Social Network Analysis Approach Research Articles

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.

Gender Identity and Student Perceptions of Peer Research Aptitude in CUREs and Traditional Laboratory Courses in the Biological Sciences.

While several studies have investigated gender inequities in the social learning environment of biology lecture courses, that same phenomenon remains largely unexplored in biology laboratory contexts. We conducted a mixed methods study to understand the influence of gender on student perceptions of their peers' research aptitude in introductory biology CUREs and traditional laboratory courses. Specifically, students (N = 125) were asked to complete a name generator survey at three time points across the semester. This survey asked students to list the names of peers whom they viewed as "most proficient" in the course investigations and to justify their choice via an open-ended response prompt. Using social network analysis, exponential random graph modeling (ERGM), and thematic analysis, we demonstrate that student gender identity did not influence nomination behaviors in CURE or traditional laboratory courses. However, the ERGMs reveal the presence of a popularity effect in CUREs and demonstrate that mutual nominations were more prevalent in traditional laboratory courses. Our qualitative data further provide insights into the reasons students nominated peers as proficient in CURE and traditional courses.

Harnessing Sociographs to Design Discussion Groups for Mathematics Learning: A Social Network Analysis Approach

As one of the 21st-century competencies, mathematical communication ability must be achieved through interactions created between teachers and students, and among students. Discussion groups are an alternative that generates interaction between students. Currently, not many teachers design discussion groups based on communication networks. This study aims to describe the results of Social Networking Analysis in independent mathematics learning through group discussions using graph representation. This network analysis is a complete communication network analysis with a quantitative descriptive method using UCINET Ver.6. This study uses five aspects to analyze the data, namely: (1) eigenvector centrality, (2) degree centrality, (3) closeness centrality, (4) betweenness centrality, and (5) network density. The subjects of this study were 32 students at a junior high school in Yogyakarta, Indonesia, who were selected based on suggestions from the mathematics teacher.The data in this study were collected using questionnaires, observation, and interviews. Hence, the validity and reliability of each one has been examined. According to the study, 43.8% of students' independent arithmetic learning falls into the medium category. It implies that students frequently decide on study sessions with discussion partners and take the initiative to identify and arrange the answers. Based on the data, four groups were created, each with eight pupils. This study is anticipated to serve as a benchmark for other investigations into the efficacy of discussion groups created in conformity with 21st-century skills.

Community detection and social presence in students’ discussion fora

In Distance Education (DE) the importance of community is often emphasized, as according to many experts in the field, the strong sense of community among learners improves the quality of teaching and learning. In this study, we use the Social Network Analysis (SNA) approach to detect the communities formed in the collaboration networks created by the actors’ (students and tutors) interactions in the Discussion Fora of a Learning Management System (LMS), in a Distance Learning setting within an Open University. Data from the actors’ communications in two Module Discussion Fora (MDF) are selected for creating graphs and applying appropriate algorithms, the Girvan-Newman and the Louvain algorithm, to reveal the communities and analyze their synthesis. As Discussion Fora within LMSs enhance the formation of communities, our study intends to visualize the dynamic interactions that emerge in such environments and provide the Coordinators and the Tutors of the Modules with useful information to improve the students’ learning outcomes. Such knowledge is valuable, especially in DE, where there is a lack of daily face-to-face interaction of a typical classroom. Furthermore, as social presence is essential for successful online teaching and learning, the absence of forum communities or the loose participation in such communities, from both Tutors and students, should alert the Coordinators to make suggestions and effectively manage the discussions and interactions among learners.

ANALISIS JARINGAN TAGAR #IKUTPAKDEPRABOWO-GANJAR PADA MEDIA SOSIAL MENGGUNAKAN NETLYTIC TOOLS

One of the social media platforms that has significantly impacted the Prabowo-Ganjar controversy as the presidential tandem in 2024 is Twitter. Due to the initiatives of various Twitter accounts to popularize and support the issue of Prabovo-Gangjar as the presidential candidate duo in Pilpres 2024, the hashtag #IkutPakdePrabowo-Ganjar arose and started trending on Twitter. The buzzer's part in making the Prabowo-Ganjar controversy popular, particularly on social media, The research looked at tweets that used the hashtag #ikutPakdePrabowo-Ganjar. Through the use of netlytic.org technologies, which were tracked from March 9 to March 15, 2023, the researchers made observations and gathered data. The hashtag #FollowPakdePrabowo-Ganjar encourages these two politicians to run for vice president and president in 2024. The Social Network Analysis (SNA) approach is used in this study to visualize social networks using Netlytic tools by crawling 2500 tweets' worth of data. The findings showed that the inclusion of a buzzer function might make the average data from the same caption and the conclusion from the #IkutPakdePrabowo-Ganjar tag a popular topic. As the 2024 presidential duo, there is active public discussion of Prabowo-Ganjar on Twitter. Buzzers and political activists utilize the Twitter platform to express their support, disapproval, and opinions on the subject.

Marketing Strategy Of Fast-Food Restaurants In Indonesia - Sosial Network Analysis On Twitter

Background – Fast food restaurants are a culinary business where competition is quite tight, especially in the Covid-19 era. To face competition between restaurants which is quite close, companies must have many strategies, one of which is related to the promotion strategy. Aim – This study aims to compare the marketing strategy content between Mcdonald's and Burger King and identify the focus of discussion of Twitter users on fast food restaurants. Design/ Methodology/ Approach – This research uses a social network analysis (SNA) approach with a qualitative descriptive research type. SNA is a form of social computing that extracts large amounts of data. This research uses secondary data sources from tweets with discussions of McDonal's and Burger King in 2017-2022 with data collection. Findings – The study results show that the marketing strategy related to promos carried out by Mcdonald's is Free Shipping, while Burger King's is Cashback. While on the menu, Mcdonald's innovates on the ice cream menu, and Burger King innovates on the burger menu. The marketing strategy related to taste at Mcdonald's and Burger King showed that the two restaurants had a delicious and delicious taste of the products produced by the two companies on the tongues of consumers Conclusion - Burger King's marketing strategy carried out via Twitter social media is superior to McDonlads' marketing strategy. Research implication –The research results show that Burger King is famous for the promos it provides, namely cashback where the promo can be used again when making subsequent purchases by consumers. Apart from that, the menu at Burger King is also very varied, starting from different colors and shapes of burgers, therefore Burger King can attract other consumers to buy their products. This strategy can be maintained to improve and maintain products at Burger King restaurants. McDonald's is famous for its delicious burgers, so this can increase consumer purchases, this strategy must also be maintained. Limitations – This study focuses on two company brands, namely Mcdonald's and Burger King, in this analysis using three marketing strategy criteria as keywords for data collection. The first keyword is a promo, the second is a menu, and the third is taste.

Assessment of Mars Analog Habitation Plans Using Network Analysis Methodologies

Space institutions place humans in analog environments that closely match the target environment, such as the Moon or Mars, to study space habitation. Seven Mars analog missions consisting of habitation units with published designs were selected for analysis using graph data science methodologies to provide insight into how their designers solved the challenge of living in an isolated, constrained, and distant environment. Social Network Analysis (SNA) and Label Propagation Approach (LPA) are utilized to examine the relationships between adjacent functional areas of habitations. The paper presents the final documentation that will be used as a design framework to generate layouts for a habitation project.

Micro-Celebrities or Teacher Leaders? An Analysis of Spanish Educators’ Behaviors on Twitter

Social networking sites have become affinity spaces for teachers. Many teachers use them with different intentions and motivations, including learning. On social media platforms there are active teachers who have developed a certain leadership and recognition from many teachers. In some areas, like marketing or fashion, people with influence are called influencers. This paper investigates who they are, how their network is configured and how they perceive themselves. The questions that directed our research were: Who are the predominant Spanish teacher leaders on Twitter? What is the network structure that characterizes them? What perceptions do these teacher leaders have about their role and its impact on their professional development as teachers and others? This study has two distinct but interrelated phases. We investigated the structure and relationships among 54 Spanish teacher leaders. Using a social network analysis (SNA) approach, through the analysis of the social behavior of these teachers on the social network Twitter, we first identify educational profiles who have a high degree of centrality in the network. These are teachers who are recognized as opinion leaders by a significant proportion of their fellows. In addition to the degree of centrality that tells us how relevant a user is in a specific digital community, we identified teachers who play a key role in the circulation of information in the network studied. In some way, these teachers share common characteristics with activists in other fields. Of the 54 teachers, we selected 20 who were then interviewed. The findings demonstrate that they don't consider themselves micro-celebrities or influencers. We found a lack of identification not only with the term, but also with the image of an influencer which was understood as banal, superficial, commercial, and far from what they do in social networks.These teachers develop their identity as new digital artisans who foster a culture of collaboration and create affinity spaces that allow informal learning. Their motivation is intrinsic, through recognition and prestige among other teachers, which leads them to build a kind of constructivist leadership.

The Main Strategy of MSMEs Able to Survive in the Upcoming Latest Variant of Covid-19

Research on the Main Strategy for MSMEs to Survive in the Face of the Latest Variants of Covid-19 in the Future is very useful research in dealing with similar problems if it happens again. This research is a qualitative research using the Netnography method with the Social Network Analysis approach through the MSME Business Actors Group on Facebook and WhatsApp. Data collection was carried out using a technical questionnaire using the Google Form application which was distributed on the MSME group's social media. The results of the study show that several strategies implemented by MSME business people have made them able to survive in the midst of a crisis storm during the Covid-19 pandemic. This research is very useful for business people and researchers in the future if there is a pandemic problem and other similar problems.

Single-cell communication patterns and their intracellular information flow in synovial fibroblastic osteoarthritis and rheumatoid arthritis

BackgroundSynovial fibroblasts are critical for maintaining homeostasis in major autoimmune diseases involving joint inflammation, including osteoarthritis and rheumatoid arthritis. However, little is known about the interactions among different cell subtypes and the specific sets of signaling pathways and activities that they trigger. MethodsUsing social network analysis, pattern recognition, and manifold learning approaches, we identified patterns of single-cell communication in OA (osteoarthritis) and RA (rheumatoid arthritis). ResultsOur results suggest that OA and RA have distinct cellular communication patterns and signaling pathways. The LAMININ (Laminin) and COLLAGEN (Collagen) pathways predominate in osteoarthritis, while the EGF (Epidermal growth factor), NT (Neurotrophin) and CDH5 (Cadherin 5) pathways predominate in rheumatoid arthritis, with a central role for THY1 (Thy-1 cell surface antigen) +CDH11 (Cadherin 11) + cells. The OA opens the PDGF (Platelet-derived growth factors) pathway (driver of bone angiogenesis), the RA opens the EGF pathway (bone formation) and the SEMA3 (Semaphorin 3A) pathway (involved in immune regulation). Interestingly, we found that OA no longer has cell types involved in the MHC complex (Major histocompatibility complex) and their activity, whereas the MHC complex functions primarily in RA in the presentation of inflammatory antigens, and that the complement system in OA has the potential to displace the function of the MHC complex. The specific signaling patterns of THY1+CDH11+ cells and their secreted ligand receptors are more conducive to cell migration and lay the foundation for promoting osteoclastogenesis. This subpopulation may also be involved in the accumulation of lymphocytes, affecting the recruitment of immune cells. Members of the collagen family (COL1A1 (Collagen Type I Alpha 1 Chain), COL6A2 (Collagen Type VI Alpha 2 Chain) and COL6A1 (Collagen Type VI Alpha 1 Chain)) and transforming growth factor (TGFB3) maintain the extracellular matrix in osteoarthritis and mediate cell migration and adhesion in rheumatoid arthritis, including the PTN (Pleiotrophin) / THBS1 (Thrombospondin 1) interaction. ConclusionIncreased understanding of the interaction networks between synovial fibroblast subtypes, particularly the shared and unique cellular communication features between osteoarthritis and rheumatoid arthritis and their hub cells, should help inform the design of therapeutic agents for inflammatory joint disease.

Framing a social network analysis approach to understanding reputational power in the water governance of Johor, Malaysia

Abstract The challenge of collaborative water governance often lies in the complexity of the networks involved in its processes, particularly in understanding the location of power and how the reputational power can be executed for policy decisions. A case study of the state of Johor, Malaysia, was done with the goal of figuring out a method for mapping out reputational powers in the network of actors involved in the water governance of the state. To achieve this goal, this study deconstructs the different facets of the state’s water governance system by outlining the spatial, operational, and legal boundaries of various agencies. The fundamental issues identified through this step are the complexity that leads to fragmented water governance. A research framework is thus proposed, derived from a qualitative approach whereby through in-depth interviews, respondents are asked to rank the water-related agencies based on their perceived influence. These rankings derived from qualitative interviews are given weights and subsequently measured using parameters such as density and in-degree centrality to provide quantitative evidence of the reputational powers held by actors in the water governance network. The study supports the future use of the reputational power research framework to achieve collaborative water governance solutions.

Who is responsible for developing energy policy interventions in Mozambique? A stakeholder analysis and social network analysis

Purpose This study highlights the crucial significance of stakeholder participation in the creation of a comprehensive energy and electrical master plan for Mozambique. The purpose of this study is to deliver a practical insights that transcend theoretical concerns by digging into the subtleties of stakeholder relationships and strategic collaborations, paving the path for pragmatic and meaningful solutions that connect with real-life conditions. This debate lays the groundwork for educated decision-making, propelling Mozambique’s energy industry towards a more sustainable and prosperous future. Design/methodology/approach The study used a combined approach of stakeholder analysis (SA) and social network analysis (SNA) to enhance our understanding of the stakeholder landscape in Mozambique’s energy sector. This methodological approach offers a unique vantage point to examine the individual stakeholders’ roles and the intricate web of connections, partnerships, collaborations and information-sharing activities. By integrating SA and SNA, this study aims to provide a more comprehensive and dynamic depiction of stakeholder interactions, contributing methodologically to the existing body of literature. Findings The findings also highlight the need to develop frameworks that promote private investment and joint endeavours with entities such as Cahora Bassa Dam/Mozambique Transmission Company. A consistent legal framework ensures uniform performance and a robust monitoring system for ongoing projects, improving accountability and progress tracking. Furthermore, the discussion includes enhancing the competence of the regulatory agency regulating the electricity industry. This includes tackling complex concerns with electricity pricing and other regulatory aspects relevant to private investment. A highly empowered regulatory agency is critical to creating an atmosphere conducive to long-term private sector involvement. Research limitations/implications While the study emphasises the need to integrate multiple stakeholders, it may not detail specific issues or impediments that may develop during the engagement process. Additional research could look into potential tensions or barriers to effective collaboration. Furthermore, the study emphasises the necessity of addressing environmental impacts; it must thoroughly examine specific environmental concerns such as carbon emissions, deforestation or renewable energy possibilities. Future research could assess the suggested policies’ environmental impact more extensively. Additionally, while the conclusion briefly mentions economic prosperity, a more thorough consideration of the possible economic and social implications of various energy policies could provide a greater understanding of their practicality and potential benefits. Practical implications In terms of practical contributions, this study aspires to shed light on how stakeholder interactions can shape energy policy interventions that ensure reliable and affordable energy sources for economic development and societal well-being. By unveiling the complex network of relationships and partnerships, this study seeks to provide actionable insights for policymakers, industry players and other stakeholders involved in Mozambique’s energy sector. By taking this action, this research aims to pave the way for more effective and inclusive energy policies that align with circular economy principles, thus addressing a critical need in scholarly discourse and practical implementation. Originality/value The study underscores the critical role of energy stakeholders in shaping energy policies and projects, given their influential positions and impact on decision-making processes. While existing literature acknowledges this influence, a discernible research gap exists in comprehensively understanding how stakeholder interactions and collaborations in the energy sector affect policy interventions within a context such as Mozambique. This study seeks to bridge this gap by delving into the intricacies of stakeholder involvement and its implications for energy policy development in Mozambique.

Ten Clusters Of Rural Development Articles Using Social Network Analysis

This article presents an in-depth analysis of Rural Development literature through a Social Network Analysis approach. The purpose of the research is to identify and categorize articles related to Rural Development into ten main clusters, focusing on the patterns of interaction and relationships between them. By applying advanced social network analysis methods, this research details the network structure emerging from this literature, revealing how the articles are interconnected and form groups based on relevant themes or concepts. Additionally, articles that have a central role in the network are also identified, highlighting their significant contribution to the understanding of key aspects of Rural Development. The results showed that the study highlighted gaps that indicate the direction of the future research agenda in rural development, with a focus on inter-regional collaboration in Asia and developing countries. Despite limitations, including limited databases and author subjectivity, this study recommends expanding the sample with broader keywords and databases and benchmarking with other bibliometric analysis tools in the future.

An organizational form framework to measure and interpret online polarization

ABSTRACT As social media becomes more ingrained in political and social discourse around the world, the need for systematic measures and interpretations of online polarization grows. In this work, we introduce five major organizational forms of community-level polarization and nine subforms to support comparison of community dynamics in controversial discussions across time, platforms, languages, and domains. We propose a multi-dimensional social network analysis approach to characterize the structure within and between ideologically opposed communities and evaluate the organizational form. Through three case studies, we demonstrate applying the proposed methodology on two social media platforms (Twitter and Reddit) and levels of conflict (topic and partisanship). This work has implications for depolarization interventions and policies on social media.

Solidarity Entrepreneurial Ecosystem in The Effort Towards Modern Cooperatives: A Social Network Analysis Approach

Solidarity Entrepreneurial Ecosystem in The Effort Towards Modern Cooperatives: A Social Network Analysis Approach

Data Analysis of Physician Competence Research Trend: Social Network Analysis and Topic Modeling Approach.

Studies on competency in medical education often explore the acquisition, performance, and evaluation of particular skills, knowledge, or behaviors that constitute physician competency. As physician competency reflects social demands according to changes in the medical environment, analyzing the research trends of physician competency by period is necessary to derive major research topics for future studies. Therefore, a more macroscopic method is required to analyze the core competencies of physicians in this era. This study aimed to analyze research trends related to physicians' competency in reflecting social needs according to changes in the medical environment. We used topic modeling to identify potential research topics by analyzing data from studies related to physician competency published between 2011 and 2020. We preprocessed 1354 articles and extracted 272 keywords. The terms that appeared most frequently in the research related to physician competency since 2010 were knowledge, hospital, family, job, guidelines, management, and communication. The terms that appeared in most studies were education, model, knowledge, and hospital. Topic modeling revealed that the main topics about physician competency included Evidence-based clinical practice, Community-based healthcare, Patient care, Career and self-management, Continuous professional development, and Communication and cooperation. We divided the studies into 4 periods (2011-2013, 2014-2016, 2017-2019, and 2020-2021) and performed a linear regression analysis. The results showed a change in topics by period. The hot topics that have shown increased interest among scholars over time include Community-based healthcare, Career and self-management, and Continuous professional development. On the basis of the analysis of research trends, it is predicted that physician professionalism and community-based medicine will continue to be studied in future studies on physician competency.

The role of social networks in the development of rural community-based eco-industry

The lack of eco-industrial development in rural areas demonstrates how isolated these people are from outside networks and resources. The ecological industrial management of clove leaf essential oil run by rural communities within the network is further revealed and analyzed in this study using the social network analysis approach. The findings of this study show how networks are crucial to understanding interactions between subgroups, density, and centralization. This study also implies that strengthening internal social networks inside rural communities, particularly subgroup interactions, must go hand in hand with initiatives to broaden external social networks. While preserving the sustainability of rural ecosystems, strengthening the social networks of rural eco-industries will also create new employment opportunities.

Discovering Key Actors and Opinion Leaders on Twitter’s Start-Up and Entrepreneurship Topics Trending: A Social Network Analysis Approach

The topic of start-ups and entrepreneurship has been widely discussed on social media to disseminate information while serving as a digital marketing platform. Unfortunately, researchers and practitioners interested in analyzing social networks to gain business advantage through digital platforms still need to be expanded. This paper analyzes networks on social media to find important actors and opinion leaders on trending start-up and entrepreneurship topics. Data analytics is performed using one of the most extensive social media, Twitter. Several visualizations of the social network of these actors are then displayed using specific network visualization applications. The results are discussed by analyzing the main attributes in the network, namely degree, centrality, modularity, and word cloud, which can lead us to discover important attributes in the network: main actors, opinion leaders, groupings of actors according to topics discussed, and specific terms that are trending topics. This paper contributes to digital marketing practitioners and social network analysis studies in related fields with a concise and duplicable methodology. Further research is recommended to work more extensively with more representative data from multiple networks to analyze these topics in more depth.

Knitting Circular Ties: Empowering Networks for the Social Enterprise-led Local Development of an Integrative Circular Economy

Circular economy (CE) discourse primarily focuses on business-as-usual and resource-related economic processes whilst overlooking relational-spatial aspects, especially networking for local development. There are, however, many mission-driven social enterprises (SEs) engaging in short-loop activities at the neighbourhood and city scales (e.g., reuse, upcycling, refurbishing or repair). Such localised activities are often overlooked by mainstream policies, yet they could be vital to the local development of the CE into a more socio-environmentally integrated set of localised social structures and relations. This paper examines the role of SEs, their networks and structures in building a more socially integrated CE in the City of Hull (UK). Drawing upon the Social Network Analysis approach and semi-structured interviews with 31 case study SEs representing variegated sectors (e.g., food, wood/furniture, textiles, arts and crafts, hygiene, construction/housing, women, elderly, ethnic minorities, homeless, prisoners, mentally struggling), it maps SEs’ cross-sector relationships with private, public and social sector organizations. It then considers how these network constellations could be ‘woven’ into symbiotic relationships between SEs whilst fostering knowledge spillovers and resource flows for the local development of a more socially integrative CE. We contend that integrating considerations of SEs’ organizational attributes and their socio-spatial positioning within networks and social structures offers new insights into the underlying power-relations and variegated levels of trust within the emergent social-circular enterprise ecosystem. These aspects are presented in the form of a comprehensive heuristic framework, which reveals how respective organizational and network characteristics may impact SEs’ performance outcomes and, ultimately, a more integrated approach to local CE development.

Novel method for ranking batsmen in Indian Premier League

Sports analytics have benefited immensely from the growth and popularity of artificial intelligence and machine learning. These techniques enable sports analysts to evaluate player performance more effectively. A literature review of player performance evaluation methods shows the need to develop a new performance evaluation index for Twenty20 (T20) cricket. A novel framework was proposed to evaluate batsman strength based on individual performance, role in the team, and team interactions. Traditionally, proposed ranking systems are derived from static networks, that is, the aggregation of game results over time. However, the scores of the players (or teams) fluctuate over time. Intuitively, defeating a renowned player during peak performance is more rewarding than defeating the same player during other periods. To account for this, we propose a new method and apply it to the T20 format Indian Premier League. The method serves three main purposes: First, it creates a new performance index for players to rank them more accurately and effectively. Second, the players are clustered based on their expertise. In the third phase, a social network analysis approach is applied to visualize and analyze crickets as a network to gain better insights into players’ team interactions. This novel approach is a helpful index for sports coaches, analysts, cricket fans, and managers to evaluate player performance and rank for future aspects.