Social Network Analysis Methods Research Articles

Storying connectivity and value: the south west creative technology network’s cultural ecologies as network visualisations

ABSTRACT This paper explores the productive connectivity developed by university-industry knowledge exchange (KE) programmes for research and development (R&D) and their emergent cultural value. The South West Creative Technology Network (SWCTN) is our case study. We build on Dovey et al.'s. work to visualise the cultural ecology supported and created by cohort-led R&D programmes. Our visualisations, combined with interview data, evidence that new connections create diverse forms of value, including inspiration, mentoring, training, and recruitment opportunities, and cooperation through collaborative working. We supplement social network and visualisation tools with rich qualitative data to explore the “why,” “how” and “to what end” of new connections, contributing to the field of Mixed Methods in Social Network Analysis (MMSNA). This methodology is novel to the field of creative economy research. We argue for new forms of R&D funding for the creative sector to take a cultural ecology approach if we wish to take seriously and invest in the diverse forms of value beyond economic drivers, sometimes described as “intangible,” that play an important role in building regional capacity, innovation and productivity.

Green Development of Chinese Agriculture from the Perspective of Bidirectional Correlation

China’s agricultural green development exhibits spatial imbalances. To promote the coordinated green development of agriculture across various regions, this paper explores the evolution of spatial association networks and driving factors of agricultural green development from a bidirectional correlation perspective, using social network analysis and spatial econometric methods. This research indicates that China’s agricultural green efficiency has steadily improved, with a complex multi-threaded network structure. Although the spatial interaction and spillover effects of the overall network structure have increased, they remain relatively weak. The individual network structure shows significant regional imbalances. The spatial association network of agricultural green efficiency forms four major blocks, with sparse connections within the blocks but close connections between blocks, demonstrating strong spillover effects. Regarding the driving factors, the proportion of the primary industry, labor level, and R&D investment have significant spatial impacts, while the spatial impacts of human capital level, degree of openness, economic development level, and new quality productivity level are not significant. Therefore, we believe that it is necessary to establish the concept of coordinated green development in agriculture, fully leverage regional associations and spillover effects, and formulate differentiated policies to improve agricultural green efficiency.

Are farmer organizations effective intermediaries and facilitators of agricultural innovations processes? Evidence from Tunisia

Integration of productivity, resource management, and institutional innovations is crucial across different system levels. Traditional research and extension services face challenges in disseminating innovations effectively, leading to the emergence of the agricultural innovation system (AIS) approach. AIS involves collaboration among various stakeholders to improve the technological, managerial, and institutional aspects of agriculture. Intermediary actors play a pivotal role in facilitating innovation exchange and learning processes. In Tunisia, farmer organizations (FOs) such as Groupements de Développement Agricole (GDAs) and Sociétés Mutuelles de Services Agricoles (SMSAs) are key intermediaries. However, there is a lack of comprehensive assessments of FOs' innovation roles, which this study aims to address using the social network analysis (SNA) method. The findings aim to shed light on FOs' effectiveness as innovation intermediaries and identify potential challenges and benefits associated with their roles in innovation processes through the comparison of three farmers' groups divided by their membership status to detect the effect of FO presence or absence on innovation facilitation and actor's configuration. The studied sample involves 592 farmers from the Kef and Siliana governorates in northwestern Tunisia. The results show that FOs are playing a crucial role in facilitating collaboration and knowledge exchange among farmers and other agricultural actors. However, their effectiveness varies depending on membership status and is always contextually influenced. While FOs contribute to reshaping sales channels and optimizing access to services, they face limitations in promoting inclusivity and equitable knowledge sharing. The recommendations include strengthening FOs' social dimension, addressing trust barriers, and investing in reinforcement measures, especially in human capital, to enhance their functionality. Strengthening measures can take many forms, such as facilitating regulation and investing in capacity building. Long-term strategies should re-evaluate the effectiveness of collective action and focus on fostering a culture of shared learning and local empowerment.

Spatial spillover effects and correlation network analysis of green construction development efficiency in China

Green construction has been implemented globally to address resource depletion and environmental degradation. The effectiveness of green construction development depends on the efficiency of resource utilization and the common progress of all regions. However, existing studies have paid limited attention to green construction development efficiency (GCDE) and its spatial correlation. This study uses the super-efficiency slacks-based measure (Super-SBM) model, spatial econometric models, and social network analysis (SNA) method to reveal the spatial distribution, spatial spillover effects, and spatial correlation of GCDE across 30 provinces in China. The results indicate significant disparities in GCDE among regions, with the eastern region exhibiting considerably higher GCDE than the western and northeastern regions. There is evidence of spatial spillover effects, and the spatial correlation of GCDE is strengthening. Provinces with high GCDE occupy central positions in the GCDE network and exert spillover effects on other provinces, while underdeveloped provinces have opportunities to benefit from regional cooperation. The findings provide policy insights for the implementation and enhancement of green construction development actions. Moreover, they provide Chinese experience for green construction practices in other areas of the world.

Exploring Electric Vehicle Patent Trends through Technology Life Cycle and Social Network Analysis

In response to environmental and energy challenges, electric vehicles (EVs) have re-emerged as a viable alternative to internal combustion engines. However, existing research lacks a comprehensive analysis of the technology life cycle of EVs in both global and South Korean contexts and offers limited strategic guidance. This study introduces a novel approach to address these gaps by integrating the S-curve model with social network analysis (SNA), time series analysis, and core applicant layouts. The study specifically utilizes the logistic curve to model technology growth. It applies SNA methods, including International Patent Classification (IPC) co-occurrence analysis and the betweenness centrality metric, to identify the stages of technological development and sustainable research directions for EVs. By analyzing patent data from 2004 to 2023, the study reveals that EV technologies have reached the saturation phase globally and in South Korea, with South Korea maintaining a two-year technological advantage. The research identifies sustainable research directions, including fast charging technology and charging infrastructure, battery monitoring and management, and artificial intelligence (AI) applications. Additionally, the study also determined the sustainability of these research directions by examining the sustainability challenges faced by EVs. These insights offer a clear view of EV technology trends and future directions, guiding stakeholders.

Spatial correlation network and influencing factors analysis of supply efficiency of basic public service (SEBPS) in rust belt regions of China: An empirical study from Northeast China

Equalizing basic public service is crucial for achieving social fairness and justice. Promoting the improvement of public service can be achieved through the improvement of supply efficiency and cross-regional coordinated development. We employed the Super-SBM model, modified gravity model, and social network analysis method to empirically study the spatial correlation network characteristics of supply efficiency of basic public service (SEBPS) based on the data of 34 prefecture-level cities in the three provinces of Northeastern China from 2011 to 2020. The results revealed the overall efficiency of SEBPS in the study area is relatively low, and the supply efficiency is polarized. There is significant non-equilibrium between regions, and the regional difference moment gradually expands over time. There exists a strong spatial correlation between SEBPS in each city, and the overall correlation effect is weak but the network stability has improved. Each city had different roles and statuses in the spatial correlation network, creating a hierarchical structure. The level of geospatial proximity had a positive impact on the spatial correlation and spillover of the network. The level of economic development and infrastructure configuration hurt the network, and there is obvious heterogeneity between cities. The differences in industrial structure, opening up level, urbanization level, population density, the level of fiscal decentralization and technological innovation and personal income level among cities affected the SEBPS network. This study not only provides a new network research perspective and theoretical foundation for public service policies in China's rust belt region but also serves as a reference for urban development in similar regions.

Technical and financial interactions between Iran groundwater institutions: A stakeholder analysis approach

The over-exploitation of groundwater resources (GWR) by the agricultural sector in Lorestan province in the west of Iran has been blamed for the severe depletion of groundwater and irreparable damages to them in this province. This problem partially originates from poor institutional interactions between groundwater institutions especially, their technical and financial interactive links. In this regard, a prerequisite is to study the interactions of the institutions, identify stakeholder institutions, categorize them, and then, study their interactive links. The process of identifying, categorizing, and studying the links of these institutions can be performed by the stakeholder analysis (SA) method. Therefore, based on this method the groundwater institutions related to agricultural sector of Lorestan province were identified, they were categorized according to the interest-power matrix, and their (technical and financial) interactive links were investigated by the social network analysis (SNA) method. Based on the results, 25 institutions were identified as groundwater institutions related to agricultural sector of Lorestan province. According to the interest- power matrix, the institutions located in the two upper categories, i.e, Key Players and Subjects, are the most important groundwater institutions related to agricultural sector of this province. The SNA shows that the institutions have, in general, poor technical and financial interactions and most technical and financial interaction links are the disposal of some limited institutions, which are mostly from the public sector. Policymaking experts have so far identified institutions related to groundwater resources management (GWRM) by relying on their limited information and subjective experience. In this regard, SA method is a comprehensive method to identify relevant institutions, categorize them, and study their interaction links. This study might have significant policy implications for groundwater management concerns in western Iran and the arid and semi-arid regions of the Middle East. The results of this study not only helps policy makers in decisions related to GWRM but also in the analysis and policy-making related to it.

Analysis of the spatial association network structure of China’s green innovation efficiency

Improving the green innovation efficiency (GIE) is the main approach to high-quality development in China. Identifying the spatial distribution and influencing factors of GIE is conducive to sustainable and balanced regional development. In this research, the slack based measure-data envelopment analysis model (SBM-DEA) is used to measure the GIE of 30 provinces in China from 2013 to 2023. The gravity model and social network analysis methods are used to explore the spatial correlation of GIE in the provinces. The influencing factors of GIE are analyzed by the Tobit model. The results show that: (1) During the study period, the GIE of China’s provinces presented a high level, the spatial accumulation characteristics were obvious and the spatial correlation showed a complex network structure; (2) The association network is still in the primary stage, and the network strength and network association degree are low; (3) Provinces with strong innovation ability do not affect the green innovation of other provinces. In addition, these regions have obtained higher innovation linkage benefits from other provinces; (4) The amount of patent, education and government support have a significant positive impact on GIE, while total energy consumption and the secondary industry’s share of the gross domestic product have a significant negative impact on GIE. This study will reveal the characteristics of green innovation behavior of China from a new perspective, and provide a scientific basis for the formulation of green innovation behavior and related policies of China.

Mega Research Infrastructure as a Driver for High-quality Development and Innovation: Promoting Scientific Cooperation and Interdisciplinarity

Mega research infrastructures, as megaprojects, play a crucial role in promoting high-quality development, particularly in relation to innovation. They contribute to the development of disciplinary layouts and scientific collaborations. Additionally, during the operational phase of a infrastructure, maximizing efficiency and ensuring sustainable development become key aspects of project management. The operation of mega research infrastructures involves increasing levels of interdisciplinarity, interagency collaboration, and cross-regional cooperation. Therefore, it is essential to further clarify the characteristics of scientific collaboration within these facilities and understand the current status and evolving trends of disciplinary and collaborative networks. This work serves as a fundamental and necessary endeavor. In this study, we employ social network analysis methods to investigate the Shanghai Synchrotron Radiation Facility as a case study. We analyze the network structure and evolution of its collaborative and disciplinary networks from 2009 to 2022. The findings reveal the enormous potential and value of mega research infrastructures in promoting scientific research cooperation and development. They emphasize the need for increased attention and support for instrument scientists by facility managers, as well as the importance of expanding collaboration areas and formats to enrich the range of disciplines involved. The contribution of this study lies in its systematic analysis of the evolutionary process of collaborative and disciplinary networks within mega research infrastructures. It reveals the scientific value of these facilities in driving scientific research cooperation and interdisciplinary integration, providing a scientific basis for project management and policy formulation in the operational phase of mega research infrastructures. The research will align the strategic development direction of mega research infrastructures with the requirements of high-quality development and deepen the foundational role of mega research infrastructures in supporting high-quality development.

A social network approach to community energy initiative participation

This perspective paper argues how a social network approach can contribute to creating a more comprehensive picture of how individual and community characteristics influence participation in community energy initiatives (CEIs). We argue how social network theory and methods for social network analysis can be utilized to better understand participation. Further, we show how this can potentially aid the implementation of interventions aimed at attracting more participants with more diverse socio-demographic backgrounds. Importantly, we argue that the structure of community social networks connecting (potential) participants could importantly influence whether and how individual and community properties affect CEI participation. Our aim is conveying the social network approach to the field of community energy researchers and stakeholders who might not be familiar with it. We discuss empirical evidence on the effect of network characteristics on CEI participation and the connection between research on CEIs and adjacent fields as a foundation for our claims. We also illustrate how a social network approach might help to overcome biased participation and low participation numbers, by providing social scientists with a tool to give empirically grounded advice to CEIs. We conclude by looking at avenues for future research and discuss how the context of CEIs might yield new theoretical insights and hypotheses.

Analysis on the spatial correlation network and driving factors of carbon emissions in China's logistics industry

Promoting the green development of the logistics industry has become a focal point of attention in China. This study combines an improved gravity model and social network analysis method, focusing on the nineteen provinces of the Yangtze Economic Belt and Yellow River Basin. It constructs a spatial correlation network of carbon emissions in the logistics industry from 2010 to 2021, exploring its formation mechanism and spatial evolution characteristics. The study utilizes a quadratic assignment procedure model to investigate internal driving factors. Building upon this, the study employs an improved STIRPAT model to predict the emission reduction path of the future logistics industry. Results are as follows: (1) Carbon consumption is most pronounced in Shandong, Jiangsu, and Shanghai. The carbon emission shows the characteristics of larger downstream; (2) The bridges of carbon emission-related networks gradually shift from Shandong to Shanxi, Anhui, and Sichuan. Carbon emissions in each sector and spatial spillover effects exhibit dynamic correlations and interactive influences; (3) Energy intensity, freight volume, and the spatial correlation network of the logistics industry are highly correlated; (4) The overall carbon emissions from the logistics industry show a decreasing trend in the future. Anhui and Shaanxi provinces will have high carbon emissions in 2035. The conclusions aim to provide policy suggestions for the region's low-carbon transformation.

Análise de rede sociais de autores e instituições participantes nos anais do WIDAT 2017 a 2023 por coautoria e palavras-chave

The Information, Data and Technology Workshop (WIDaT), with its six editions from 2017 to 2023, published 210 articles in the proceedings with the participation of 395 authors linked to 80 institutions based in 46 cities and 7 countries. The objective of the research is to reveal affinity groups between authors and institutions participating in WIDaT. Qualitative research of an applied nature, used information visualization techniques with the support of social network analysis methods supported by software, such as: OpenRefine, Gephi and Looker Studio. The main result was the analysis of social networks of authors and institutions participating in the six events. The network of authors by co-authorship showed a giant component composed of the majority of authors, while the network of authors by keywords amplified the density of connections, making it a 'small world'. The network of co-authorship institutions revealed strong collaboration between institutions. The network of institutions using keywords identified seven clusters, complemented by keyword clouds, which revealed a semantic cohesion of the topics covered by the institutions belonging to each cluster. Observing the most common keywords for a given cluster can motivate approaches to research collaboration, both for those already consolidated and to strengthen the development of new investigations and studies.

Spatial correlation network structure of carbon emission reduction capacity on urban agglomerations and its driving factors: A perspective of Sustainable Development Goals

Sustainable Development Goal 7 and Goal 13 are important for evaluating carbon emission reduction capacity in urban agglomerations. Exploring the spatial correlation network structures of carbon emission reduction capacity can help synergize carbon reduction actions between cities. Existing research regarding the urban agglomerations to address carbon emission reduction goals has neglected both coordination with Sustainable Development Goals and the impact of spatial correlation network structures. Based on Sustainable Development Goals, an evaluation system of carbon emission reduction capacity is constructed. The characteristics of spatial correlation network structure for carbon emission reduction capacity are described using the social network analysis method. Its driving factors are described using the quadratic assignment procedure method. The Guanzhong Plain urban agglomeration in China is used for validation. The spatial distribution of carbon emission reduction capacity in urban agglomerations is significantly unbalanced, and the spatial correlation network structure follows a stable core-edge pattern. Factors such as differences in technological level, economic level affect the formation of the spatial correlation, but the differences in urbanization level have no significant impact. Countermeasures are proposed to provide a scientific basis for the collaborative management of carbon emission reduction in urban agglomerations.

Academic knowledge brokers in Iran’s health sector: Characteristics, skills, and qualifications

BACKGROUND: Knowledge brokers, as a bridge between producers and users of knowledge, need a set of skills and abilities to fulfill their role. The current study was carried out with the aim of identifying the characteristics, skills, and qualifications needed by knowledge brokers in Iran’s health sector. MATERIALS AND METHODS: This qualitative study was conducted through semi-structured interviews with 18 participants selected using social network analysis and snowball method from June to December 2022. All interviews were analyzed through the conventional content analysis method using the MAXQDA, version 20. RESULTS: Two main categories (personality traits and professional competencies) and six subcategories (extroversion, acceptability, problem-solving skills, interactive skills, specialized skills, and specialized knowledge) were identified for knowledge brokers in Iran’s health sector. Interpersonal communication skills, negotiation and persuasion skills, knowledge in both policymaking and research fields, and marketing and commercialization skills were defined as the most important factors in knowledge brokering. CONCLUSION: Identifying and training qualified and interested individuals to undertake the task of knowledge brokering, by taking into account the characteristics identified in this research and strengthening the required skills and qualifications, can increase the effectiveness of knowledge brokering and help to bridge the gap between research and policymaking.

DIGITAL MARKETING COMMUNICATION STRATEGIES OF COMPANIES TRADING ON SOCIAL MEDIA PLATFORMS

Contemporary trade companies operate within a multifaceted and rapidly changing environment that is shaped by both exogenous and endogenous factors, where digital marketing technologies play a special role. The purpose of the article is to identify the connection between digital marketing technologies and retail business sales regarding their use in marketing budget effectiveness. The study utilized the method of econometric analysis (regression analysis, analysis of descriptive statistics) as well as the method of social network analysis. Regression analysis showed the importance of investment in advertising and customization of marketing campaigns due to the cutting-edge technologies. Factors such as advertising budget, the number of posts, likes, and comments on social networks have a significant impact on sales. Based on the model's findings, every extra dollar allocated towards advertising amplifies sales by 0.0497 units, indicating the importance of investment in advertising campaigns. The sales distribution is somewhat skewed with a mean of 909 and a median of 922. The analysis revealed significant variability in key variables, indicating the diversity of strategies and conditions in which different companies operate. Practical digital marketing solutions for retail businesses include increased investment in social media advertising, regular posts, and engagement through likes and comments. The promising area for further research is to explore the potential of artificial intelligence for personalizing retail business marketing.

An Analysis of Policy Transmission Flow in the Chengdu Plain Urban Agglomeration in Southwest China: Towards Building an Ecological Protection Network

Regional ecological protection is an urgent task in today’s social development, and constructing an ecological protection network is an important way to achieve regional ecological coordination. However, previous studies have lacked a systematic review and analysis of policy document transmission paths, failing to consider the spatial network structure and its complex characteristics of regional ecological protection policies, resulting in deficiencies in regional coordinated governance of the ecological environment. To address this gap, this study constructs an ecological policy transmission network lineage for the Chengdu Plain urban agglomeration (CDPUA) based on 400 ecological environmental protection policy documents issued by cities in the CDPUA from 2015 to 2022, focusing on the transmission perspective of policy documents. Social network analysis methods, a GIS spatial analysis, and other methods were employed to construct the ecological protection network of the CDPUA and analyze the complex spatial structure and characteristics of the network. It was found that the integrated ecological protection network of the CDPUA exhibits a multi-core triangular pattern with spatial characteristics of density in the east and sparsity in the west. The integrated ecological protection network has a density of 60.71%, indicating a strong intercity linkage, with Suining as the central nucleus transmitting policies to surrounding cities, forming the Suining–Chengdu–Mianyang policy transmission triangle. The urban agglomeration has formed an ecological protection network dominated by multiple cities, offering diverse and distinct types of ecosystem services. This study provides insights to enhance regional collaborative ecological governance and protection, promoting sustainable development in the region.

The “Belt and Road” Initiative and China's sporting goods exports: Basic characteristics and policy evaluation

The paper analyzes the basic characteristics of China's sporting goods exports using data from the CEPII BACI database from 2007 to 2019, combined with the social network analysis method, and evaluates the policy effect of the “Belt and Road” initiative implementation on the impact of China's sporting goods exports using the difference-in-differences method. The research findings are as follows: 1) The overall scale of China's sporting goods exports has consistently expanded, marked by a rapid increase in the total export volume. The exported goods exhibit a comprehensive range of product categories, indicating an ongoing evolution in the structural composition of products. Geographically, the export destinations are widespread, covering a diverse range of countries. However, there is a noticeable concentration trend in sporting goods exports, with gymnastics and track and field equipment being the primary export commodities. These sporting goods predominantly penetrate markets in Southeast Asia, West Asia, and Eastern Europe. In the sporting goods trade network associated with the “Belt and Road” initiative, China holds a central role, with Thailand, Turkey, and Poland progressively advancing toward central positions. 2) The implementation of the “Belt and Road” initiative has had a positive impact on China's sporting goods exports, and the policy's influence is particularly significant on the countries and regions along the “Belt and Road”. The implementation of the policy does not favor the breathing growth of sporting goods exports, but it does promote the deepening of the export product. Based on these perspectives, it is imperative for China to establish a robust and sustainable trade network, proactively foster sporting diplomacy, maintain strategic focus, and enhance product quality to effectively propel the development of a sporting powerhouse.

Türkiye in International Energy Trade: Implementation of Social Network Analysis

Energy resources are fundamental inputs in almost every sector and play a crucial role in development and economic stability. This situation has increased the importance of keeping energy costs low, becoming a significant factor in attaining global superiority. In the contemporary era, where states represent the highest level of the organization, the strategic importance of these resources has been further exposed. The strategic value of energy resources, predominantly encompassing fossil fuels such as oil, natural gas, and coal, has precipitated intense global competition. The dynamics of energy resource trade have transcended mere profit-driven motives, transforming into a tool wielded by governments for various political objectives. This paradigm shifts underscores the vitality of energy supply security, prompting the formulation of energy trade networks guided by policies and national strategies. Within these networks, participating actors exhibit diverse traits shaped by distinct circumstances, assuming varied roles through pre-existing relationships. The purpose of the research is to examine the energy trade network of Türkiye, implementing the social network analysis method that integrates empirical data and mathematical approaches. The study aims to unveil pivotal aspects of the network, including its size within the global energy trade landscape, density, relational ties among actors, centrality, and brokerage degrees. The research aims to contribute valuable insights to understanding Türkiye's positioning in the global energy trade through these analyses. The results indicate that the volume of Türkiye's energy trade network accounts for around 1/3 of the global energy trade. While no single dominant actor exists in the network, specific entities demonstrate significant brokerage power. The analysis highlights the impact of global energy players, including Russia, the United States, and some European countries. Finally, the study involves recommendations for future research, anticipating a continued exploration of the complicated dynamics shaping energy trade networks on a global scale.

The global production pattern of the semiconductor industry: an empirical research based on trade network

Semiconductors are an important electronic component and play a central role in many industrial fields, whose production system is spread all over the world, involving trade in many raw materials, mechanical equipment, and finished products. Comprehending a broad global production picture of the semiconductor industry can be an arduous task. To tackle this complexity, the social network analysis method was used to capture the flows of products between economies in the semiconductor industrial chain. This study analyzed the evolution of the trade pattern of four key commodities in the semiconductor industrial chain, with a focus on identifying the status of major economies in the global semiconductor trade system. Additionally, the influencing factors of the formation of the trade networks were explored by using the Exponential Random Graph Model. The results showed that: (1) From 2001 to 2019, the import and export trade pattern of four key commodities in the semiconductor industrial chain has shown the characteristics of “rising in the east and decreasing in the west”, but the change range shows strong commodity heterogeneity, the change of the spatial pattern of integrated circuits trade is the most significant, and the integrated circuits trade proportion of Asian economies has increased hugely with more than 80%. (2) The trade connectivity of various commodities in the semiconductor industrial chain has increased, upstream support products with high technical requirements such as wafers and equipment have the lowest average degree and weak trade liquidity, and the average degree of trade network of packaging materials and integrated circuits is relatively high, with strong trade liquidity and closer and more prosperous trade connections. (3) From 2001 to 2019, the “core-periphery” system of global semiconductor industry trade has changed significantly, with the core circle undergoing obvious iterative reorganization. for example, China and Singapore have achieved status improvement to the core circle in the base materials trade network, while Malaysia has been squeezed into the semi-peripheral circle. (4) The formation of trade networks of various commodities in the semiconductor industrial chain was driven by three aspects: network self-organization, exogenous endowment attribute, and exogenous network embeddedness. Among them, the influence of the technological innovation level of economies on different commodity trade networks showed heterogeneous.

Evaluation of mine ecological environment based on fuzzy hierarchical analysis and grey relational degree

In order to improve the level of mine ecological environment management and restoration, and to improve and enhance the overall environmental quality of mines. This study takes coal mine as the perspective, and constructs evaluation indexes in two steps, i.e., social network analysis method and relevant policy documents are combined to construct evaluation indexes. The indicator system contains 5 first-level indicators and 23 s-level indicators, and the triangular fuzzy number hierarchical analysis method is introduced to determine the comprehensive weight of each evaluation indicator, which overcomes the inadequacy of the objective empowerment method or the subjective empowerment method of single empowerment. The grey correlation analysis theory is used to establish a grey correlation evaluation model of mine ecological environment, which is applied to the evaluation of ecological environmental protection level of four coal mines in a province of China, making full use of the information of each index for quantitative evaluation, and finally obtaining the evaluated value of ecological environmental protection level of each coal mine. It is demonstrated that the evaluation model can make scientific and effective evaluation of the level of ecological environmental protection in mines. The study concludes that coal mines should pay attention to improving the comprehensive utilization rate of coal gangue in the next mine ecological environment management and restoration, and at the same time, reduce the ton of coal power consumption, ton of coal water consumption, and Increase in vegetation cover. This study provides a useful evaluation method for ecological environment management in mining areas, which is helpful to improve the quality of ecological management in mining areas.