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

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 .

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.

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.

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.

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.

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.

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.

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.

Obviously, timely and reliable services by these centers will require their proper space arrangement and optimal routing of relief and emergency services between the location of the emergency base to the accident site and the accident site to the hospital location. In the present research, selecting the city As a case study, Sanandaj has tried to provide a suitable model for the spatial organization of emergency aid centers in the city, while exploiting network analysis capabilities in the ArcGIS environment. In this regard, the first step is to prepare and process data and layers of information used in the network analysis process such as the length of the path, the speed of the path, one-way and bi-directional paths, non-intersecting intersections, and the location of the databases Emergency at the city level, in the ArcGIS environment, and after the creation of the corresponding Dataset, they were loaded in the framework of the network analysis model as an applicable model and displayed in the ArcGIS environment. According to the results of the research, factors such as the presence of traffic areas, the lack of relief centers, as well as the lack of location of the existing relief centers, make the operation of emergency centers in the service. In the field of activity, it is accompanied by weaknesses. In the implementation of the research, while presenting a representative pattern of suitable routes and determining the preferred bases for dispatching relief units to the accident site in the shortest possible time period, the areas outside the optimal performance radius of emergency sites are identified and given the optimal situations For the establishment of emergency units, in order to cover the relief services, they were identified at specified time limits.

Digitalization affects many organizational strategies of a company, including the development of market opportunities, and is known as an element that strengthens the internationalization of small and medium-sized enterprises. However, the use of digital technologies requires investment and changes in the internal procedures of a company through the mobilization of new resources based on digitalization and the use of special capabilities for their management. Research on the impact of digitalization on the export maturity of SMEs is scattered and there is a need for a comprehensive research on the past research trend and the future trend of this topic. This study is a bibliometric analysis using Vosviewer software, with the aim of reviewing published scientific products and drawing a scientific map in the field of digitization and export maturity of small and medium companies, which investigated this field using 240 articles indexed between 1984 and 2022. To conduct this study, co-authorship analysis, co-citation analysis and co-occurrence analysis were used for network analysis. In the end, according to the analyzes carried out, five main topic clusters were identified, which include organizational resources based on digitalization, organizational capabilities based on digitalization, dimensions of export maturity, export and internationalization, and sustainable development; According to the trend of the articles, we can expect the field of sustainable development to attract more attention in the coming years.

The aim of this study was to analyze the dispersion and evaluate the level of access to sports uses based on data from Tehran

The method of the present research was applied and was descriptive-analytical in terms of monitoring variables and data analysis. ARC GIS software was used for data analysis. Evaluation of distribution and distribution of sports spaces was done in two ways: network analysis method based on access to sports spaces and focal spatial statistics analysis method based on the size of sports spaces

All results showed that District 10 to 86 percent, the highest level of sport's coverage area and then the 6, 14, 8 and 3 respectively with 84, 80, 79, and 77 percent in the next category were located. Regions 21 and 22 were not well distributed despite high per capita sports area with minimum coverage level of service sports space. After this, regions 18, 5 and 4, respectively 35, 43 and 57 percent of the least important loss of service. In the region of 21 only 43 percent of the residential land use sports spaces located in the service area. And then 22 and 5 least favorite areas in the distribution of its sports spaces. Regions 8 with 96% and District 10 to 99% have the highest proportion of residential land use in the coverage of sports spaces.

According to the results of this study, having a high per capita sport does not necessarily require more use and more access. In fact, the main sports facilities in Tehran are located in areas where the opportunity to visit them is relatively small.

The stock market, as a prominent financial domain, presents a formidable challenge in comprehending and evaluating an extensive array of stocks employing centrality measurements to portray the key variables within a network, companies' stocks can be visualized and comprehended. The utilization of stock network analysis facilitates a comprehensive understanding of the entire network through diverse visualization techniques. This study delves into the data of the top 50 companies listed on the Tehran Securities Exchange during the period from January 1, 2019, to July 6, 2021. Employing unsupervised machine learning tools such as Community Detection algorithms and network analysis methods like Louvain and Girvan-Newman, we construct a stock network. Subsequently, we compute five Centrality Metrics, including Degree Centrality, Closeness Centrality, Eigen Centrality, Betweenness Centrality, and PageRank, for these companies. By formulating a similarity matrix based on these criteria for the remaining stocks in the network, we determine a portfolio of 25 stocks suitable for investment, derived from the ranking of stocks according to the Centrality Metrics

The present study is a combination of documentary and survey methods in terms of applied purpose. Documentary and field methods have been used to collect the required information and data. Also, according to the purpose of the research, among the households of selected villages, 352 households have been determined as a sample using Cochran's formula. In particular, in this study, using Gephi and GIS spatial analysis software and network analysis methods, the flows and relationships mentioned in the study area have been analyzed in order to form a regional network based on links. And to integrate integrated rural-urban development. The results show that there is a direct correlation between flows and the level of development of rural settlements to form a regional channel. Spatial flows, especially economic flow, and population, have provided the background for urban-rural interactions in the study area, and in the first level network hierarchy, all cities and rural centers are subordinated to the Hanza urban center with the highest score in providing services. In fact, the lack of spatial development planning to regulate the relations and connections, and consequently the lack of attention to the role of the surrounding villages of Hanza, has caused us to not be able to direct the currents and factors that shape and influence these connections which pave the way for the development of the whole system.

Changing the direction of monetary policy from targeting the monetary aggregates to targeting reference rates, the interbank market interest rate is considered as one of the most significant operational objectives of the Central Banks. Identifying the interbank market is important as it enables the monetary policymakers to achieve more in following their goals with limited intervention. Due to the completion of the initial stages of the formation of interbank market and the establishment of Open Market Operations (OMOs) mechanism as well as the provision of standing facilities in the Iranian money market, the analysis of interbank market network with the aim of identifying the core of this market increases the effectiveness of the implemented policies. According to this, the formation mechanism of the interbank market was examined using graph theory and network analysis techniques as well as the transactions performed during the twelve-month period from March 21, 2018 to March 20, 2019. The findings show that it is challenging for the market to identify a core with fixed members owing to direct communication between the members and the frequent changes of the core members; nonetheless, it was possible to identify the members that played the biggest role. This, along with other factors such as health and financial stability index, can be used by the CBI as a useful criterion for identifying primary dealers in monetary operations.

Financial markets are considered to be a kind of complex network due to the interaction and interrelationship of its various actors. Therefore, the development of stock communication networks is an important issue for discovering potential connections between different companies. Therefore, the purpose of this research is to investigate and analyze the communication structure of companies in the capital market based on price, return, and trading volume of stock with a network approach.
 
This study employs a quantitative research methodology, specifically focusing on network analysis. The data were collected in the period between 2017 and 2021 and analyzed using the network analysis method and with the help of Excel 2021, SPSS 26, UCINET 6, and its complementary package NetDraw. In addition to the general analysis and review of the price, returns, and trading volume of the stock correlation network, the performance of each node in the network was also investigated using micro-indices. Centrality is one of the most important micro-concepts of network analysis, which examines the influence and importance of people in the network. Also, it was studied with three indices of degree, betweenness, and closeness of centrality of network nodes.
 
The results indicated that as the correlation basis expands, there is a decrease in communication between different companies along with an increase in irregularity. The higher the correlation basis, the less likely it is to be affected by a common variable or interaction, which will reduce the correlation between stocks. In addition, there are companies in the communicative network that are in a better position than the rest. They may have higher connections, faster access to information, and greater influence over other units' price changes. As a result, these companies can play a decisive and leading role, or in other words, the role of key and influential actors in the governing structure. Also, the results showed that in the second period of 2021 compared to the first period, communication networks were much more erratic and scattered.
 
Considering the importance of capital market communication networks and the decisive role of key companies, relationship pattern analysis helps to increase transparency, reduce risk, and, consequently, improve decision-making, policy-making, portfolio optimization, etc by revealing the network structure of the capital market. The results of this research can lead to a better understanding of the forces that create the communication structure of companies and enable policymakers to make better decisions. Therefore, all users are suggested to pay attention to the communication structure governing the companies in the capital market and the role and impact of their position on the advancement of the company's goals in their decisions and to consider this communication structure and the way power is distributed.