Application Of Social Network Analysis Research Articles

Measuring the adaptive capacity of rangeland users under drought stress in North-easternIran: application of social network analysis

Drought events have significant impact on ecosystems and the livelihoods of rural communities in Iran. So, the purpose of this study was the analysis and evaluation of dimensions of adaptive capacity (AC) against drought in Bajestan county, Khorasan Razavi province, Iran. A questionnaire was used to collect data for social network analysis (SNA) and AC by the full network method. Then, a combined SNA-SEM model was developed to determine what was the social response of rangeland users in dealing with drought. In this study, the AC of rangeland users was compared in two groups of villages covered by the collaborative management or Carbon Sequestration Project (CSP) and uncovered by CSP. The results confirmed that the villages under CSP had higher levels of AC and social capital. Among five capitals, indicators of economic resources and information, skills and management were more effective on AC. Among the SNA indexes, effsize, constrain, indirects, density and betweenes centrality are more effective on AC of rangeland users. Results showed that identifying the key actors, who have the power and influence to determine the information flow and financial inflows in these components, can help increase the AC of rangeland users to mitigate effects of drought.

Natural language processing applications in social network analysis: a data mining approach

Natural language processing applications in social network analysis: a data mining approach

Analysis of smallholder farmers' dynamics of knowledge sharing, skill transfer, and participation in using biogas (application of social network analysis)

Air pollution, population growth, and the lack of fossil energy sources are critical factors that drive people toward clean and renewable energies in the current century. Biogas is suitable for rural farmers as a source of clean energy. Since there are many social interactions in knowledge exchange and sharing, the transfer of skills, and participation among individuals, various actors are involved in the network. The power and influence of actors and the social interactions between smallholder farmers and these actors fuel the development of biogas consumption in rural areas. Therefore, this study analyzes the social network structures and characteristics of various actors by social network analysis (SNA) in knowledge sharing, the transfer of skills, and participation networks among traditional smallholder farmers in Iran. The research sample consisted of some smallholder farmers in four provinces of Fars, Khorasan Razavi, Golestan, and Kermanshah (144 smallholder farmers). The research instrument was a questionnaire designed as a matrix. The findings showed that based on the betweenness centrality score, biogas-consuming smallholder farmers (34.56) and cooperatives of smallholder farmers (24.79) were the main actors in the network of knowledge sharing, respectively. Furthermore, biogas-consuming smallholder farmers (28.04) and pioneer smallholder farmers (27.11) were the main actors in the network of participation, respectively. The betweenness centrality score revealed that cooperatives of smallholder farmers (29.23) and opinion leaders (23.33) were the main actors in the network of skills transfer, respectively. It can be concluded that these actors had high social power and influence among smallholder farmers and can be the core of the smallholder farmers’ social networks. It means that they can influence the development of biogas consumption among Iranian smallholder farmers.

Finding small feedback arc sets on large graphs

The minimum feedback arc set problem (FASP), which seeks to remove a minimum set of arcs from a directed graph to make the remaining graph acyclic, is fundamental in graph algorithms with many applications in social network analysis, circuit testing, deadlock resolution, algorithmic games, and other fields. However, in theory, FASP is NP-Hard and cannot be approximated within any constant under the Unique-Games Conjecture. In practice, the performance of existing algorithms on large graphs is still unsatisfactory. To solve FASP on large graphs, we propose two novel methods in this paper. First, we systematically study the reduction rules for FASP that can quickly reduce the scale of input graphs without losing optimality. We integrate the reduction rules into an algorithm that can be used as a preprocessor for all existing FASP algorithms to simplify the input graphs. Second, we provide a scalable heuristic algorithm based on the divide-and-conquer method for better solution quality. Extensive experiments on a wide range of real-world graphs show that the reduction algorithm effectively reduces the size of input instances. Furthermore, for half of the circuit benchmark graphs, our final algorithm improves the quality of the existing heuristic solution by 24% to 40% within an acceptable running time.

Advancing the Measurement of Social Functioning in Schizophrenia: Applications of Egocentric Social Network Analysis.

People with schizophrenia face challenges with forming and maintaining social relationships, often resulting in poor social functioning. Commonly used measures of social functioning provide broad information relating to social relationships, but they do not adequately capture information regarding network structure and characteristics of network members. One method that can assess these more detailed aspects of social networks and provide a more comprehensive understanding of social functioning deficits is egocentric social network analysis (SNA). SNA is a scientific discipline that uses principles of network science and graph theory to analyze social relations quantitatively. Even though some types of SNA have been applied in prior schizophrenia studies, its application as a framework to measure social functioning has been extremely limited. Therefore, this article aims to formally introduce SNA and select quantitative SNA metrics, including measures of network composition, structure, homophily, and centrality, to schizophrenia researchers as novel ways of measuring components of social functioning. To demonstrate the application of SNA, we provide illustrative examples of the SNA metrics and graphical diagrams of social networks for two individuals with schizophrenia.

A network of designs: studying Early Lapita exchange networks in the Bismarck Archipelago, Papua New Guinea through Social Network Analysis

ABSTRACTThe application of Social Network Analysis to the study of archaeological networks has become increasingly common around the world, with a proven track record of processing large, complex, spatial and temporal archaeological datasets. This study builds upon previous network‐based analyses of interaction between communities of the Lapita Cultural Complex, with a specific focus on the Early Period (c.3300/3200–3100 calBP) in the Bismarck Archipelago, Papua New Guinea. Employing motif inventories from 13 Early Lapita Period assemblages, motif similarity and Centrality Analysis are undertaken, with the results compared to data from portable material culture, particularly obsidian and pottery, to further define the networks of interaction that linked communities during this period. We conclude that motif similarities and Centrality Analysis scores show good agreement with patterns of interactions established from the analysis of other types of portable material culture, which together support the existence of northern west to east and southern obsidian distribution networks, comprised of communities that employed unique types of interaction tailored towards their own cultural and societal circumstances and needs. Finally, we further conclude that these two networks may have arisen during the initial formation of the Lapita Cultural Complex, as populations established new social connections with other settler communities and incumbent populations across the region to survive in a new and foreign environment.

Research on the Evolution of the Spatial Association Network Structure and Driving Factors of China’s Agricultural Green Development

Against the backdrop of global environmental challenges and sustainable development goals, this paper pioneers the application of social network analysis to the study of spatial associations in China’s agricultural green development. It not only enhances the understanding of the spatial interconnectivity and network structural characteristics of agricultural green developments, but also captures the complex dependencies and interactions among provinces through a network lens, offering a fresh perspective on regional agricultural cooperation and competition. The study reveals: (1) The spatial network of China’s agricultural green development displays strong overall connectivity and enhanced stability, with regional green development trends becoming increasingly interlinked and interdependent. (2) The network exhibits a clear hierarchical and core-periphery structure which, over time, shows signs of diminishing, indicating a narrowing of developmental disparities among regions. (3) Significant shifts in the roles and positions of provinces within the network occur due to the relocation of industrial focal points and adjustments in development strategies, highlighting the complexity of dynamic changes among regions. (4) The spatial association network can be divided into four main clusters: Net spillover block, Bidirectional spillover block, Net beneficial block, and Broker block, with significant gradient characteristics in the relationships between these clusters, suggesting directional and differential flows and exchanges of resources and information among regions. (5) Geographic proximity, economic development level, informatization, and agricultural technological advancement significantly influenced the development and structural evolution of the network.

Social Network Analysis: A Survey on Process, Tools, and Application

Due to the explosive rise of online social networks, social network analysis (SNA) has emerged as a significant academic field in recent years. Understanding and examining social relationships in networks through network analysis opens up numerous research avenues in sociology, literature, media, biology, computer science, sports, and more. Therefore, certain studies review and discuss some research verticals of SNA, such as viral marketing, information diffusion, clustering, link prediction, and so on, to provide background knowledge and understanding. These studies still lack the SNA process, tools, and practical aspects in multidisciplinary applications. Inspired by these facts, we have discussed the background, process, tools, and application of SNA. First, we have presented a detailed description of the SNA process. Thereafter, we presented a comparative analysis of SNA tools and languages. Finally, we have discussed the various applications corresponding to SNA research verticals.

Application of Social Network Analysis for Comparison and Ranking of Internet Service Providers

In this digital era, the Internet has become a basic necessity in life. This has had a significant impact on the growth of internet service provider (ISP) companies in Indonesia. Comparison and ranking of ISPs is needed to make it easier for users to choose services according to their needs as well as to encourage healthy competition between ISPs in improving their services. The problem is ranking ISPs using conventional methods (surveys) to obtain primary data is expensive and takes a long time. On the other hand, Social Network Analysis (SNA) is a method that has been widely used to understand customer desires by extracting information from social media. This information is in the form of User Generated Content (UGC), namely track records left by customers on social media. This research aims to measure the ISP rankings of Indihome, Biznet and FirstMedia using UGC data. The research method used is to collect consumer tweet data rapidly, carry out preprocessing to eliminate irrelevant data and apply SNA, including network structure analysis in the form of visualization and network property analysis with the Gephi application, as well as network content analysis in the form of sentiment analysis and WordCloud analysis. The number of dominant network properties and sentiment analysis calculates ISP ranking. Apart from that, the results of this SNA are in the form of recommendations for ISPs to improve services to customers.

The effects of the COVID-19 pandemic on connectivity, operational efficiency, and resilience of major container ports in Southeast Asia

The COVID-19 pandemic in 2020 has had significant impacts on the connectivity and performance of container ports in Southeast Asia. The application of social network analysis (SNA) in conjunction with key indicators, such as container throughput, total capacity of ships, number of ship calls, and berth duration, provides a comprehensive understanding of the development of the regional port system. While major ports in the region, namely Singapore, Port Kelang, Manila, and Laem Chabang, have exhibited signs of recovery owing to the expeditious and timely implementation of targeted policies to mitigate the adverse effects of the pandemic, smaller ports in the region, such as Bangkok, Penang, Tanjung Priok, and Tanjung Perak, are grappling with enduring repercussions and encountering challenges in resilience. These challenges stem from inadequate infrastructure, limited accommodation capacity, low loading/unloading productivity, and other significant risk events associated with the pandemic, all of which have weakened their competitiveness. In contrast, ports in Vietnam, including Cai Mep, Hai Phong, and Ho Chi Minh, as well as Malaysia's Tanjung Pelepas, have demonstrated that they are less impacted by the COVID-19 pandemic. This can be attributed to the sustained growth of their respective economies and the continued surge in domestic production to meet the unabated demand for exports. Based on these findings, several policy recommendations can be suggested for port authorities to effectively manage and mitigate the impact of risky events, such as pandemics, in the future while also enhancing the competitiveness of ports.

The Evolution of Social Network Analysis in Public Administration

Despite the importance of social network analysis (SNA) in public administration, comprehensive reviews on this topic are rare. This study aims to fill this gap by focusing on the application of SNA in network research within public administration. This research analyzes 144 empirical papers from top public administration journals (January 1997–January 2022), utilizing bibliometric and content analyses. The study identifies social capital, the Advocacy Coalition Framework (ACF), the ecology of games framework, and resource dependence theory as the predominant theoretical foundations of SNA. The primary focus of these works is on collective action problems and public service delivery, with a trend towards the integration and comparison of theories. Through content analysis, we find a notable shift in SNA application from descriptive analysis to network inference, predominantly using Exponential Random Graph Models (ERGMs). It also reveals the growing significance of network visualization in SNA. The study concludes with potential future directions for SNA in public administration, highlighting its evolving role and significance.

Mapping routine interactions in port operations: Insights from social network analysis

Social network analysis proves to be a valuable instrument for comprehending and visually representing intricate relationships among diverse entities within a network. This study aims to explore the application of social network analysis within the context of hinterland port operations. In pursuit of this aim, we examined the interactions amongst various stakeholders, including port authorities, truck drivers, port agent companies, vigilant guards, import/export firms, and terminal operators. As a result, we unveiled patterns, pinpointed bottlenecks, and unearthed opportunities to amplify efficiency and collaboration within this system. This inquiry contributes to the existing body of knowledge concerning the utilization of social network analysis within the maritime industry while also providing insights to enhance port performance.

‘We knew a cyclone was imminent’: Hazard preparedness and disaster management efficiency nexus in coastal Bangladesh

Natural hazard-prone countries in the global south adopted an anticipatory-preparedness approach in disaster risk reduction (DRR) by shifting away from the response and rehabilitation approach. It was highly associated with the policy recommendations of the United Nations Office for Disaster Risk Reduction (UNDRR) framework. Nevertheless, challenges remained in managing disaster risks due to heterogeneous efficiency among disaster managers. This research examines the institutional effectiveness of the disaster management agency in cyclone-prone areas in southwestern coastal Bangladesh through network analysis. This research also explores institutional efficiency's impact on household preparedness in mitigating losses. We collected two distinct data sets from the local Union Disaster Management Committee (UDMC) and households in the same operational area of UDMC that were at risk of cyclonic disasters. To evaluate the effectiveness of local disaster management institutions, we conducted structured interviews with 336 representatives, spanning eight UDMCs in the cyclone-prone regions. To assess the impact of institutional performance (specifically, the UDMCs) on household disaster preparedness and loss mitigation, we collected data from 696 at-risk households. These households were located within the operational zones of the eight UDMCs, and the data was obtained using a structured questionnaire. Based on the application of social network analysis, our findings demonstrated that UDMC members were more active in the aftermath of disasters, as confirmed by three centrality measures - degree, eigenvector, and betweenness. Consequently, upon employing the Negative Binomial and Poisson regression models, we found a positive association between household engagement with UDMCs and participation in disaster preparedness training. This training appeared to enhance the knowledge and capacity of the respondents. The spill-over effects from disaster preparedness appeared to bolster the resilience of at-risk households, assist them in avoiding disaster-induced damages, and maintain consumption stability in the wake of disasters.

A Study on the Application of Social Network Analysis Based Approach in the Optimization of Cultural Communication Paths and Efficiency

Abstract The optimization of cultural communication paths is an important part of Chinese culture’s continued dialogue with the world in the face of increasingly fierce international competition. In this paper, we use social network analysis to collect relevant data on the microblogging platform and analyze the overall network structure of “The Belt and Road Initiative” using network density, network distance, and clustering coefficients. Using social network analysis metrics, we calculate the node position of the network path of “The Belt and Road Initiative” and analyze the influence of each microblog account. We filter the cultural communication topics of “The Belt and Road Initiative”, scrutinize the participating regions, and establish the characteristics of the cooperation mode within this cultural communication. “The Belt and Road Initiative” has a network density of 0.247, 0.281, and 0.295, respectively, which indicates that the network density of these three topics is small and there is less information exchange, but the cohesive force of cultural communication is stronger. “People’s Daily,” “Central Committee of the Communist Youth League,” and “Phoenix Video” have high intermediary centrality (712.256, 700.425, and 695.253, respectively). The high intermediary centrality indicates that these nodes have a great influence on the flow of resources in the information dissemination network and can accelerate the efficiency of the “Belt and Road Initiative” cultural dissemination path.

텍스트마이닝을 활용한 부동산 시장 인식 변화 연구

This study compared and analyzed real estate market trends over the last six years using social big data generated on the web and social media. To this end, the applicability of social network analysis as a method of confirming and understanding public perception of the real estate market was confirmed. Big data were used for analysis, and because keyword network analysis was at the heart of the study, the author's patented “emotional information analysis method” was partially used. The analysis result reveals that from 2017 to 2019, keywords related to the rising phase of the real estate market were derived with high influence, and real estate policy keywords were ranked highly. Meanwhile, from 2020 to 2022, keywords related to the real estate market downturn had a high impact, and those related to real estate costs were ranked high. These research findings are a preliminary study that seeks an effective research methodology in understanding the past and present real estate markets. More specific policy research should be conducted using these research results.

Central Industries in the Ecuadorian Input–Output Network. An Application of Social Network Analysis

The present study identifies the most influential industries in Ecuador according to the Input–Output Table for 2019. For this purpose, four weighted centrality indices are used from Social Network Analysis: Degree Centrality, Closeness Centrality, Betweenness Centrality, and Alpha Centrality. The results suggest that wholesale and retail trade, transportation, and professional activities are the most influential in the Ecuadorian economy due to their high centrality in commercial relationships. According to Chenery and Watanabe's methodology, all are base sectors, that is, they mainly are supply-driven. So, these centrality measures highlight the relevance of sectors based on their forward linkages. This result is not surprising. The theory of shock diffusion suggests that productive shocks on high centrality sectors can spread cascading effects downstream and generate aggregate fluctuations.

Communication Network Anaylsis of “WTS” (Want to Sell) on Twitter

This research examines communication networks and key actors in the distribution of information, types of relationships, and communication carried out via computer platforms using the keyword WTS (Want To Sell). This research aims to determine and analyze the communication network and actors involved in the phenomenon of the trending topic "wts (want to sell)". This research uses Computer Mediated Communication (CMC) Theory. Social Network Analysis (SNA) is a visualization method for understanding relationships between individuals, which includes a general overview of social networks with the topics discussed. Application of SNA with Netlytic and Gephi models. Data of 10,000 samples was successfully recalled by Netlytic among active Twitter users. This research uses quantitative research methods with a descriptive approach. The results of the research show that there is degree centrality on the @Indomyfess account, this account is the most dominant actor and has a score of 273, betweenness centrality on the @sunrowf account with a value of 1373.83 as the strongest account in distributing link-related information, closeness centrality is 2,736 nodes which are popular actor in information distribution, and eigenvector centrality on the @indomyfess account with a value of 1.0 as the most important actor in information distribution and continues to be associated with related information. Interaction between actors in the "WTS" communication network occurs because they exchange information about topics surrounding the keyword "WTS."

APPLICATIONS OF SOCIAL NETWORK ANALYSIS IN PROMOTING CIRCULAR ECONOMY: A LITERATURE REVIEW

Circular economy (CE) is a sustainable alternative to tackle global challenges like climate change, waste, and pollution. The relations, perceptions and behaviors of stakeholders in circular economic activities may form barriers that hinder the circular transition. The promotion of CE requires investigating the interactions and information flow between CE stakeholders from a network perspective. This study revisits the applications of social network analysis (SNA) in promoting CE. Related concepts of CE and the research contents of SNA are reviewed. A bibliometric analysis is conducted to provide a bird’s eye on the research status and trend. On this basis, we summarize the challenges of promoting CE and refine specific problems, around which we review the research status of network modeling methods and statistical measures, information diffusion models, mining methods of perceptions, and social influence analysis. This study outlines the pathways through which SNA contributes to promoting CE, such as through revealing the relational structure and characteristics of stakeholders, forming and changing perceptions of stakeholders, improving behaviors of stakeholders, and examining the development of CE. The lessons learned from the review and future prospects are extensively discussed in combination with the features of the information age from both theoretical and practical perspectives.

Social Network Analysis as a Tool in the Care and Wellbeing of Zoo Animals: A Case Study of a Family Group of Black Lemurs (Eulemur macaco).

Social network analysis (SNA) is an increasingly utilised technique in the literature examining the social structures and organisation of animals and understanding the bonds between groups and individuals. Using a case study as an illustration, the applications of SNA are explored, including the identification of dominance hierarchies and detection of sources of social pressure, with a particular focus on the applications of SNA to holistic assessments of animal welfare alongside other methods. Based on the examination of social dynamics in a family group of four black lemurs (Eulemur macaco), a primate whose social organisation is characterised by patterns of female dominance, it is demonstrated that SNA can be used to examine the affiliative and agonistic interactions between individuals living in human care. SNA showed species-typical forms of female dominance that were largely directed towards the two males, characterised by the initiation of aggressive interactions and male submission. More intricate relationships and consistent social roles across networks were revealed through the examination of SNA. It is concluded that SNA has wide-ranging benefits in the assessment of effects of environmental changes, such as informing social management decisions, developing enrichment and intervention programs, and guiding overall improvements to the housing and care of individual animals. SNA, as part of an animal welfare toolbox, could, therefore, be a pivotal technique for modern animal welfare assessment that considers individual animals and their social lives. By sharing a case study of the technique in use, it is hoped that animal collections may adopt similar modern and evidence-based assessment methods.

Construction Site Layout Planning: A Social Network Analysis

Construction site layout planning (CSLP) is the strategic arrangement and planning of construction site spaces, which has an enormous impact on the success of any construction project. Over the past two decades, multiple planning models have been developed to generate layouts that maintain safety and productivity within the construction environment. Yet these models vary significantly with disparate assumptions, many of which remain unstated. This study harnesses social network analysis (SNA) as a means to convert data into knowledge. It applies SNA to shed light on CSLP, providing a comprehensive overview of the existing models, and illuminating the critical parameters that should be considered in layout planning. This analysis delves deep into past methodologies and sets the potential for forthcoming research investigations. This study aims to be a reference for readers and researchers venturing into the realm of CSLP. Numerous related records and studies from diverse databases and sources were reviewed and analyzed. Out of these, 70 articles were singled out, from which 14 pivotal parameters were distilled as the foundation for any CSLP framework. Through the application of SNA, gaps within the existing research domain and literature were pinpointed. The study findings demonstrate the growing interest in shifting to cutting-edge approaches in CSLP. However, the results show that the majority of these models in the literature fall short of sufficiently addressing realistic facility representation, noise effects, or the construction impact on the surrounding environment. Accordingly, this research illuminates these knowledge gaps. The findings of this review guide future research by sketching a broad outline for future optimization models and planning studies.