Social Network Analysis Methods Research Articles

Research on Chengdu-Chongqing Urban Agglomeration and Guangdong-Hong Kong-Macao Greater Bay Area Innovation Network Structure

Under the background of factor-driven to innovation-driven, urban innovation is very important in the regional development pattern.In this paper, Chengdu-Chongqing urban agglomeration and Guangdong-Hong Kong-Macao Greater Bay Area are taken as the research objects. Based on the co-authored data of papers among cities, a theoretical knowledge innovation network is constructed.With the help of social network analysis method, the overall characteristics and network centrality are compared and analyzed, thus revealing the development status of Chengdu-Chongqing urban agglomeration and Guangdong-Hong Kong-Macao Greater Bay Area knowledge innovation network.The empirical research shows that: (1) During the research period, the overall density and agglomeration capacity of Guangdong-Hong Kong-Macao Greater Bay Area theoretical knowledge innovation cooperation network are higher than those of Chengdu-Chongqing urban agglomeration. (2) Dual-core cities Chongqing, Chengdu, Guangzhou and Shenzhen have significant innovation polarization effects.

Research on Adaptive Reuse Strategy of Industrial Heritage Based on the Method of Social Network

With the deceleration of urban expansion, the adaptive reuse of industrial heritage buildings has emerged as a novel area of research. In previous times, the majority of approaches to adapting industrial heritage buildings relied on experiential knowledge, which lacked the ability to objectively assess the relationship between spaces and engage in rational planning. However, the social network analysis method offers an objective and comprehensive means of perceiving the spatial structure and analyzing its issues from a detached perspective. This study presents a proposal for addressing three spatial challenges encountered during the conversion of industrial heritage buildings into public buildings. It also suggests spatial optimization strategies to overcome these challenges. The Sanlinqiao Thermal Bottle Factory is selected as the research subject, and a spatial network structure model is constructed to analyze the existing issues using the social network analysis method. The proposed spatial optimization strategies are then applied, and the optimized space is evaluated through a re-analysis of the spatial layout. The spatial utilization rate has been significantly improved, leading to an effective enhancement of the spatial vitality of the site. This study presents a spatial strategy aimed at converting industrial heritage buildings into public buildings, thereby offering valuable insights for similar projects involving the transformation of industrial heritage sites.

Research on the green innovation effect of digital economy network – Empirical evidence from the manufacturing industry in the Yangtze River Delta

The digital economy is open and borderless, and the development of an urban digital economy forms an associated network. Based on the social network theory, the digital economic association network formed between cities can enable manufacturing enterprises to obtain heterogeneous resources, stabilize the network relationship between nodes, and improve innovation performance. The digital economy's spatial correlation network drives the manufacturing industry's green innovation to improve quality and efficiency. Through the integration of external relations, green innovation, proximity, regional innovation system, and other dimensions of the theory, this study takes 41 prefecture level cities in the Yangtze River Delta from 2006 to 2021 as samples to construct the digital economy correlation network of urban agglomerations and uses the social network analysis method (SNA) to reveal the evolution law of the digital economy correlation networks. We establish the panel fixed effect model to explore the green innovation effect of digital economy networks. The results show that the Yangtze River Delta urban agglomeration constitutes a spatial correlation network of the digital economy, promotes the sharing and exchange of manufacturing resources through factor linkage, and produces a green innovation effect. The network centrality and relationship strength have a significant inverted U-shaped relationship with the green innovation of the manufacturing industry. There is a significant U-shaped relationship between structural holes and the green innovation of the manufacturing industry. Accordingly, we should further improve the design of digital economy development and promote the development of the manufacturing industry.

Assessment of network structure characteristics and factors of corporate flows in Guangdong Province.

With the rapid development of the world city network, the traditional location theory has gradually been disproven, and the advantages of the flow space over the traditional vertical organizational structure are gradually being revealed. Therefore, from corporate branch networks and corporate investment networks, 21 cities in urban agglomerations of Guangdong are taken as case studies for this paper. Furthermore, in this paper, 5 representative types of corporate contact data (catering service, financial service, life service, sports and leisure and accommodation service) are selected, the social network analysis (SNA) method is used to quantitatively analyze the network structure characteristics of urban agglomerations, and a spatial interaction model is constructed to explore the factors influencing. The results indicate that secondary networks have developed in Guangdong. The financial service network is the most complex, followed by the life services, sports and leisure and catering networks. The accommodation service network structure is the simplest. Among all kinds of networks, Guangzhou and Shenzhen have the highest status. The catering and accommodation corporations in Yangjiang in the west have a relatively major external development. Shantou in the east has many branches of various types, while most of the capital exchange in the region is concentrated in Heyuan and Qingyuan in the north. The coefficients of geographical proximity and the urban development level play a significant role in promoting the development of networks. However, administrative capacity limits the attractiveness of origin cities to a certain extent.

A data envelopment analysis model for opinion leaders’ identification in social networks

Through Online Social Networks (OSNs) such as Instagram, X (Twitter), and Facebook, employing Opinion Leaders (OLs) is becoming integral to companies’ strategies for influencing the public. The graph-based methods are one of the most important approaches for finding OLs in OSNs. Social Network Analysis (SNA)-based OLs finding methods deal with a considerable amount of data due to using entire relationships between all of the users in a network, which makes the algorithms time-consuming. Our main goal is to introduce a new method of OLs discovery that works with fewer data and maintains or improves performance metrics. Consequently, a new application of the Data Envelopment Analysis (DEA) method is presented here for OLs identification in social media. Another contribution of this paper is introducing a new framework (OL-Finder Evaluator or OLFE) for validating the OLs’ detection algorithms under imbalanced datasets. DEA methods, when compared with SNA methods, have the advantage of being able to apply over non-graph-based datasets and to work with substantially smaller datasets. In contrast, SNA methods require transparent relationships between people. In this study, we compare both DEA (including CCR and BCC) and SNA measures (including “Betweenness (BC),” “Degree (DC),” “Page Rank (PRC),” “Closeness (CC),” and “Eigenvector (EC)” centralities) on a real Instagram network for OLs detection. Compared with SNA, our proposed method can identify OLs with considerably fewer data. Besides the advantages of DEA for time-saving, close competition exists between the DEA and the SNA methods. On average, DEA performs better in accuracy, precision, recall, and F1-score performance metrics.

An in-depth analysis of green innovation efficiency: New evidence based on club convergence and spatial correlation network

Green innovation is the cornerstone of global economic transformation. Based on the green innovation efficiency calculated under the two-stage innovation process, this paper discusses its convergence and network structure characteristics by applying the club convergence model and social network analysis method. The quadratic assignment procedure approach is employed to analyze the influencing factors. The results reveal that: (1) this paper finds β convergence but not convergence within subgroups based on regional classification. (2) Regarding network correction characteristics, the correlation ties and network density of the green innovation efficiency network demonstrate a downward trend, while the network hierarchy characteristics are still apparent. (3) The regional green innovation efficiency cluster performs different roles, as the core provinces become the beneficiaries of green innovation resources. (4) The differences in regional development and the clustering of block models are unfavorable to the formation of green innovation efficiency networks, while the differences in geographical proximity, green finance, resource environmental carrying capacity, and green innovation R&D efficiency foster the development of the spatial network. This paper contributes to promoting coordinated regional green innovation efficiency development.

Spatial correlation network characteristics and influencing factors of water environmental efficiency in three major urban agglomerations in the Yangtze River Basin, China

Within the framework of achieving carbon peak and neutrality, studying the measurement and spatial correlation network of water environmental efficiency (WEE) is beneficial for protecting the water environment and strengthening the coordinated development between regions. This study quantifies WEE under carbon emission constraints in three major urban agglomerations in the Yangtze River Basin. Employing a modified gravity model paired with social network analysis (SNA) method, we establish a spatial correlation network. Furthermore, we explore the determinants of the spatial correlation network using Quadratic Assignment Procedure (QAP) model. The research findings indicate that: (1) WEE exhibits fluctuations and increases, illustrating a trend of 'high on both sides and low in the middle.' (2) The spatial connection of WEE is tightening, demonstrating significant spatial spillover effects. Compared to Chengdu-Chongqing and the Midstream, the Yangtze River Delta has transitioned from a 'dual-core' setup to a multicentric network, which is more stable and showcases tighter interconnections. (3) Urbanization, population density, industrial transformation, and technological innovation emerge as the primary influencing factors of the spatial correlation network, displaying both temporal and regional heterogeneity. This study provides a theoretical framework and empirical support for water environmental protection and offers insights for policy-making towards green sustainable development.

Mapping the intellectual structure and evolution of information technology and auditing: a bibliometric review

Purpose- The goal of this study is to conduct a bibliometric analysis of papers relevant to information technology (IT) and auditing that were published in the Web of Science Core Collection database between 1978 and 2022. Methodology- This study does a bibliometric analysis of 2991 audit and information technology publications from a pool of 7738. It works in two steps: descriptive performance metrics and co-word analysis. The descriptive metrics include publishing patterns, productive nations and authors, effect on certain areas and journals, number of citations by country, and publications with the highest citations. The co-occurrence analysis maps the ties between concepts by utilizing social network analysis methods to investigate the field's interconnections. Findings- This study identifies six major trends in IT and auditing: increased technology use in internal auditing, the demand for information security expertise, transparency in the digital age, technology for ethical auditing, cloud-based auditing with blockchain, and post-COVID IT continuous auditing standards. These trends highlight the need for auditors to adapt to evolving technology and ethical considerations, prioritizing data security and privacy. Additionally, the survey reveals key authors, publications, and countries in this field, offering valuable insights for industry leaders and potential research collaborations. Conclusion- This study provides a complete overview of the topic of IT and auditing by integrating several methodological techniques. This study provides direction for future research in addition to offering significant insight into the main research trends, issues, and problems in this subject. Keywords: Information technology, auditing, co-occurrence analysis, bibliometric analysis. JEL Codes: M41, M42

The Spatial Structure and Influencing Factors of the Tourism Economic Network in the Yangtze River Delta Urban Agglomeration

The optimization of a tourism economic network is critical in the promotion of the high-quality development of a regional tourism economy. In order to explore the spatial network structure of the tourism economy of the Yangtze River Delta urban agglomeration and its influencing factors, this study used a modified gravity model and social network analysis methods for evaluation and analysis. The results show the following: (1) the spatial network of the tourism economy in the Yangtze River Delta urban agglomeration in 2016–2021 was characterized by significant non-equilibrium; however, that trend has weakened, and the tourism connections are now stronger in economically developed regions. (2) The density of the network structure was slightly strengthened. The structure of the tourism economy network shows an obvious core–periphery distribution pattern. The external radiation of the center city was enhanced, and the core area of the network expanded. (3) The concept of the “small world” is characterized by a significant evolution from five major associations to four major associations during the study period. (4) The quadratic assignment method (QAP) of regression analysis showed that tourism service reception capacity, tourism information flow, tourism resource endowments and transportation convenience make a significant contribution to the formation of the spatial network of inter-city tourism economic connections. The results of this study can provide a theoretical basis for the optimization of the tourism economic network of urban agglomerations and the scientific decision-making underpinning tourism economic cooperation.

Biased innovation and network evolution: digital driver for green innovation of manufacturing in China

ABSTRACT The study aims to explore the spatial association network characteristics of biased green innovation in the manufacturing sector and its core drivers. This study constructs a Malmquist-Luenberger decomposition index model to identify the input and output biases of green technological innovation (GIIM and GIOM) in the manufacturing industry. This study uses a modified gravity model and social network analysis method to conduct a robust assessment of GIIM spatial association network of 30 provinces in China from 2012 to 2021. The results show: (1) The GIIM association network structure is stable and has good accessibility, with close connections between provinces and blocks, and significant spillover effects between provinces. (2) The regional network shows a “core-periphery” spatial variation, with the core area expanding and the peripheral area shrinking. (3) The digital transformation characteristics of the network components and the intensity of environmental regulation have a significant impact on GIIM.

Bibliometric Analysis on the Distributed Decision, Decentralized Decision, and Fuzzy Logic

This study aims to survey the bibliometric properties of distributed decisions, decentralized decisions, and fuzzy articles published between 1995 and 2023 in the Web of Science (WoS) database. During the analysis process, the keywords “distributed decision, decentralized decision, and fuzzy” were scanned in all languages, both in the titles and the content of all publication types. As a result of the analysis, 79 articles in all fields comprised the dataset. The most used keywords in the articles were related to the distributed decision, decentralized decision, and fuzzy logic, and the most frequently cited publications were examined using the social network analysis method, which uses VOSviewer (version 1.6.19) to visualize the relationships. The study’s goal on “active researchers, active journals, journal metrics, title document type, active countries, and active institutions” was to look at the words most frequently used in articles on distributed, decentralized, and fuzzy logic. The social network analysis represented the relationships between these keywords and the most frequently cited publications. The findings demonstrated a significant correlation between using these keywords in academic literature and their contribution to this field’s research. These results can assist researchers in finding potential partners and keeping up with current research trends. Overall, this study offers important new perspectives on the state of research on fuzzy logic, distributed decision making, and decentralized decision making.

Research on the Public Environment Renewal of Traditional Villages Based on the Social Network Analysis Method

Constructing digital models of public spaces of social networks found in traditional villages helps us explore the logic behind the interactions that occur within various relationships as well as achieve the optimization of spatial layouts and the equalization of the different use needs that social groups have. However, this analytical method has not been fully studied in the field focusing on the rationality of public spaces in traditional villages. This paper takes the traditional village protection demonstration area in Mentougou District, Beijing, China, as the object of research and selects three different forms of traditional villages to be analyzed. It tries to excavate the universal laws and unique differences in the models of the different forms of traditional villages and establish models for quantitative research, such as index calculation, so as to increase the depth and accuracy of research and embody the characteristic laws of the spaces studied in terms of the nature of the structures and relationships that are part of these spaces. The results show that the spatial characteristics of the different forms of traditional villages are obviously different from the relevance, equalization, and connectivity of spatial networks. The cluster form of traditional villages tends to focus on the villagers’ use demands and the assessment of the spatial status quo by increasing the number of spatial nodes and transforming spatial functions in order to achieve higher equalization. The dispersed form of traditional villages tends to focus on optimizing the relevance of spatial network structures. The linear form of traditional villages tends to establish public spaces so as to increase the depth and accuracy of research. Villages ought to establish direct links between public spaces in order to increase the connectivity of traditional villages. This study provides a rational basis for the differentiated planning decisions of traditional villages and lays the foundation for the promotion of the smooth and sustainable development of regional villages.

Social Network Analysis of Ant Group

Through constructing animal social network structures based on the relationships between individual ants of two groups of ants, this essay utilizes social network analysis methods to compare the degree of concentration and utilization power on resource and information of these two groups.

Topological analysis, endogenous mechanisms, and supply risk propagation in the polycrystalline silicon trade dependency network

High-purity polycrystalline silicon, as a core raw material in the photovoltaic industry, has a trade structure whose robustness affects the supply security of the entire photovoltaic industry. Using social network analysis methods and dependence indicators, this study constructs a Polycrystalline Silicon Trade Dependency Network (PSTDN) from 1995 to 2019, and performs descriptive statistical analysis and trade community divisions on the network. The Temporal Exponential Random Graph Model (TERGM) is used to explore the factors influencing the formation of trade dependencies. Based on the cascading failure model, a Photovoltaic Multilayer Network Supply Risk Propagation Model (PMNSRPM) is constructed to study the risk propagation process of polycrystalline silicon supply interruption as a raw material in the photovoltaic industry. Finally, using the risk propagation range and dependency degree, the study measures the importance of nations comparatively. The results show that (1) the PSTDN exhibits reciprocity, geographical clustering, and weak network convergence; (2) the evolution of the PSTDN's community has gone through three stages: the rising expansion phase from 1995 to 2007, the crisis recession phase from 2008 to 2010, and the competitive contraction phase from 2010 to 2019; (3) the evolution of the PSTDN shows strong reciprocity effects, transitive effects, stabilization effects, and lag effects as endogenous mechanisms; (4) the average risk propagation range is continuously increasing along the supply chain, while there is no significant difference in the risk propagation rate along the supply chain. The risk propagation rate of different risk sources shows a long-tail effect, with the risk propagation rate of leading countries like the United States and China growing rapidly over time. The United States can infect China, but China cannot infect the United States and Western Europe; (5) The risk propagation range and the dependency degree present a positive correlation ranging between 0.5 and 0.7, which is not as highly positive as initially anticipated, and the correlation between them shows a downward trend. This study explores the statistical characteristics of the PSTDN, community evolution, and evolutionary factors, demonstrates the importance of polycrystalline silicon supply security for the production of the photovoltaic industry, quantifies the risk propagation capabilities of different countries, and identifies a group of countries that actually have a high risk propagation range but tend to be underestimated due to their low dependency degree in normal trade network. This can help enhance the early warning capabilities for photovoltaic supply security risks of various countries.

Research on Cooperation Mode and Evolution Analysis of Huawei Company based on Patent Collaboration Network

Patents, as a vital tool in open innovation, play a significant role in enabling enterprises to access and utilize external resources, thereby enhancing their competitive advantage. This paper uses Huawei as a case study, employing patent metrics and social network analysis methods to examine the evolution characteristics and attributes of Huawei’s collaboration network. The analysis, based on authorized patent data from the Incopat database, explores Huawei’s collaboration mode. This study aims to provide insights and guidance for Chinese enterprises in the development and management of their patent collaboration networks. The findings reveal that Huawei adopts a mononuclear radiation cooperation mode, primarily industry-university oriented, with a focus on technological proximity.

Policy-induced cooperative knowledge network, university-industry collaboration and firm innovation: Evidence from the Greater Bay Area

The major goal of this paper is to analyze the interactive impact of China's high-tech policies on university-industry (UI) collaboration and firm innovation by a network-based approach. Introducing high-tech policy to traditional innovative networks, we constructed a policy-induced UI collaboration network and applied social network analysis (SNA) method to empirically study the role of high-tech policies and the underlying mechanisms in firm innovation in the Greater Bay Area (GBA). This policy-induced innovative network consists of over 2000 innovative entities in GBA from 2012 to 2021, which reflects dynamic characteristics of innovative activities in this region. Based on this network, we find that high-tech policies play a positive and key role in regional innovation and we also clarify some potential mechanisms and routes in the effect of policies on UI collaboration and firm innovation. This paper advances our understanding of innovative networks and policy-induced regional innovation, which has implications for innovation policymaking in world-class innovative centers.

Unpacking intercity competitive relations in the global corporate spatial organization of manufacturing

AbstractDespite being a traditional research topic in urban studies, competitive relations among cities have rarely been quantified in empirical research. Drawing on methods of social network analysis, this study aims to extract intercity competitive relations at the global scale based on the global corporate spatial organization of manufacturing. The geographies of competitive relations manifest different patterns from those of global city networks based on cooperative relations. This study finds an inverse U‐shaped relationship between cities’ connectivities and their gross intensity of competition. Although most global cities have unique positions in global manufacturing competition, intensive competition occurs among some global cities, whereas extensive competition exists between wide‐ranging cities with weak global connectivities. Furthermore, there is strong competition among cities of similar size and among those located in the same region. This research not only re‐examines global intercity relations from a competitive perspective but also informs the formulation of policy‐making on competition strategies of cities.

Can the opening of high-speed rail boost the reduction of air pollution and carbon emissions? Quasi-experimental evidence from China

This study utilizes panel data from 282 cities in China and employs the difference-in-differences method, mediating effect model, social network analysis method, and spatial econometric model to thoroughly investigate the impact of high-speed rail development on urban air pollution and carbon emissions reduction. The results of the study revealed that the introduction of high-speed railways correlated negatively with metropolitan PM2.5 and carbon emissions, suggesting a reduction in urban air pollutants and carbon emissions. The impact of high-speed rail installation on urban air pollution and carbon emissions reduction depends on various factors, such as the metropolitan area's location, size, and access to resources. Moreover, by optimizing the industrial structure and promoting technological innovation within the metropolitan region, high-speed rail installation can contribute to efforts to reduce air pollutants and carbon emissions. Over time, the influence of high-speed rail on industrial structure and technological development becomes increasingly significant. In urban centers connected to high-speed rail networks, the introduction of high-speed rail plays a significant role in fostering the reduction of urban air pollution and carbon emissions. Given the spatial correlation, the advent of high-speed rail will impact not only local air pollution and carbon reduction processes but also those of neighboring cities.

Research on the evolution of China's photovoltaic technology innovation network from the perspective of patents

Photovoltaic (PV) technology, as a low-carbon energy technology, is crucial to mitigating climate change and achieving sustainable development. China has the largest total number of PV technology patents in the world, but the lack of core technologies has restricted the further innovative development of China's PV industry. Therefore, it is necessary to clarify China's current PV technology accumulation to better catch up with key technology areas. To clearly describe the structural characteristics of China's PV technology innovation network, this study uses China's patent PV technology data over the past 20 years from the Incopat global patent database and analyses the structural characteristics of the network from the perspectives of one-mode and two-mode networks, using method of social network analysis (SNA). The results show that 1) the leading PV enterprises have basically formed relatively stable internal collaborations and that the scale of innovation network development has expanded rapidly, with very strong stamina; 2) with the development of China's PV industry, many innovative PV techniques have been developed by leading enterprises in the field of innovation and research and development (R&D) of PV technology, and among patent applicants with strong collaboration, kinship collaboration with investment relationships is dominant; 3) provinces participating in PV technology innovation are increasing significantly, the network is more influenced by leading nodes, and the eastern coastal provinces are pioneers in the innovation and R&D of PV technology; and 4) PV technological innovation collaboration between patent applicants and cities has changed from local collaboration to cross-regional collaboration, high-value areas are basically concentrated in the eastern coastal region of China, with scattered spatial characteristics, and cross-regional collaboration presents a “triangular” spatial structure, with the Yangtze River Delta, Pearl River Delta, and Beijing-Tianjin-Hebei as cores. The conclusions can provide patent information support for scientific research on energy conservation and emission reduction to achieve low-carbon goals, and can also provide reference for policy formulation of renewable energy development and green development strategies.

Research on Social Media, Short Video, Digitization and International Communication of Chinese Culture

Abstract Social media have become a pivotal platform for countries to engage in international discourse in the context of globalization and integration. In this study, a six-degree communication model is utilized to construct the online communication body of Chinese culture. Based on the social network analysis method, a communication analysis is completed for Chinese culture’s international communication. As a final step, 434 effective communication samples are chosen as research objects on the TikTok platform, which combines social media, short videos, and digital technology to facilitate the international communication of Chinese culture. The results show that on the TikTok platform, the global communication distance effect of Chinese culture is reflected in the network distance of 0.3900, the content distance of 0.2971, and the emotional distance of 0.3129, all of which are much smaller than the communication distance of traditional methods. The way Chinese culture spreads on TikTok, a platform that combines social media, short videos, and digitization, exhibits a degree of efficacy and feasibility.