Social Network Analysis Methods Research Articles

Identifying opinion leaders and narrative agency in the rejection omnibus law discourse

As a social media platform, Twitter can become an arena for civil citizens to contest the state discourse. The rejection of the Omnibus Law Bill proves the legitimacy of the massive resistance and mass mobilisation to reject policy products that contradict the public interest. This research was meant to provide a social media analysis of the issues of the plan of legitimation of the Omnibus Law Bill by employing two analysis methods: social network analysis and descriptive qualitative method. Twitter interactions during the Omnibus Law Bill rejection era were dominated by civil actors. The primary activity on Twitter was not only civil movements but also confronting individuals who could help to form public ideas. Within the agency’s narrative framework, Twitter interactions related to Omnibus Law Bill are communal and social endeavours as part of participation in digital activism. Other dictions were also visible within various hashtags constructed to assert the agent’s political position. Various content and digital media platform were produced as the media for transferring information and knowledge. They were put for the best use in a beautiful package. By opinion leaders’ agency, the narrative built by the State can be contested to influence others.

The Network Structures and Characteristics of Global Hubs of STI in Big Data Analysis and Mining Technology

Global hubs of STI are strategic nodes in the global science network and will lead the future of global scientific progress. This paper takes big data analysis and mining technology as an example, exploring the structures and characteristics of global science network of 15 representative global hubs of STI from 2000 to 2019. Based on the data of highly cited papers and methods of social network analysis, we find that the global science network has the structure of hierarchy, with an obvious characteristic of regionality. Based on the structures and characteristics of global science network, the knowledge flow and management model of global hubs has been proposed, which may be conducive to strengthening the knowledge management and network collaboration among global hubs of STI in other frontier technologies.

The networked role of intermediaries in education governance and public-private partnership

ABSTRACT Education governance networks are increasingly common and very diverse. In a strategic case study, we apply a new social network analysis method to evaluate the sustainability of a public-private education governance network. We examine the balance of satisfaction across public and private sectors and the network’s fairness in terms of whether actor groups’ investments in the network are proportional to their influence. We find that this established, long-term network is not entirely balanced but is fair, and argue that the fairness contributes to its sustainability. This fairness might arise due to the existing intermediaries in the network. Intermediaries play important roles in many networks, operating between other actors to build capacity and facilitate cooperation. We investigate how intermediaries operate, especially in networks that connect the public and private sectors. We find that intermediaries’ roles differ according to sector. Public-sector intermediaries perform a direction function, complementing the effort and interconnectedness of individual actors. In contrast, private-sector intermediaries play a representing role, substituting for individual actors’ effort and interconnectedness. These different roles of the public- and private-sector intermediaries contribute to the sustainability of the network.

Discussion on the Scientific Research Cooperation Network of Local Colleges and Universities -- Based on the Perspective of Knowledge Governance


 
 
 
 In recent years, many scholars at home and abroad have carried out relevant research work on scientific research cooperation, but the social network analysis method is commonly used, and the literature on research cooperation network of local universities is relatively small and lacks a systematic theory. Taking knowledge governance as the basic perspective, we analyze the existing research on scientific research cooperation, carry out the analysis of the necessity and feasibility of establishing scientific research cooperation network in colleges and universities, and take 10 colleges and universities in Fujian Province as samples to explore the existing problems of scientific research cooperation network in local colleges and universities, so as to provide theoretical support and new perspectives for the level of scientific and technological innovation and service capability of colleges and universities to enhance the competitiveness of college education.
 
 
 
 

Exploring the Project-Based Collaborative Networks between Owners and Contractors in the Construction Industry: Empirical Study in China

In the project-based construction industry, organizations build collaborative relationships through specific projects. The owners and contractors who are the key project stakeholders have gradually formed a complex project-based industry-level collaborative network in many different projects, closely related to knowledge exchange and industry development. Based on the data set of the National Quality Engineering Award (NQEA) projects in China from 2013 to 2021, we empirically analyze the characteristics and evolution of project-based collaborative networks between owners and contractors in the construction industry by using social network analysis (SNA) and network motif analysis (NMA) method. The results show that (1) the owner–contractor collaborative network exhibits small-world network characteristics. The island effect caused by small groups in the network makes the overall connectivity of the network low. During the study period, the collaborative network became more compact. (2) State-owned construction companies, such as China Construction Third Engineering Bureau Corporation Limited, China Construction Eighth Engineering Bureau Corporation Limited, and China Construction Second Engineering Bureau Corporation Limited, with high degree centrality and betweenness centrality, are the core companies in the collaborative network. In China, state-owned construction enterprises are favored by owners and have established collaborative relationships with many owners and contractors. (3) There are two local collaborative patterns in the collaborative network: motif and anti-motif. Motifs include some triangle-based tight collaborative patterns, while anti-motifs involve some loose binary collaborative patterns. The results help understand the structure and evolution of the industry-level collaborative relationship network between owners and contractors and can provide references for owners and contractors to develop relationship cultivation strategies more effectively.

Historical Co-offending Networks: A Social Network Analysis Approach

Abstract Recent decades have witnessed growing use of social network analysis (SNA) to study criminal activities, including that of co-offending. However, few studies have examined co-offending networks within a historical context. This paper focuses on group-based crime in a large English town during the Victorian period, employing SNA methods to examine the prevalence, structure and composition of co-offending relationships. Networks for property, violent and victimless crimes were partitioned to compare co-offending across crime categories. Results indicate that co-offending groups were typically segregated, although there was a loosely-organised community of property crime offenders connected by ‘brokers’ who collaborated with multiple groups. Evidence also suggests that co-offending was largely characterised by assortative mixing in regard to sex, age and marital status.

The Institutional Social Role for Maritim Village’s Food Stability

This study aims to explore social networks and interactions between networks in strengthening food stability in maritime villages in coastal areas. The geographical condition of the region has become one of the triggers for food instability and food security problems in coastal areas. This study uses the method of Social Network Analysis (SNA). Data processing uses R to visualize the role of stakeholder centrality. The analysis used is the analysis of baseline network, degree, and betweenness centrality. The value of modularity is an indicator of increasing or decreasing community networks. The number of nodes and links identifies the actors in the network and the interactions between actors. The results showed that social networks have an essential role in food stability. The private sector is a key actor in food stability in maritime villages. Is indicated by the modularity value of 0.43 (>0), which connects to 30 social network nodes and 62 links to food stability in maritime villages in the coastal area of Bintan Regency.

Research on the structural characteristics and influencing factors of global environmental services trade networks.

The development of the environmental services trade is crucial to achieving climate goals and a green economic transition. Based on environmental services trade data from 2001 to 2019, this work uses the social network analysis (SNA) method to depict the structural features of global environmental services trade networks, empirically testing the influencing mechanism of network evolution based on the quadratic assignment procedure (QAP) model. The results indicate that the global environmental services trade is now in a rebound stable period. The market of the environmental services trade is becoming increasingly diversified, the accessibility and convenience of trade are constantly being enhanced, and there is an obvious core-edge structure in the network. Belgium, Italy, and the Netherlands are at the center of the global environmental services trade network; Greece, as the most prominent trade catch-up country, has gradually become an important "bridge" and "hub." Climate change, geographical distance, and population size are the key factors affecting the global trade network of environmental services; environmental regulation, economic distance, and green technology distance have no significant impact on the development of the global environmental services trade, and language difference is no longer an obstacle to the growth of this trade. The results indicate that countries should develop in-depth transnational trade cooperation in the field of environmental services and do so with a more open attitude. The government should give sufficient policy support to the import and export of environmental services, guaranteeing the development of the environmental services trade.

Smart Transportation Behavior through the COVID-19 Pandemic: A Ride-Hailing System in Iran

During the COVID-19 pandemic, significant changes occurred in customer behavior, especially in traffic and urban transmission systems. In this context, there is a need for more scientific research and managerial approaches to develop behavior-based smart transportation solutions to deal with recent changes in customers, drivers, and traffic behaviors, including the volume of traffic and traffic routes. This research has tried to find a comprehensive view of novel travel behavior in different routes using a new social network analysis method. Our research is rooted in graph theory/network analysis and application of centrality concepts in social network analysis, particularly in the ride-hailing transportation systems under monumental competition. In this study, a big city, with near to ten million habitants (Tehran), is considered. All city areas were studied and clustered based on the primary measures of centrality, including degree centrality, Katz centrality, special vector centrality, page rank centrality, proximity centrality, and intermediate centrality. Our data were the trips of this system in Tehran, where the nodes in this network represent Tehran’s districts, and the connection between the two districts indicates the trips made between those two districts. Also, each link’s weight is the number of trips between the two nodes (district). The districts of Tehran were ranked in the smart transportation network based on six criteria: degree centrality, degree centrality of input, degree centrality of output, special vector centrality, hub, and reference points. Finally, according to comprehensive data-driven analysis, the studied company was suggested to create shared value and sustainability through the platform to perform a legitimate system to meet the new challenges. Our proposed system can help managers and governments to develop a behavior-based smart transportation system for big cities.

Technology Trend Analysis of Japanese Green Vehicle Powertrains Technology Using Patent Citation Data

As automobiles are major contributors to greenhouse gas emissions, the technological shift towards vehicle powertrain systems is an attempt to lower problems such as emissions of carbon dioxide and nitrogen oxides. Patent data are the most reliable measure of business performance for applied research and development activities when investigating knowledge domains or technology evolution. This is the first study on Japanese patent citation data of the green vehicle powertrains technology industry, using the social network analysis method, which emphasizes centrality estimates and community detection. This study not only elucidates the knowledge by visualizing flow patterns but also provides a precious and congregative method for verifying important patents under the International Patent Classification system and grasping the trend of the new technology industry. This study detects leading companies, not only in terms of the number of patents but also the importance of the patents. The empirical result shows that the International Patent Classification (IPC) class that starts with “B60K”, which includes hybrid electric vehicle (HEV) and battery electric vehicle (BEV), is more likely to be the technology trend in the green vehicle powertrains industry.

Spatial Correlation Network of Energy Consumption and Its Influencing Factors in the Yangtze River Delta Urban Agglomeration

Accurately understanding the correlation characteristics of energy consumption between regions is an important basis for scientifically formulating energy policies and an important entry point for realizing carbon peak and carbon neutrality goals. Based on the energy consumption data of the Yangtze River Delta urban agglomeration (YRDUA) from 2004 to 2017, the social network analysis method is applied to investigate the spatial correlation characteristics of the energy consumption of 26 cities and its influencing factors in the YRDUA. The energy consumption presents an obvious spatial correlation network structure. The network density fluctuates by approximately 0.3, and the network structure is relatively stable. Hangzhou, Suzhou and other cities are at the center of the network, playing the role of intermediaries. In the network, 10 cities, such as Shanghai and Shaoxing, have the characteristics of bidirectional spillover effects and act as “guides”, while Nanjing, Yangzhou and Chuzhou have the characteristics of brokers and act as “bridges”. The regional differences in geographical adjacency, FDI, industrial agglomeration and environmental regulation intensity are positively correlated with the network, and the impact coefficients are 0.486, 0.093, 0.072 and 0.068, respectively. Infrastructure differences are negatively correlated with the network, with an impact coefficient of −0.087.

Spatial Association Network Evolution and Variance Decomposition of Economic Sustainability Development Efficiency in China.

The economy's sustainable development has become a national strategic deployment in China. Research on the difference between the economic sustainable development efficiency (ESDE) and the spatial network will assist the government with the deployment of sustainable development strategies and the achievement of the "peak carbon dioxide emissions". This paper designs the input-output indicator system of sustainable economic development efficiency and builds an unexpected output super-EBM-Malmquist model to measure the ESDE of 30 provinces in China from 2008-2020. According to the ranking of ESDE, the 30 provinces in China are classified into four groups by applying the quartile method, and the difference in the ESDE in different regions and the temporal variation of different provinces are studied by using the Dagum Gini coefficient and Gaussian Kernel density. Moreover, the relationship between ESDE in different provinces is studied based on the revised gravity model and social network analysis method. The connections between provinces with related relations constitute the ESDE network. Results show that (1) the average ESDE in China shows an upward trend, the eastern region is in a leading position, the central and western regions are trying to catch up with the eastern region, and the development of the northeast region is lagging behind. (2) The level of ESDE in different provinces is clearly arranged from high to low, illuminating a distinct pattern. Moreover, provinces with high levels of development are much higher than provinces with low levels of development, presenting a phenomenon of polarization. (3) The regional ESDE development imbalance is prominent, and the ESDE in the eastern region is closely related, while the connection in the western region is lower. (4) Beijing-Tianjin Urban Agglomeration and the Yangtze River Delta have significant spatial spillover effects in the association network, while the northeast, northwest, southwest and central regions have significant spatial benefit relationships. These findings provide important enlightenment for promoting the sustainable and balanced development of China's economy.

Nuclear energy: Twitter data mining for social listening analysis

Knowing the presence, attitude and sentiment of society is important to promote policies and actions that influence the development of different energy sources and even more so in the case of an energy source such as nuclear, which has not been without controversy in recent years. The purpose of this paper was to conduct a social listening analysis of nuclear energy using Twitter data mining. A total of 3,709,417 global tweets were analyzed through the interactions and emotions of Twitter users throughout a crucial year: 6 months before and 6 months after the beginning of Russian invasion of Ukraine and the first attack on the Zaporizhzhia NPP. The research uses a novel approach to combine social network analysis methods with the application of artificial neural network models. The results reveal the digital conversation is influenced by the Russian invasion of Ukraine. However, tweets containing personal opinions of influential people also manage to enter the digital conversation, defining the magnitude and direction of the debate. The digital conversation is not constructed as a public argument. Generally, it is a conversation with non-polarized communities (politics, business, science and media); neither armed conflict or military threats against Zaporizhzhia NPP succeed in rousing anti-nuclear voices, even though these events do modify the orientation of the sentiment in the language used, making it more negative.

Global textile and apparel value-added exports network structure and China’s network position

ABSTRACT By taking the textile and apparel value-added exports data of 43 economies as the research sample, the social network analysis method is used to measure the global textile and apparel value-added exports network structure. The results show that the world textile and apparel value-added trade network is uneven, China has the widest range of trading partners, and the breadth of trading partners is growing over time. Germany and Italy have a stronger ability to control trade among other economies, and China’s ability to control trade with other economies is generally average, but the gap between China and Germany or Italy has narrowed significantly. China’s core degree has risen sharply. The trade networks are concentrated in a small number of core zone countries. The small group located in China is characterized by contraction.

Lineages as Network: A Study of Chan Genealogy in the Zutang ji 祖堂集 Using Social Network Analysis

This paper attempts to examine the genealogical framework of “lamp records” (denglu 燈錄) of the Chan Buddhist tradition using analytical tools and methods of Historical Social Network Analysis (HSNA) and graph theory. As an exploratory study, the primary objectives are to investigate the possibilities offered by HSNA and visualization tools for research on Chan genealogy in lamp records, explore the benefits of this approach over traditional lineage charts, and reflect on its limitations. The essay focuses on the Chan community portrayed in the Goryeo 高麗 edition of the Zutang ji 祖堂集 (Collection of the Patriarchal Hall; K.1503). It shows that the lineage reportedly stemming from Qingyuan Xingsi 青原行思 (d. ca. 740) and Shitou Xiqian 石頭希遷 (701–791), as well as the branch descending from Tianhuang Daowu 天皇道悟 (748–807) to Xuefeng Yicun 雪峰義存 (822–908) and his successors, play a crucial role within the structure of the Zutang ji’s genealogical network. The study further highlights possible irregularities in lineage claims by contrasting metrics of degree and betweenness centrality with features of the text (e.g., number of hagiographic entries, length of the entries).

Spatial structure and influencing factors of regional city supply networks in manufacturing: A case study of Shandong, China

COVID-19 has driven the formation of regional supply chains. In addition, cities became the basic units of intra-regional supply chain organization under urban administrative economies. Based on the data mining of the buyer-supplier relationship of listed manufacturing firms, this study explores the spatial characteristics of city supply networks within Shandong by the indexes of degree centrality, closeness centrality, betweenness centrality, eigenvector centrality, and a community detection algorithm using the social network analysis (SNA) method and ArcGIS software. It investigates the influencing factors of city supply networks by the correlation and regression of the quadratic assignment procedure (QAP). The results show the following: 1) Shandong has formed a multi-center city supply network with Jinan, Qingdao, Yantai-Weihai, and the distribution pattern of city centrality measured by different centrality indicators shows differences. 2) Cities belonging to the same network community show a coexistence of spatial proximity and “enclave” distribution. 3) Geographic proximity, convenient transportation links, administrative district economy, similarity of business environments represented by development zones, export-oriented or domestic market-oriented division of labor between cities, value chain division of labor between cities, and land price differences between cities promote the formation of regional city supply networks. Conversely, differences in local market size and wage levels between cities hinder the formation of city supply networks. This study attempts to apply the analysis results to regional planning from the perspective of regional industrial synergy development. Additionally, as it is based on typical Chinese provinces, it can provide policy references for national administrative regions and countries/regions at similar spatial scales for manufacturing supply chains, as well as for regional spatial layout decisions of manufacturing enterprises.

Using social network analysis approach in developing rural psychiatrist workforce

This study examines how rural and remote junior doctors career decisions are influenced by highly connected principles within a discipline. Social network analysis was completed with data collected, by structured interview, with five psychiatry trainees and three early career psychiatrists in a rural location rated MM3 using the Modified Monash Model. UNICET software was used to determine the interactions between individual networks to look for overlap and common influencers. A single central, highly connected, psychiatrist was found at the core of the entire social network. This connector was instrumental in recruitment and retention in rural psychiatry workforce. Improving the understanding of human capital can encourage innovative solutions in developing sustainable strategies for recruiting and retaining rural psychiatry workforces.

Analysis of the Characteristics and Causes of Night Tourism Accidents in China Based on SNA and QAP Methods.

The key purpose of this paper is to address an inherent gap in the literature on safety issues in the development of night tourism. This research takes a novel methodological approach, by using 8787 cases of tourism safety accidents in typical night tourism cities in China, and applying social network analysis (SNA) and quadratic assignment procedure (QAP) regression analysis to explore the multidimensional structural characteristics and risk-causing factors of night tourism accidents. Key findings include: (1) Amidst the complexity and diversity of the night tourism safety accidents in cities, disastrous accidents, public health accidents, natural disasters, and social security accidents are the main types of night tourism safety accidents. (2) Night tourism safety accidents have strong aggregation in specific time periods and spatial regions. There are differences in the timepoint and duration of each accident type, showing different distribution characteristics in different cities and locations. (3) Distribution of accident types in night tourism products shows obvious core-edge structure characteristics. (4) The degree of co-occurrence of four risk-inducing factors, i.e., personnel, facilities, environment, and management, has high explanatory power at the accident correlation level in the co-occurrence network of night tourism safety accidents in cities, and the influence effects of risk factors are heterogeneous at different timepoints. Our results provide some valuable implications for optimizing night tourism safety governance in cities.

Analysis of Cashback Marketing Content to Increase Business Competitiveness Through the Electronic Trading Company Marketplace

The nature of writing this research has the first purpose to map the interactions and structures that occur among tokopedia consumers on social media twitter, the second to find out strategy recommendations digital marketing on tokopedia marketplace processed using methods social network analysis. Today's global civilization, manufacturing activities are beginning to witness tremendous changes in various countries. With the emergence of information technology and its increasingly advanced convenience, we all have the ability to think creatively in the face of more and more competition, the most important thing in the era of Covid-19 is the decline of the world economy. Business actors are expected to continue to think and be creative in order to improve, advance and maintain their business in order to obtain maximum profits and be known to the wider community. This research is qualitative descriptive research using data Secondary derived from Twitter. Methods used in this study Using the Social Network Analysis (SNA) method by using big data. In data retrieval assisted by a variety of tools. The support that will be used in this research is Google Colab, Jupyter Colab, Dictionary, Wordij and Gephi.

An approach of selecting cold chain logistics service provider based on SNAand FCE method

In this paper, an integrated decision-making methodology is proposed to solve the subjectivity and fuzziness in the selection of cold chain logistics service providers (LSPs). Firstly, the social network analysis (SNA) method is applied to select the evaluation criteria of cold chain LSPs, which is based on the systematic literature analysis. Then, a novel combination weighting method that combines the advantages of entropy weight (EW) method and improved analytic hierarchy process (AHP) is constructed to calculate the weight of criteria. Further, the fuzzy comprehensive evaluation (FCE) method is utilized to generate a ranking order of providers and recommend the optimal provider. Finally, the illustrative example and comparison analysis are provided to prove the validity and feasibility of the approach. In addition, a sensitivity analysis is presented to discuss the stability of the proposed method. In conclusion, this paper innovatively constructs an index system of cold chain LSPs evaluation and selection, and the process of evaluation and selection is also objective.