highly productive authors). In contrast, "Abolfazl Shahabadi" and "Manouchehr Manteghi, with 49 and 40 citations respectively, were recognized as the most cited authors (considered highly influential authors) in the field of Information Technology (IT). The average number of citations per article was less than one, specifically 0.95. Articles on "Organizational Agility" and "Open Innovation" were identified as the most cited works in this domain. Additionally, the average number of sources cited per article was 29.8. The number of contributions that produced articles accounted for 42.5 percent of all publications. Of these articles, 39.7 percent were authored by three co-authors. The largest co-authorship network comprised 35 individual authors. "Mohammad Javad Valdan Zoj, "Sepehr Ghazi Nouri, and "Maghsoud Amiri" were the leading authors in the field of Information Technology (IT) based on their degree, betweenness, and closeness centralities, respectively. The keywords “Information and Communication Technology”, “Information Technology”, and "Knowledge Management" were the three most frequently used terms in this field. The most common pair of co-words among the author-assigned keywords was "knowledge management - information technology, followed by  - information and communication technology, - information technology, technology - education. Clusters in the field of IT were illustrated using 104 high-frequency keywords that appeared at least six times. The clusters included "Genetic Algorithm, "Knowledge-Based Development, "Research and Innovation, "Human Resources Productivity, "Higher Education, "Electronic Development, and "Knowledge Management. The network revealed eight main clusters, with the largest cluster containing 32 keywords and the smallest consisting of four keywords. These eight clusters were named as follows:  with 32 keywords,  with 16 keywords,  with 14 keywords,  with 12 keywords,  with 10 keywords,  with four keywords.

In conclusion, there is a pressing need to focus more on the production of articles related to specialized topics within the field of information technology for subject integration. Particular emphasis should be placed on the quality of the content in these articles, as well as the necessity for increased participation of women in the creation of articles in the information technology sector.

Today, researchers encounter challenges in scientific collaboration and the alignment of results with their peers. This study aims to evaluate the accuracy of identification and the extent of researchers' genuine participation in the convergence of multi-authored articles written by aerospace researchers, utilizing the three-dimensional Collaborative Author Writing Hierarchy (CAWH). Author associativity is a concept closely linked to scientific collaboration and multi-authored publications. The complexity of knowledge and the increasing demand for specialization and interdisciplinary skills have shaped scientific participation. Aerospace researchers and specialists are pivotal in conducting scientific and industrial research within the aerospace sector, focusing on technology development and providing support and guidance to fellow researchers. The aerospace industry is multi-faceted, strategic, and dynamic, possessing significant potential for wealth generation, economic development, enhancing national competitiveness on the global stage, job creation, and export opportunities. In various fields of study, numerous indicators have been established for observing, monitoring, and quantitatively and qualitatively evaluating researchers' publications, leading to the introduction of diverse metrics accordingly.

The research is applied in nature and employs an analytical approach. To assess the improvement in accurately identifying the author's true contributions in published articles, a composite measure that examines multiple dimensions has been utilized. The research outputs of aerospace researchers were analyzed, drawing on data categorized under "Engineering, Aerospace" in the Web of Science Core Collection (WOSCC). English-language articles published from 1945 to 2021 were extracted for this study. Data extraction was conducted on February 4, 2022, a Friday. The current research community encompasses all aerospace researchers from 1945 to 2021, comprising 153,994 records indexed in the Web of Science Core Collection (WOSCC). The total number of authors is 161,156, of whom 154,450 researchers with identifiable names (without sampling) were examined. The total number of citations is 2,617,712. Data extracted from the scientific website during the research period were analyzed. In this research, two tools, namely the "MiMFa Scraper, were employed to gather detailed information about each author. Additionally, another tool was utilized to match the gauge information with PHP (Hypertext Preprocessor). This tool is considered part of the DataLab software suite. Ravar PreMap software was also used to standardize the data. To normalize the data, the codes developed in the DataLab software were implemented. Excel 2016 was also utilized to extract data from various websites using PHP. The CAWH measure is defined as the average number of weighted citations based on co-author credit for a researcher.

The results of the H-weighted co-authorship index indicate "Florian Menter" (from ANSYS Germany GmbH), "Chae M. Rhie" (from Raytheon Technologies USA), "Philippe R. Spalart" (from Boeing), "Edward F. Crawley" (from Massachusetts (from the Institute of Technology (MIT)), "Irving Reed" (from university (from Southern California) are in rank fifth ranks of among based on the CAWH index. This measure was used to calculate the utilizing assessment of each author in writing a multi-author article.

The emphasis on recognizing researchers' contributions in article writing will be beneficial and effective for both researchers and the scientific community. Acknowledging researchers' involvement in writing allows them to showcase their contributions and achievements fairly and transparently. This approach enables researchers to properly receive their scientific credit and build their reputation, thereby gaining a competitive advantage within scientific communities. Within research teams, the implementation of this measure will enhance collaboration, facilitate the division of labor, and more equitably determine the rights and benefits of each team member. This approach fosters active collaboration and enhances the productivity of research teams. It enables research organizations and universities to conduct more accurate scientific evaluations of individuals and allocate resources based on equitable distribution and participation. Additionally, this method can improve transparency and build trust within research organizations. Consequently, it can help cultivate a culture of participation and cooperation within scientific communities. This approach can foster healthy, justice-oriented competition in science and enhance the quality of research. The evaluation offers readers and the scientific community detailed information about the authors and their collaborators involved in the research. This transparency enables readers to better assess the contributions and expertise of the article’s authors, thereby increasing their trust in the results and citations presented. Overall, acknowledging the participation of researchers in writing articles supports the scientific process and advances the field of science. This approach offers guidance for justice, transparency, cooperation, and the enhancement of research quality within scientific communities. It fosters an environment conducive to scientific development and progress, which can be assessed and refined using the index introduced in this study.