Social Network Analysis Approach Research Articles

A social network analysis approach to assess COVID19-related disruption to substance use treatment and informal social interactions among people who use drugs in Scotland.

To assess the extent of Coronavirus-related disruption to health and social care treatment and social interactions among people with lived or living experience of substance use in Scotland, and explore potential reasons for variations in disruption. Cross sectional mixed methods interview, incorporating a social network 'egonet interview' approach asking about whether participants had interactions with a range of substance use, health, social care or third sector organisations, or informal social interactions. Five Alcohol and Drug Partnership Areas in Scotland. 57 (42% women) participants were involved in the study, on average 42 years old. Five-point Likert scale reporting whether interactions with a range of services and people had gotten much better, better, no different (or no change), worse, or much worse since COVID19 and lockdown. Ratings were nested within participants (Individuals provided multiple ratings) and some ratings were also nested within treatment service (services received multiple ratings). The nested structure was accounted for using cross classified ordinal logistic multilevel models. While the overall average suggested only a slight negative change in interactions (mean rating 2.93), there were substantial variations according to type of interaction, and between individuals. Reported change was more often negative for mental health services (Adjusted OR = 0.93 95% CI 0.17,0.90), and positive for pharmacies (3.03 95% CI 1.36, 5.93). The models found between-participant variation of around 10%, and negligible between-service variation of around 1% in ratings. Ratings didn't vary by individual age or gender but there was variation between areas. Substance use treatment service adaptations due to COVID19 lockdown led to both positive and negative service user experiences. Social network methods provide an effective way to describe complex system-wide interaction patterns, and to measure variations at the individual, service, and area level.

Measuring Enterprise–University–Institute collaborative innovation network of climate change mitigation technologies in China: a social network analysis approach

Measuring Enterprise–University–Institute collaborative innovation network of climate change mitigation technologies in China: a social network analysis approach

Intelligent construction technology based information sharing network for prefabricated building supply chain: a social network analysis approach

PurposeIn the context of Industry 4.0, intelligent construction technologies (ICT) represented by information technology and networking will undoubtedly provide new impetus to the development of the prefabricated building supply chain (PBSC), but they will also bring various potential risks. So far, there is a large lack of research on the comprehensive consideration of the risks associated with the intelligent transformation of PBSC based on the information sharing perspective, and the critical risks and interactions are still unclear, making it difficult to identify efficient risk mitigation strategies. Therefore, this paper aims to reveal the interactions between stakeholders and clarify the critical risk nodes and interactions in information sharing of PBSC (IS-PBSC), and propose targeted risk mitigation strategies.Design/methodology/approachFirstly, this paper creatively delineates the risks and critical stakeholders of IS-PBSC. Secondly, Data is collected through questionnaires to understand the degree of risks impact. Thirdly, with the help of NetMiner 4 software, social network analysis is conducted and IS-PBSC risk network is established to reveal critical risk nodes and interactions. Finally, further targeted discussion of critical risk nodes, the effectiveness and reasonableness of the risk mitigation strategies are proposed and verified through NetMiner 4 software simulation.FindingsThe results show that the critical risks cover the entire process of information sharing, with the lack of information management norms and other information assurance-related risks accounting for the largest proportion. In addition, the government dominates in risk control, followed by other stakeholders. The implementation of risk mitigation strategies is effective, with the overall network density reduced by 41.15% and network cohesion reduced by 24%.Research limitations/implicationsIn the context of Industry 4.0, ICT represented by information technology and networking will undoubtedly provide new impetus to the development of the PBSC, but they will also bring various potential risks. So far, there is a large lack of research on the comprehensive consideration of the risks associated with the intelligent transformation of PBSC based on the information sharing perspective, and the critical risks and interactions are still unclear, making it difficult to identify efficient risk mitigation strategies.Originality/valueBased on the results of risk network visualization analysis, this paper proposes an ICT-based IS-PBSC mechanism that promotes the development of the integration of ICT and PBSC while safeguarding the benefits of various stakeholders.

Analysis of the structure of the global avocado (Persea americana Mill) trade network

ective: To analyze the structure of the global avocado trade network and to understand the dynamics of commercial interaction between the leading countries in the market, using the social network analysis approach. Design/Methodology/Approach: One-hundred thirty-three countries that established 989 commercial exchange relationships were analyzed. This exchange accounted for 99% of the volume of the global avocado market for the year 2021. Results: The significant diversification in the import sources and export destinations of countries such as Netherlands and Spain suggests a robust and diversified trade strategy. Network indicators give a valuable insight into the centrality and importance of countries in the global avocado trade network. Mexico plays an important role in the network that goes beyond the quantity produced. Study Limitations/Implications: The most current analyzed data available to date belong to the year 2021. Findings/Conclusions: The analysis reveals the complex dynamics of interaction between the leaders of the global avocado trade.

Understanding rural social networks addressing adverse childhood experiences: A case study of the San Luis Valley.

The purpose of this study is to assess a cross-sector, interorganizational network addressing adverse childhood experiences (ACEs) in a rural Colorado community. We characterize the organizations in the network, assess their awareness of ACEs, and evaluate how they participate in the network. We also assess the network health. Employing a social network analysis approach, we collected survey data from 45 organizations that support young children and their families, including nonprofits, health care clinics, and early childhood education centers, among others. On average, nonprofit organizations had relationships with a greater percentage of network members than other types of organizations. Network members engaged in relationships focused on a wide range of activities (e.g., client assessments, sharing information, providing services), with some organizational types leading the network in certain activities. Scores across all dimensions of trust and value were above 3 (range: 2.1-3.8), which is advantageous for a network and network relationships existed across a range of relational intensities (from awareness to organizational integration). Nonprofit organizations that reported high levels of connectedness in the network were able to effectively mobilize the ACEs network. Health clinics participated in a greater share of relationships involving assessment, service provision, and tool sharing than other types of organizations. As such, health care clinics may serve as leaders in directly serving children and families experiencing ACEs in rural communities. The rural context may also explain high levels of trust and value, which can serve as assets for future network development and mobilization. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The Influence of MSME Marketing Strategies on Business Able to Survive During the Covid 19 Pandemic

This research aims to determine the influence of MSME marketing strategies on how Business Able to Survive during the Covid-19 pandemic. This research is a quantitative descriptive study using survey and netnograph methods with the Social Network Analysis approach for MSME business people who are members of MSME groups on Facebook and WhatsApp by providing questionnaires via Google form distribution. The basis for sampling is convenience sampling, namely a sampling technique by easily selecting members from the population to be sampled. The data analysis test tool used in this research is SPSS version 21. The research results show that there is a significant relationship and positive correlation between marketing strategy variables and business variables that continue to run during the Covid-19 pandemic. It is hoped that the research will be able to inspire MSME players to continue to organize marketing strategies so that their businesses can still survive even during a pandemic. This research can also be used as a reference for future researchers in researching marketing strategies of business people.

Disclosure of Origin in European Biotechnology Patent Law: A Social Network Analysis Perspective

Abstract Recital 27 of the European Union Directive 98/44/EC on the Legal Protection of Biotechnological Innovations mandates the disclosure of the geographical origin of biological material when the invention is based on or incorporates such material. This requirement seeks to monitor the origin of biological materials, often linked to indigenous and local communities, to ensure prior informed consent and equitable benefit-sharing with resource providers. Several European countries, such as Switzerland and Norway, legally require this disclosure, and the Draft International Instrument of the World Intellectual Property Organization is poised to expand the list of nations with such requirements. However, the definition of ‘origin’ presents challenges for patent applicants, as it may refer to the primary source (e.g. indigenous and local communities, the country of origin) or secondary sources (e.g. ex situ plant collections or commercial suppliers). Moreover, defining the information to be disclosed as the origin is crucial for the credibility of disclosure statements. To address this issue, this article pioneers a social network analysis approach to the issue of biopiracy and disclosure of origin. It introduces the network-centric narratives of 30 prominent cases of biopiracy from South and Southeast Asia, Latin America, and Africa, and unveils the average distance between the nodes previously accused of biopiracy and the nodes that correspond to the origin of the biological material in question. By highlighting the role of intermediaries in distorting information within material distribution networks, the findings contest the feasibility of requiring patent applicants to provide information on both primary and secondary sources.

Characterizing Food Policy Councils' Network Partnerships and COVID-19 Responses.

The COVID-19 pandemic pushed millions of Americans into food insecurity. Food policy councils (FPCs) across the country played a vital role in organizing coordinated food responses across multiple sectors. We used a social network analysis (SNA) approach to investigate: (1) the network of partnering organizations and agencies within FPCs; (2) how the characteristics of FPCs' network partnerships (i.e., degree, coreness, and density) related to programmatic, policy, and advocacy actions in response to the pandemic; and (3) how FPCs' use of a racial or social equity framework shifted their network partnerships and responses. Local government agencies and food supply chain actors were core in FPCs' network partnerships, while public utilities, correctional facilities, social justice groups, and others were non-core partners. Network density was more likely to be associated with any action by FPCs, and it was especially pronounced for advocacy actions taken by FPCs; trends were similar among FPCs that reported using a racial or social equity framework. The findings begin to uncover core actors in FPCs' partnerships and opportunities to establish new partnerships, particularly with social justice groups. The results also suggest that network density (interconnectedness) may be more important than other network characteristics when responding to food-related needs.

Social structures of urban governance: strategic spatial planning in Addis Ababa

ABSTRACT Focusing on strategic planning for spatial development, this paper explores the social structures that underpin urban governance in Addis Ababa, Ethiopia. To bridge the divide in the literature between studies that are narrowly focused on public service networks (typically more quantitative) and broader studies of urban governance (typically more qualitative), we use a social network analysis approach based on structured interviews to chart the actors and connections that influence the strategic planning process. Our results show that the governance network in this city is very homogeneous and centralised. The majority of actors at the core of strategic decision-making are city government entities, where most ties are structured around the Addis Ababa City Plan Commission and the mayor. With few exceptions (notably, the prime minister), other tiers of government, civil society organisations, the private sector and international donors are mostly peripheral. The fact that some powerful actors – such as international investors and the ruling coalition parties – are also playing a marginal role in the network may threaten governance stability and coherence. Although the mayor is a very powerful actor at the city level, the structural features of the governance network and the institutional power of the prime minister allow them to streamline their influence over the city’s future. The current governance regime for strategic spatial planning in Addis Ababa seems to privilege the effectiveness of the developmental agenda over the inclusiveness of the governing process. This has troubling implications for participatory development and the emergence of a more democratic society.

Emergent leadership in agile software development teams: leader identification through network analysis and aggregation approaches

PurposeAgile project teams are self-managing and self-organizing teams, and these two characteristics are pivotal attributes of emergent leadership. Emergent leadership is thus common in agile teams – however, how these (informal) emergent leaders can be identified in teams remains far from understood. The purpose of this research is to uncover techniques that enable top management to identify emergent agile leaders.Methodology/designWe approached six agile teams from four organizations. We employ social network analysis (SNA) and aggregation approaches to identify emergent agile leaders.Design/methodology/approachWe approached six agile teams from four organizations. We employ SNA and aggregation approaches to identify emergent agile leaders.FindingsSeven emergent leaders are identified using the SNA and aggregation approaches. The same leaders are also identified using the KeyPlayer algorithms. One emergent leader is identified from each of the five teams, for a total of five emergent leaders from the five teams. However, two emergent leaders are identified for the remaining sixth team.Originality/valueEmergent leadership is a relatively new phenomenon where leaders emerge from within teams without having a formal leadership assigned role. A challenge remains as to how such leaders can be identified without any formal leadership status. We contribute by showing how network analysis and aggregation approaches are suitable for the identification of emergent leadership talent within teams. In addition, we help advance leadership research by describing the network behaviors of emergent leaders and offering a way forward to identify more than one emergent leader in a team. We also show some limitations of the approaches used and offer some useful insights.

Support Networks of Immigrants in Canada: A Multilevel Multinomial Analysis of Social Support

This study examines the role of support networks in the integration process of Ghanaian immigrants to Canada. Although social support networks have been widely argued to shape the immigrants’ pre- and postmigration experience, their presence and roles are neither self-evident nor constant. Common conceptualizations of social support exchange often perceive support as unidirectional, flowing only from network members to immigrants. This underlies a rather linear notion of support networks among immigrants. Given this, this study investigates the directionality of support regarding emotional, instrumental, and informational support and the extent to which closeness, delineated as familial (kinship), perceived (importance of relationship), temporal (frequency of interaction), and geographic (location) influence these support exchanges. The study employs a multilevel multinomial analysis of 172 egocentric networks in Toronto, Canada, using a social network analysis approach. Results show that geographic closeness was consistently less important than kinship, temporal, and perceived closeness in both emotional, instrumental, and informational support—regardless of directionality. This broadly support the assertions about “death of distance” and that spatiality might no longer be a key influencer within the social support networks of immigrants.

Topic modeling and social network analysis approach to explore diabetes discourse on Twitter in India.

The utilization of social media presents a promising avenue for the prevention and management of diabetes. To effectively cater to the diabetes-related knowledge, support, and intervention needs of the community, it is imperative to attain a deeper understanding of the extent and content of discussions pertaining to this health issue. This study aims to assess and compare various topic modeling techniques to determine the most effective model for identifying the core themes in diabetes-related tweets, the sources responsible for disseminating this information, the reach of these themes, and the influential individuals within the Twitter community in India. Twitter messages from India, dated between 7 November 2022 and 28 February 2023, were collected using the Twitter API. The unsupervised machine learning topic models, namely, Latent Dirichlet Allocation (LDA), non-negative matrix factorization (NMF), BERTopic, and Top2Vec, were compared, and the best-performing model was used to identify common diabetes-related topics. Influential users were identified through social network analysis. The NMF model outperformed the LDA model, whereas BERTopic performed better than Top2Vec. Diabetes-related conversations revolved around eight topics, namely, promotion, management, drug and personal story, consequences, risk factors and research, raising awareness and providing support, diet, and opinion and lifestyle changes. The influential nodes identified were mainly health professionals and healthcare organizations. The study identified important topics of discussion along with health professionals and healthcare organizations involved in sharing diabetes-related information with the public. Collaborations among influential healthcare organizations, health professionals, and the government can foster awareness and prevent noncommunicable diseases.

ANALYSIS OF TWITTER USER INTERACTIONS USING SOCIAL NETWORKS AT PAYDAY SALE EVENTS ON THE MARKETPLACE

The goal of this study was to ascertain the marketplace companies' commitment to implementing SCRM on social media and to identify patterns of engagement, interaction, and communication between Twitter users and the marketplaces Shopee, Tokopedia, and Lazada that emerged on social media at payday sale events. The Social Network Analysis (SNA) approach is being used in this qualitative study. Twitter users in Indonesia are the focus of this study. The users of Tokopedia, Shopee, and Lazada are the research population. Dictionary, Notepad++, Wordij, and Gephi are supporting tools used in this study together with Jupyter Notebook. The Shopee Marketplace is superior and performs better, according to an analysis of network features. According to the analysis, the Shopee marketplace has a broader network. According to this study, many consumers utilize Shopee as their online shopping destination, particularly during payday sale events when each marketplace offers alluring discounts and free delivery.

Crowdfunding from the perspective of young people

Research aims: This study aims to identify the dominant factors that make young people interested in joining or using crowdfunding platforms.Design/Methodology/Approach: This research was conducted using the topic method or text analysis with the Social Network Analysis (SNA) approach. Data in the study were obtained by distributing questionnaires to 201 respondents who were young people aged 19 to 22 years.Research findings: The results of this study revealed that the dominant factors attracting young people to use crowdfunding include web technology, ease of use, high rate of return, transparency, and legality. The results of this study indicate that convenience is the primary attraction for young people in transactions. Theoretical contribution/Originality: The results of this study offer indicators that can be used to measure, in particular, the usability variables of web-based crowdfunding platforms in TAM (Technology Acceptance Model). These indicators encompass the amount of return, clarity of business fields and objectives, and transaction security. As for the variables of ease of use, among others, clarity of navigation and information on the web makes users comfortable.Practitioner/Policy implication: The findings of this study imply that Web 2.0 has become a suitable way of interacting with young people. Hence, crowdfunding platform websites need to be designed to support ease of transactions. However, accountability, transparency, clarity of effort, reciprocity, and legality can be effective campaign methods to attract young people to contribute to crowdfunding. Research limitation/Implication: This study used researchers' judgment to interpret the meaning and the relationship between keywords in sentences submitted by respondents in questionnaires.

Understanding the relationship between idea contributions and idea enactments in student design teams: A social network analysis approach

AbstractBackgroundExisting research has demonstrated that student characteristics, such as race/ethnicity, sex, and personal beliefs about engineering knowledge, shape students' experiences in ill‐structured problem‐solving, such as engineering design, where ideas must be communicated, negotiated, and selected in complex social processes.PurposeThe purpose of this research was to examine the how student characteristics, such as race/ethnicity, sex, and epistemological beliefs, are associated with patterns of idea contributions and ideas enactments in collaborative project teams.MethodIn this article, I use the multilayer exponential random graph model (ERGM) for examining multiple complex social relationships simultaneously. Drawing on survey data from a study of engineering student teamwork, this research examines the relationship perceptions of idea contributions (layer 1) and idea enactments (layer 2) in collaborative project teams.ResultsResults indicated no sex differences in the perceptions of idea contributions and enactments in student design teams. However, underrepresented minority students and Asian America/Pacific Islander students were reported as less frequently having their ideas enacted. Further, epistemological beliefs similarity effects were a significant predictor on the idea contribution layer, and epistemological beliefs sociality effects were significant on the idea enactments layer.ConclusionAchieving equity in teamwork pedagogies requires understanding the dynamic social processes that shapes patterns of participation in student teams. This research demonstrates the power of social networks methodologies for modeling teamwork processes, pointing specifically to the ways that student characteristics are associated with perceptions shape idea contributions and enactments in student teams.

Networked framing of GMO risks and discussion fragmentation on Chinese social media: a dynamic perspective

Genetically modified organisms (GMOs) have been highly controversial in China and beyond. The burgeoning of social media has created an online activist field where participants utilize networked framing practices to engage in connective actions related to GMO risks. However, a dynamic perspective on the co-production of GMO risk discourses has yet to be fully explored, and it is still under debate whether such a collective interpretation is fragmented. To address this gap, this study investigates the risk-invoked GMO controversy by longitudinally exploring the structural characteristics and discursive power structures in the networked framing of GMO risks on social media. This study examines 356,227 GMO risk posts from 2010 to 2020 on the Chinese social media platform Weibo. A longitudinal social network analysis and computational text-mining approach are used to construct representation networks among participants based on their joint sponsorship framing practices of GMO risks. The findings suggest that there is a multipolar discussion fragmentation in the networked framing of GMO risks. However, the temporal evidence shows that the risk discussion has become increasingly interconnected and less structurally fragmented over time. In addition, this study highlights the unequal distribution of discursive power among participants; nevertheless, the analysis reveals that this inequality has shown signs of easing over the study period. Overall, this study provides a comprehensive analysis of the GMO controversy from a risk perspective and sheds light on the dynamics of networked framing practices and discursive power structures on social media.

A Social Network Analysis Approach to Explore the Dualistic Interaction between the Digital Economy and Industrial Economics

Abstract In recent years, the digital economy has continuously innovated the traditional industrial economy and brought about the continuous optimization of economic structure. In recent years, the digital economy has continuously innovated the traditional industrial economy and brought about continuous optimization of economic structure. By combining the AP clustering algorithm, this paper creates a representative viewpoint extraction model that extracts the relevant features of relevant variables and generates a more representative economic viewpoint. The social network structure between the digital economy and industrial economics is analyzed using the social relationship graph. Using the information gain calculation formula, the correlation calculation is carried out on the characteristics of variables with stronger relationships and larger information gain. Meanwhile, the correlation coefficient between variables with larger information gain is calculated by Spearman’s coefficient. The influencing factors of industrial economic development under the digital economy are analyzed through three dimensions, and the theoretical model of group effect analysis is constructed to analyze the binary interaction between the two. Through the method of empirical analysis, the interaction between the digital economy and the industrial economy is tested in terms of smoothness and cointegration. HP filtering, as well as impulse response analysis, are carried out to analyze the interaction between the two in A. After 9 groups of experiments, the cointegration number of the original hypothesis is 0 or ≥1, the original hypothesis is rejected at a significance level of 1%, and the eigenvalues range from 67.4566 to 69.7445, and there is a correlation between the two. The impulse response value of the industrial economy improves from 0.0002 to 0.001. The development of the digital economy will lead to the development of the industrial economy.

Social interaction and stock price crash risk: a social network analysis approach

ABSTRACT Using a social network analysis (SNA) approach to construct a retail investor interaction network, this paper examines whether investor social interactions increase stock price crash risk. The results show that social interactions on social media increase the likelihood of a stock price crash, suggesting that such interactions among retail investors breed irrational emotions that spread throughout the network, leading to increased risk in the stock market. We also find that this relation is more pronounced in bear markets.

The Construction of Online Interactive Teaching Mode of Cross-border E-commerce English in Colleges and Universities under the Background of Internet

Abstract In this paper, we first constructed an online interactive English teaching model through the interaction hierarchy tower model and adopted a data-driven social cognitive network analysis approach to explore the evolutionary dynamics of cross-border e-commerce English learning communities in higher education and their potential correlation with the development of participants’ interaction patterns. Then, the online synchronous and asynchronous interaction patterns of learners are compared and integrated by extracting the characteristics of online interactive teaching learners. Finally, an instructional design for an online English for Cross-border E-commerce course was used to explore the differences and associations between online interactive teaching modes. The results show that in the teaching experiment, students have 39 nodes in the synchronous interaction network (SMN) and 34 nodes in the asynchronous interaction network (UMN), and the degree centrality and eigenvector centrality Rank=4.07 and 3.15 of the SMN are also significantly higher than those of the three interaction networks. The SMN interaction model is found to be the most efficient in the online interaction teaching process. This study helps to improve the dynamic regulation and precise guidance of the online learning process for cross-border e-commerce English, which ultimately enhances the quality of online teaching.

Vulnerability analysis of cruise shipping in ASEAN countries facing COVID-19 pandemic

The COVID-19 pandemic has significantly affected the cruise shipping industry, disrupting ports and shipping. However, current research predominantly focuses on the impact on individual ports or vessels, leaving a gap in understanding how these disruptions propagate across cruise shipping networks. To address this gap, a novel vulnerability assessment methodology that offers a comprehensive perspective on the broader impact of COVID-19 on cruise shipping networks is developed. It first uses a new weight social network analysis approach to quantify the vulnerability of each cruise port in a shipping network and then combines the curie port local pandemic risk to generate a new index to reveal the COVID-19 impact on the whole cruise shipping network systematically. The new methodology is applied to analyse the ASEAN cruise shipping network. This real-world COVID-19 pandemic case study yields valuable insights that bridge theoretical and practical domains. Integrating local port-level vulnerabilities with shipping network-level vulnerabilities creates a unique index. This index quantifies the individual and collective influence of COVID-19 risks at different cruise ports on the entire regional cruise shipping network. The results directly impact cruise lines seeking to enhance their operations' resilience in the face of COVID-19 challenges. The vulnerability index explains how risk exposure at various ports shapes the network's dynamics. This insight empowers cruise lines to optimise ship deployment schedules, lowering the network's overall COVID-19 pandemic risk. The research method and outcomes offer a pioneering perspective on the vulnerability of cruise shipping networks to COVID-19 disruptions, and other possible disruptions (e.g., climate change) in a broad sense. By elucidating interconnected vulnerabilities, cruise lines are equipped with actionable insights to navigate the complexities of global challenges.