جستجوی مقالات مرتبط با کلیدواژه "تحلیل شبکه" در نشریات گروه "علوم انسانی"

The aim of this research was to analyze the spatial distribution of current libraries and the optimal distribution of libraries in the future in Rasht city.

In this research, the data of Rasht's existing libraries, statistical blocks of the 2015 census of the Rasht, and Rasht's spatial data were used in shape file format. This research was conducted based on the instructions of the Iran Public Libraries Foundation, 2017. Spatial statistics analysis has been used to investigate the spatial distribution of existing libraries and network analysis has also been used to determine the service range of libraries. Finally, VIKOR decision-making model was used to prioritize future service areas.

The values ​​of the tests show the significance of cluster distribution of libraries in Rasht city, which indicates heterogeneous distribution based on population or distance from population centers. In fact, the distribution of libraries in Rasht is not suitable and they are mostly concentrated in the city center. There are few libraries in the south, west and north of Rasht city. Based on the criteria of distance and population for existing libraries, 4 service areas were determined (due to the proximity of some libraries to each other, their service areas were merged with each other). Considering the population of Rasht city, there is 14,991 square meters lack of library infrastructure to reach the access standard in this city. The existing libraries cover only 163,633 people (equivalent to 24.2%) of Rasht’s population, and with the development of about 3500 square meters of library space at the available libraries, 32.4% of Rasht's population will be covered by library services. By conducting network analysis and applying distance and population filters, twenty future service areas in Rasht city were proposed to cover the population of Rasht city in the most equitable way. These twenty areas will cover 442,575 people of the population of Rasht city, which includes 65.3% of the population of Rasht, and if they are realized and the infrastructure level of the current libraries is increased, a total of 661,943 people (97.7%) of the population of Rasht city will be covered by public libraries services. In determining the priority of the future service areas, the population is more important than the distance, and respectively, the areas with the largest population in the south, west, north and northeast of Rasht city are in the first six priorities for the construction of new libraries, and marginal areas in the north of Rasht is the last priority due to its lower population and proximity to existing libraries. 2.3% of the population of Rasht, including 15,322 people do not have the necessary population and distance criteria, and currently it is not possible to propose the establishment of a new library for them, who are mainly located in the south of Rasht city.

Originality/value: 

Conducting land use planning researches is the basis of future planning. Lack of this type of studies and lack of foresight will lead to waste of resources and duplication in different projects. According to the basic criteria, this research has determined the amount of library infrastructure based on the population, the amount needed to increase the infrastructure of existing libraries and also the number and area of ​​new libraries in order to cover the needs of the population of Rasht city. By doing it, libraries can be expanded in principle in Rasht and new libraries can be established at the right areas of the city.

Considering the critical importance of the response time of fire stations in reaching the incident scene and the necessity of examining the spatial distribution of these centers to identify areas lacking standard coverage, the main objective is to determine the spatial-temporal distribution of fire stations in Neyshabur and to designate uncovered areas so that the areas requiring the construction of these centers can be identified as a result.

The method is descriptive-analytical, and data collection was done through library and field sources. The data used in this study includes road data, fire stations, and the boundary of Neyshabur. Subsequently, the spatial-temporal distribution of fire stations along the roads was analyzed using the Network Analysis Extension in ArcGIS 10.8 software.

Research results indicate that the spatial-temporal distribution of fire stations in Neyshabur shows that reaching the incident location within the standard time (4 minutes) is only satisfactory in the city center. However, the western, northern, northwestern, southern, and southwestern outskirts of the city, covered by these centers, are not within the standard time range.

Approximately 25 square kilometers of the city's outskirts are within the inaccessible range of fire stations, while 14 square kilometers from the city center are within the accessible range. Therefore, the priority of constructing new fire stations on the outskirts of the city is well highlighted. It can be concluded that following the horizontal expansion of the city, establishing essential land-uses is of great importance.

Innovation:

 Spatial distribution analysis of fire stations using a Geographic Information System and assessing the accessibility level to the incident site considering constraints. The findings can assist urban managers in the study area in identifying and establishing more numerous and logical fire stations.

In this study, considering the characteristics of complex networks such as dynamics and comprehensiveness in analyzing the behaviors of countries, the global network of foreign investment inflows consisting of 248 countries and trade territories in the years 2009 to 2022 was constructed, and network indicators including degree, closeness centrality, betweenness centrality, PageRank, hub, and authority were calculated. Then, the functional position of the top-performing countries based on the intensity and level of the obtained network indicators was analyzed and compared annually. The results obtained during the study period showed improvement in the degree, betweenness, and PageRank indices, which respectively indicate the number and diversity of communications, the share of information control among countries, and countries' efforts to use the influence of neighbors to reach polar and influential countries. The effect of increasing closeness centrality, which indicates the level of independence, on the main countries in the effective network has improved. Therefore, it is recommended that if countries seek to increase foreign direct investment inflows, they should plan in such a way that their network indicators, resulting from increased interactions and communications, are improved.

Recently, network analysis has become one of the most popular and practical areas in data science. This technology, by analyzing complex data and identifying communicative patterns among different elements, delves into a deeper understanding of the structure, behavior, and interactions within networks and complex systems. Despite the critical importance of network analysis in data science and social research, particularly in the field of human resources, there remains a lack of comprehensive studies on this topic. In particular, domestic market data have not been fully studied and discussed. This lack of attention misses opportunities for deeper understanding and presenting innovative solutions to future challenges. Therefore, researchers need to employ modern approaches to investigate the challenges in this field and propose new solutions. This study introduces an innovative model that utilizes multimodal network analysis to enhance the understanding of labor market communications and predict its future developments.

To design the proposed network, the required primary data were collected from international classifications and the initial network was drawn based on them. Then, to ensure that the network matches the current labor market conditions, data from one of the domestic job search websites were also extracted and the network was updated accordingly. The Jaccard index was employed to quantify the connections between network elements, while the algorithms of preferential attachment, Adamic-Adar, and common neighbors were utilized for network validation. The Dijkstra algorithm was used to calculate the shortest path in the network and the term frequency-inverse document frequency metric was used for ranking.

This research sought to present a new method for designing a multimodal labor market network and described how it was updated and diversified to match the dynamic changes of the labor market. With the final network obtained, the connections between labor market elements (jobs and skills) were examined, and a method for quantifying these connections was presented. Additionally, a method for calculating the most efficient job transitions within this network was outlined, along with an approach for ranking skills according to various job levels. Finally, the network was validated with three link prediction algorithms. The results indicate that the use of the preferential attachment algorithm will be the best option for predicting the future of this network.

The innovative model presented in this research offers a powerful tool for network design and analysis in understanding the labor market. It not only provides a comprehensive overview of the current and future state of the domestic labor market but also offers practical solutions for addressing future challenges. In particular, discovering communicative patterns and predicting emerging trends enables better and faster adaptation to labor market changes, which in turn leads to the development of sustainable job opportunities and economic growth. Through a deep analysis of existing data and predicting potential developments, this model can help labor market managers, policymakers, and social analysts design more effective strategies to enhance labor market capacities and optimize human resources. Ultimately, the results demonstrated that innovative models based on network analysis can open new horizons for predicting and managing future developments.

The pervasive use of technology among children and adolescents has made issues related to their digital life a new public concern. This issue has engaged various stakeholders including parents, educators, child rights advocates, technology companies, and policymakers. Each of these stakeholders has its own perspectives and concerns about cyberspace and how to govern it. This study aims at identifying the main stakeholders in the cyberspace policy for children and adolescents as well as to identify the uncertainties that affect policymaking in this area. To this end, the content of 356,210 tweets in the 8 months leading up to August 2023 was analyzed using content analysis and social network analysis methods. The results show that there are 5 main stakeholder groups in cyberspace for children and adolescents: parents, educators, child rights advocates, technology companies, and policymakers. These stakeholders engage in dialogue with each other on 6 main topics: access to educational resources, global communication, creativity and self-expression, digital literacy and skills, cyberbullying and harassment, privacy risks, and digital addiction and mental health. This study identified three pairs of influential policy uncertainties, each of which was favored by one or more stakeholder groups: the uncertainty of global governance advocates versus local governance advocates, the uncertainty of open access to information advocates versus information security advocates, and the uncertainty of free market advocates versus government intervention advocates. The diversity of stakeholders and their views on cyberspace is a major challenge for policymakers. Policymakers must seek ways to balance the interests and concerns of different stakeholders while taking this diversity into account.

The main stream of researches that tried to explain the unfavorable situation of sociology in Iran have pointed to the weakness of scientific communication between researchers and in one word, the weakness of the scientific community as the main factor of the unfavorable situation of sociology in Iran. While these researches have completely ignored one of the most frequent scientific communications among researchers in this field, i.e. the links formed through participation in the refereeing teams of theses. The current research has sought to describe and explain the network of links of these arbitration teams. For this purpose, the dissertations presented in the sociology departments of Tehran, Tarbiat Modares, Allameh Tabatabai, Shahid Beheshti and Alzahra universities from  the year  2001  to 2016 and the information related to the background of the members of the judging teams of these dissertations were collected. For data analysis in order to describe and explain the network the software R was used. The findings of this research shows that the communication structure of arbitration teams is centralist, and this centralism are partly explained by some background characteristics of the network members, including the workplace university, the workplace department, and the university where the doctoral degree is obtained, as well as some scientific factors including specialized field of research, the subject of theses and also the diversity of these .

The research objective is to know the political geography of cyber forces in Persian Twitter and measure their influence in the discussion network during the Corona virus. The question of the research is: Is the fake news published by cyber forces effective during the Corona period and has it been highlighted on Persian Twitter? In this regard, more than four million tweets have been extracted and analyzed and interpreted. By identifying cyber forces in 11 clusters and analyzing their network, the prominent presence and influence of cyber and fake forces in the clusters: monarchists, fundamentalists, the MKO, Irfan-Halkha, the cluster of supporters of Imam Mahdi, and the cluster of the oppositions were determined. The results show one of fundamentalist clusters that with the presence of 80% of cyber forces, it is generally identified as fake and the other cluster is in a critical situation with the presence of more than 40% of these forces. In sum, according to the findings of this research and according to the network centrality indicators, cyber and fake forces have penetrated to the depth and core of each cluster in almost all clusters, and we are facing a public domain infected with fake cyber forces in Persian Twitter.

Forest fire in many ecosystems is a natural phenomenon, but also a serious and dangerous threat with environmental, ecological, and physical effects. Therefore, this research investigated the risk areas of fire in Zagros forests identification to evaluate the changes in the time series of deals with a potential fire hazard. To achieve this goal fuzzy layers of analysis network process and order weighted average method were used regularly. For this purpose, fire Zagros forests using satellite images Landsat and MODIS Lordegan city in the period between 2000, 2007, and 2014 and the factors affecting fire are examined. The high-risk areas based on classification utility area and the number of zones were identified as fire-prone areas. In the analytical network process procedure, the largest weighs were assigned to the distance from residential areas and roads, GVMI index, and maximum daily air temperature factors which were 0.209, 0.198, 0.09, and 0.0716, respectively. Time series analysis map showing the extent of critical areas from 2000 to 2014 decreased by investigating the factors affecting fire occurrence in critical areas, distance for roads and residential areas, slope, aspect, GVMI index, and NDVI and maximum temperatures have the greatest impact were on fire. The low-risk scenario and a small amount of compensation with the ROC higher than 0.7 as the best model was the estimated risk of forest fires. The preparation of a map of areas susceptible to fire, as well as analyzing and analyzing the time series of factors affecting the fire in different years, is an effective step in helping forest managers to plan and implement preventive operations in high-risk areas.

Tourism destinations as a spatial phenomenon are an important part of the tourism system and the product of the interaction between natural-ecological and human-cultural factors. Therefore, in order to effectively use the capabilities and capacities of tourism for the sustainable development of tourism, regulating the flows Space in the form of relationships and connections is essential for the optimal spatial organization of destinations. In this regard, the analysis of the spatial organization of rural tourism destinations with the approach of network analysis and based on the attraction model was chosen as the goal of this study. The research method in this article is quantitative (descriptiveanalytical). The statistical population of the research is 73 villages of Shabstar city, which were fully investigated. The main data of the research (attractions of villages, amenities-infrastructure, and distance between villages) were collected by documentary method (referring to Cultural Heritage Department and Iran Statistics Center) and field. To analyze the distances between villages, the network analysis method in Geographical Information System (GIS) was used, and social network analysis and ucinet software were used to construct the proximity matrix with the aim of calculating the centrality analysis indicators of the rural tourism destinations of Shabstar city. The results showed that the spatial organization of Shabestar city has many centers with the spatial role of tourism. This feature has caused the spatial pattern of tourist destinations to follow the multicentered pattern. In this pattern, the villages of Nazarlu, Dizj Khalil and Amir Zikri are the most important villages with centers. As tourist destinations. Also, from the methodological aspect, the network analysis approach has good capacities for analyzing the spatial network, especially tourist destinations, so that the application of this model along with other models such as attraction, analysis of characteristics and distances of tourist destinations In a combined form, it shows a suitable potential for analyzing similar issues in research.

New cities, which have been established for about three decades in Iran, are now facing various problems, one of these problems is access to urban public services in these cities. In the present research, which was carried out by descriptive-analytical method and using library and field data, access to urban public services in 7 districts of the new city of Sahand was analyzed in connection with its road network. In the present research, using The method of network analysis, the levels of access to urban public services in the new city of Sahand, were investigated and the result of the work, in the form of separate maps, for 9 types of urban public service users, first in the form of access radius maps and then by integrating the maps It was prepared in the form of weighted access radius maps. In the end, by combining the maps produced in the previous stages, the final map of integrated access to urban public services was presented. . By using the network analysis method, access to urban public services was evaluated in the form of 9 users. The results showed that among the uses of urban public services, the new city of Sahand in terms of the desirability of access are: educational, commercial, urban equipment, administrative-administrative, religious, medical, park and green space, sports and cultural. The radius of access to educational and commercial use is in a more favorable condition than the rest of the use; While sports and cultural uses are in a weaker situation in this regard; The reason for that is the spatial distribution and the number of these uses. Also, the results of the map of integrated access to urban public services showed that only 45% of the entire city is covered by good and very good services, and these levels often include middle and older areas and inequality in access to services. A city is evident in the new city of Sahand. Therefore, considering the high population of the new city of Sahand and the important role of this city in attracting the population of the mother city of Tabriz, it requires planning and special attention to the creation and design of various functions of urban public services, especially in areas with poor and very poor access levels.

Worn-out textures are parts of the city that have not been developed compared to other textures and we have witnessed residents abandoning them. In this regard, the present research has aimed at recreating worn-out textures, while examining the state of damage to have an analysis of the current situation of Saqqez city, in order to determine the mental model of experts for re-creation and provide practical suggestions. The present research method was descriptive-analytical which used the JHA model to check and identify damage caused by worn-out textures and used the Q factor to analyze the mentality of experts to extract the best mental model of recreation and finally used network analysis in GIS to explain how to do it from the desired pattern. It is necessary to explain that the sample of this research was 15 people which have been selected in a purposeful way. Research findings have shown that 50% were at an unacceptable level of 16 potential hazards from worn-out urban textures in Saqqez which shows the necessity of regeneration. In this regard, the results of the analysis of the experts' mentality have shown three mental models (First commercialization, second: integrated management and urban unit, third: Supervision and control of construction) to recreate and the first model is the most important. Findings show that Center 5 has the best position by connecting with 149 population points and covering 3504 people within 10 minutes by identifying 7 prone points in worn-out areas and four competing centers to implement the commercialization model from worn-out textures in Saqqez.

One of the primary concerns of the Iranian National Pension Fund is managing its investment portfolio. In this respect, the present study aimed to examine the long-term investment portfolio, the largest subset of which is V-sandoq. The analysis used the R2 connectedness approach proposed by Naeem et al. (2023) over the period from September 17, 2013, to September 22, 2023. The study focused on the immediate influence and susceptibility to influence of the stocks within the National Pension Fund. The results showed that, in terms of net influence and susceptibility, the stocks of Group 1 (i.e., Kechad, Foulad, Kegol, and Sheranol) were the most influential, transferring risk to the network. Conversely, the stocks of Group 2 (i.e., Shepas, Pasa, Shekabir, and Vebshahr) were the most influenced by the network. Therefore, risk is transferred from Group 1 stocks to the network, impacting Group 2 stocks the most. In network analysis, during a bear market with a threshold of -4%, there is a high degree of connectivity among the stocks in the portfolio. This suggests that portfolio adjustments are necessary under bear market conditions. Conversely, in a bull market with a threshold of +4%, there is no connectivity between the stocks, indicating that no portfolio adjustments are needed under such conditions.

Today, we are witnessing the widespread use of artificial intelligence in various fields of marketing. For example, Prime Air Amzon.com uses drones to automate transportation. Domino's Pizza is experimenting with self-driving cars and delivery robots to deliver pizzas to customers' doorsteps. Lexus uses IBM Watson to script its "Intuition Drive" TV commercials. Based on emotional analysis, affective detects the emotions of consumers while watching advertisements. Replica is a chatbot based on machine learning that provides emotional comfort to customers by imitating their communication styles. It has even been claimed that artificial intelligence will fundamentally change the future of marketing. However, academic marketing research to date has not provided sufficient guidance on how best to leverage the benefits of AI for marketing impact. Artificial intelligence systems and programs have become widespread in different industries and different sectors of companies and organizations and have led to close competition between them and have also provided various opportunities for marketing strategy and process. However, research on the application of artificial intelligence in marketing planning has been scattered, and there is a need for a comprehensive research on the past research trend and the future trend of this issue. The current study aims to identify the antecedents and consequences of the application of artificial intelligence in the develop a marketing plan.

This study was conducted with a mixed approach, in the quantitative section by using bibliometric network analysis of existing research background published between 2010 and 2022 and in the qualitative section by using the meta synthesis strategy. A comprehensive review of 115 articles indexed in the Scopus database helped to identify the performance of scientific actors such as the most appropriate authors and the most appropriate sources. In addition, co-authorship and co-occurrence analysis using VOSviewer software suggested a conceptual and rational network. By applying the meta synthesis method to investigate the dimensions of the marketing plan based on artificial intelligence, 59 articles out of 115 indexed articles were analyzed.

According to the results, only one paper was published in 1985 in the field of "Artificial Intelligence and Marketing". Until 2010, when this issue has been gradually noticed by researchers, and the trend of publishing articles from 2010 to 2022 had an upward trend. In 2021, 50 articles have been published, and in 2022, 21 articles have been published until today. Most of the articles related to artificial intelligence and marketing have been published in the Australian Journal of Marketing. To understand the most effective source, 5 of the most suitable sources were compared in terms of H index and SJR index. Journal of Business Research in terms of H index and Journal of Marketing Science Academy in terms of SJR index have the most points and are the most suitable sources. "Liu Wai" won the highest rank among all researchers with 3 articles published in the field of artificial intelligence and marketing. "Liu Wei" has an H-index of 8 and 16 published articles, while "Huang" has an H-index of 75 and 328 published articles, which has more citation records than the rest of the authors. Among the analyzed articles, the highest percentage of studies related to the product/consumer factor (38%) and the lowest The percentage of studies conducted is related to the price/cost factor (14%). Based on the results of the meta synthesis study, it is possible to use mechanical artificial intelligence for standardization, intellectual artificial intelligence for personalization, and emotional artificial intelligence for relationalization. Based on the results, the antecedents of the use of artificial intelligence in developing a marketing plan include technological, organizational, environmental, behavioral and individual factors and the consequences include customer experience, customer journey management, profitability, competitive advantage, customer satisfaction, customer loyalty, customer relationship management and customer engagement.4. Discussion and coclusion: The research findings of the review of all scientific sources conducted from 2010 to 2022 show that so far no comprehensive research has been done for the integration of the Rabazi program stage. Therefore, the most important finding of this research is the review, analysis and classification of the planning phase of artificial intelligence based on metacombination. In this research, 59 articles that directly examined the issue of marketing planning based on artificial intelligence were selected for analysis. The selected studies were coded and finally, 152 distinct primary codes were identified. In the next step, the codes were categorized in the form of 35 concepts or sub-categories, and finally, based on the results of the analysis, concepts in 4 main categories as dimensions of the evaluation program based on artificial intelligence, 5 main categories as antecedents of the evaluation program based on The basis of artificial intelligence and 7 main categories were identified as suffixes of the marketing program based on artificial intelligence, and their quality test was also confirmed. Finally, based on the analysis, a model for the use of artificial intelligence in developing a marketing plan is proposed, which consists of the three dimensions of artificial intelligence, mechanical, intellectual, and emotional, and their benefits include standardization, personalization, and relationship building. It uses marketing mix dimensions.

The present study investigated the impact of the position of audit institutions on the accounting information quality. In a way, this research tried to evaluate these variables from the aspect of relationship structure and network.

In this research, the network analysis method was used in order to examine the pattern of the relationship structure of audit institutions and their place and position in this structure, as well as multivariate regression was used to test the hypotheses. The statistical population of this research is all the companies in the capital market of Iran and all the audit institutes that audited them during the years 2012-2022. The statistical sample includes 135 audit institutes (stage 1) and 124 companies (stage 2).

The findings of the research showed that in the communication network of the institutions, some of them are in a better position and have more access and influence. A better location can lead to easier and faster access to information and resources. Also, the results of the hypothesis test indicate that there is no significant relationship between the closeness centrality and the accounting information quality; however, there is a significant negative relationship between the degree centrality and the accounting information quality, and there is a significant positive relationship between the betweenness centrality and the eigenvector and the accounting information quality.

The results of this research indicate the existence of an unequal structure in the network of audit institutions and the influence of the position and position of audit institutions in this structure on the accounting information quality of companies.

Contribution: 

The study highlight the role and importance of relationship structure and can be an important factor in the decision-making process of all stakeholders in the market.

no society is independent of the pathology. Special conditions of Iranian society in terms of density and diversity of social problems on the one hand and the need to the political institution for problem-oriented research with the aim of increasing efficiency, on the other hand, necessitate such a thing. Identifying the focal problems and measuring their relationship with each other is the main goal of this research; for this purpose, the network analysis method was used using cross-impact analysis techniques and multi-criteria cluster technique. The tool used for data analysis is Gephi software. The sources of identification of social problems in the present study are 650 academic and organizational research documents prepared on the topic. Identification, clarification and classification of problems have been done by the focus group. The results of the research show that disorders related to governance, injustices, poverty, various types of extremism and educational problems are the most important influencing variables and on the opposite point; The dimming of the discourse of the Islamic Revolution, the loss of social capital, the disruption of social cohesion and the weakening of the family institution are the most effective variables in the network of social problems.

The aim of the current research was to identify the complications in the process of the comprehensive system of tourism education in Iran in the field of entrepreneurship. This research is applied in terms of purpose and qualitative-quantitative in terms of method, based on semi-structured interviews with experts involved in the supply and demand system of tourism education and the technique of social network analysis. In the qualitative part, the statistical community of organizations involved in the tourism education supply and demand cluster included 238 organizations. In qualitative results, according to two clusters of supply and demand - supply with 160 and demand with 78 units - based on Cochran's formula, interviews were conducted with experts of 177 organizations using random sampling. Then, the aforementioned interviews were coded and entered into the process of analyzing social networks in the form of scrutinized problems. In the quantitative part, social network analysis method and Gephi software have been used. In this software, existing relationships between actors are set based on input matrices and network analysis indicators, the existing situation and the most important actors have been extracted according to the test of the average degree of input and output. The results have shown that the Ministry of Cultural Heritage, Tourism and Handicrafts and universities active in tourism have the highest number of problems from the side of other actors. This actors have been the most influential actors of the network. Also, the Ministry of Heritage, the Foundation of the Underprivileged, and the tour guide community, with a high degree of output, have more power in the network. Diagnosing the current state gives the experts the opportunity to identify the most important problems and actors, clarify the scope of duties of each organization and use its capacities to improve the system.

In land use planning, justice in the distribution is considered one of the basic indicators in sustainable urban development. One of the most important land uses in cities is educational use, the necessity of which is not hidden from anyone, However, its position in the Islamic city becomes doubly important, because in Islamic attitude and with the recommendation of the Quran to think, research in the world of creation, the creating scientific centers in Islamic societies has been emphasized. this research evaluates educational uses (primary schools) and their distribution status among the 10 districts of Tabriz, and then re-locates educational spaces by interpreting the indicators. The study at hand is practical and the research method is descriptive-analytical research. In this research, first, the nearest neighborhood (RN) method has been used to show the distribution of primary schools in Tabriz then The network analysis method in GIS has been used to analyze the current situation of the spatial distribution of schools and to check the radius of their performance and finally, the TOPSIS model was used to evaluate the three criteria so that the evaluation unit of the criteria is unified. The results of this research show that regions 6, 8 and 10 are ranked highest and region 7 is ranked last and only region 8 is covered by 100% of the useful performance radius and in terms of the distribution pattern of schools, region 6 has a regular pattern. And in terms of per capita, none of the regions have a satisfactory situation.

Human thought in the field of crisis management is focused on preventing, preparing for, and dealing with crises in various areas such as organizational crises and natural disasters. However, accessing information on crisis management and related areas can be challenging due to the interdisciplinary nature of the concept of crisis, and there are differing opinions on this matter. One of the most critical and essential tasks of crisis management is to take measures, within the framework of urban management, to eliminate the problems caused by natural disasters, reduce their adverse effects, and prepare for relief and the improvement of the situation. Considering the significance of crisis management worldwide and the need to mitigate its impact, it is crucial to regularly analyze and advance crisis research. This will ensure that research in this field progresses with accuracy and relevance. Therefore, the objective of this study is to identify research topics in the field of crisis and risk management using the Scopus database from 1973 to 2020.

The present research is a scientometric study that utilizes content analysis techniques, specifically co-word analysis and network analysis. The research community encompasses all documents in the field of crisis and risk management from the inception to 2020 in the Scopus database. In this research, the documentary method was used to collect data. First, the relevant keywords were identified, and the search was conducted using Boolean operators and truncation techniques. Finally, on November 7, 2021, 2,330 documents were retrieved and entered into Excel software. Using Bibexcel software, the names of organizations, countries, and keywords were extracted and analyzed. Centrality indices, such as closeness centrality, betweenness centrality, and degree centrality, were analyzed using Gephi software. Additionally, a vocabulary co-occurrence network was created using VOSviewer software.

According to the increasing trend of scientific publications in the field of crisis and risk management, there has been a rise in the production of works. The highest number of publications was recorded in the year 2020, with 222 documents. Most of the documents in terms of the type of work are research articles, and the majority of the published documents are in English. The United States, with 467 documents, Runciman, W.B. The author with 15 documents and the social science field with 694 documents were the most active in terms of country, author, and field. The topics of crisis management and risk can be categorized into five clusters of issues. The first cluster focuses on risk management and disasters caused by crises. The second cluster addresses crises, vulnerability, and disaster management during crisis situations. The third cluster examines the assessment of potential risks. The fourth cluster explores risk factors and interventions in crisis occurrence, as well as training individuals to prevent such accidents. The fifth cluster discusses post-accident management, healthcare, and providing relief to victims. The vocabulary co-occurrence network also shows that the keywords "crisis management," "risk management," and "risk assessment" have a degree centrality of 196, 194, and 192, respectively. The keywords "risk management," "vulnerability," and "water management" have an equal value of 1 and the highest value of closeness centrality. The keywords "human," "risk management," and "risk assessment" have the highest value of betweenness centrality, with values of 8.653, 491, and 3.398, respectively. These three nodes have the shortest path connecting them to other pairs of nodes, indicating that they have more influence and occupy a vital position in the network.

  The key to crisis management lies in proper planning and the implementation of continuous structured processes that are designed before a crisis occurs in order to fully equip and prepare. Crisis management is a process that involves evaluating crisis signals and taking necessary measures before, during, and after the crisis to effectively overcome it and minimize the resulting damage. Conducting research in this field is one of the practical methods that can assist countries in crisis control and management. The results of previous research in the field of crisis management and natural hazards indicate that the majority of studies focus on crisis management, risk management, and human health. This highlights the significance of global research on human health during accidents. However, despite this, Iran, known as one of the accident-prone countries, has a low level of scientific output and limited international collaboration in this area. Policymakers and crisis management planners in countries can take a significant step towards identifying the principles of crisis prevention and mitigating the resulting damages by prioritizing the crisis issue and conducting further research on the identified hot issues in the present study.

Today, with the advancement of communication technologies, particularly the Internet, we are witnessing the generation of a vast amount of information. In academic research, it is crucial to identify the most frequently studied topics and challenges in each field, as well as to determine their significance. One way to evaluate scientific research in any field is by analyzing its scientific map. One of the most effective methods for visualizing and analyzing a scientific map is to utilize network analysis approaches. This technique can effectively demonstrate the structure of scientific networks. 

In this study, we visualized and analyzed the scientific network of articles published in the journal "Research in School and Virtual Learning" using network and co-word analysis methods. A total of 227 articles were included in the analysis. The general research approach includes collecting and cleaning data, constructing matrices of scientific networks, and analyzing and evaluating the results. Various scientific networks of articles, including the co-authorship network, co-organization network, semantic network of articles, and co-occurrence network of words, have been analyzed. PHP language was used for data crawling and processing, while Python language and Gephi software were utilized for network-based analysis and visualization of different networks. In addition, a proposed approach based on the TF-IDF method has been used to calculate the adjacency matrices of each network. This approach includes ten steps. 1) Integrating the title, keywords, and abstract of each article. 

The findings reveal the extent of semantic connection among the published articles in the semantic network. In order to plot and analyze the semantic network of articles, the semantic matrix is obtained by multiplying the word-article matrix with the article-word matrix. The final semantic graph was clustered using the Grivan-Newman algorithm. The top six communities were evaluated based on various metrics. Also, the results showed that there are few articles with high and low degrees, and they are mostly located in the middle of the distribution chart. Therefore, the semantic network of the articles can be classified as a free scale type. The results of the co-occurrence analysis of words show that satisfaction, psychology, and emotion have been addressed more frequently than other topics. The result of the co-authorship network analysis showed that it has a degree of 2.881. Each author has contributed to the writing of the article with three other authors. The average clustering coefficient of the authors in the co-authored network was 0.685. The network exhibited a compactness value of 0.936 and consisted of 83 communities. Additionally, the results showed that the majority of articles were written collaboratively by three authors, followed by four and five authors. The largest component of the co-authorship network of articles was also extracted. Also, the individual network of the top authors in the co-authorship network was drawn and analyzed up to a depth of 3. Personal networks describe a person's relationships in the network with other authors. The structural characteristics of individual networks determine many aspects of a person's cooperative behavior, including the willingness to cooperate and share resources. The analysis of the intra-university collaboration network showed that the researchers of Payam-e-Noor University had the highest number of intra-university collaborations, with 42 articles. After that, Islamic Azad University ranks next with 23 articles. The analysis of the co-university cooperation network showed that each educational institution has participated in the publication of articles with at least three other educational institutions. 

Upon analyzing the word count, it is evident that the topics published in the journal exhibit a wide range of topic distribution. Also, the investigation of the authors' co-authorship network and its clustering showed that the authors of the articles were more inclined to form small scientific groups within their respective organizations, such as universities or research institutes. Also, Payam-e-Noor and Islamic Azad universities have the largest number of co-authored articles within the university. The co-authorship network of Payam-e-Noor University exhibits an interesting and significant structure, indicating a higher willingness to cooperate among university members compared to independent groups. While the authors at Azad University are more inclined to conduct research as independent groups.

Among the goals of managers is to maximize the wealth of shareholders and reduce the capital cost. In this regard, deciding on the capital structure is one of the most important strategies to achieve these goals. Since, Board of directors is one of the main decision-making groups in in this field. Therefore, the relationships that can be seen in the form of a social network between the board members of different companies, the purpose of this study is to examine the capital cost and the capital structure in the relations network of the board of directors of companies in the Iranian stock market and is based on data related to 115 companies in the period 2012-2020. Network analysis and regression analysis were used to conduct research tests. Findings showed that in the communication network of companies, some of them are in a better position and have more access and effectiveness. Better location can lead to easier access to information and resources faster. Also, the results of testing the hypotheses showed that there is no significant relationship between the betweenness centrality, and the capital cost and the capital structure. But there is a significant negative relationship between the closeness centrality, and the capital cost and capital structure, and a significant positive relationship between the degree centrality and the capital cost and the capital structure. In other words, it can be said that the position in the structure of relationships can somehow affect the capital cost of companies and their capital structure.