Social Network Analysis Approach Research Articles

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.

Identification and evaluation of collaborative relationships of internal project stakeholders: a social network analysis approach

PurposeThe present research is trying to construct the network of relationships between different department of an organization during the design and development of car engine. Analyzing the structure of the network, finding the patterns of collaborations, and determining the important departments are the main purposes of the present research.Design/methodology/approachImproving relationships during a project life is an effective way to enhance employee performance in project-oriented organizations. This paper examines the collaborative relationships between internal project stakeholders through social network analysis (SNA) in a project for the design and development of car engine. In the first step of the research, the network of internal stakeholders was studied based on collaboration in the common activities performed by the resources. Then, the network of correspondences between internal stakeholders was studied. Finally, the two networks were integrated into a single network.FindingsIn the integrated network, the “fuel and combustion department” had the largest degree centrality (i.e. highest collaboration with others). The “integration department” was found to have the highest closeness centrality (i.e. more rapid access to other nodes). Furthermore, the “procurement department” had the highest betweenness centrality (i.e. the most strategic department). Our results revealed the potential capabilities of SNA method for the project management in the vehicle industry.Originality/valueThe obtained results of the present research show us the value of applying SNA methods and concepts to analyze the inter-organizational network of the Project Stakeholders relationship.

Mapping Policy Actors Using Social Network Analysis on Integrated Urban Farming Program in Bandung City

This study aimed to produce a network structure in Integrated Urban Farming Program in Bandung City to map the involved policy actors to realize a food-smart city. In this study, a mixed method was used with an exploratory sequential strategy involving policy actors from the government, private sector, academia, community, and mass media. To obtain a network structure in Integrated Urban Farming toward determining the most important actors, the Social Network Analysis (SNA) approach was also employed through the Gephi application. From this context, the structure emphasized four dimensions, namely Degree, Betweenness, Closeness, and Eigenvector Centralities. The results showed that the actor with the most connections (degree of centrality) and best communication control (betweenness centrality) is Parahyangan Catholic University (academic). At the same time, the actor that plays the most important role (eigenvector) is at the lower level of the government’s Sub-District and Urban Village. This study is useful for explaining the importance of the position of actors in the urban farming policy network, which is the key to the success of a program.

A social network analysis approach to estimate export disruption spread in the US during the Covid-19 pandemic: how policy response and industry ties relate

We examine how the Covid-19 pandemic led to the propagation of export disruptions on a state-by-state basis using a social network analysis model. We measure the impact of import disruptions, Covid-related hospitalizations, subsequent policy responses, and structural network effects on economic outcomes. In addition to examining contemporaneous effects, we include lagged policy response variables to determine their effect on disruption recovery trends. Findings suggest that disruptions cluster along shared industry connections. The results are consistent with previous work that shows that non-pharmaceutical policy interventions had limited contemporaneous and medium-term effects on trade flows.

Twitter Social Network Interaction As Customer Engagement In Competition For E-Commerce E-Health Performance In Indonesia

Background – The presence of e-commerce e-health is a societal solution to health needs in the era pandemic. Social distancing rules cause considerable restrictions on community socialization, so they use social media alternatives to share experiences. That matter causes customers to talk about the performance of digital e-health services and create consumer engagement. Public opinion and ratings on social media become data information analyzed to improve service quality. 
 Aim – This study aims to identify customer conversations on Twitter about e-commerce e-health to see its performance and compare e-health results networks in Indonesia.
 Design / methodology / approach – The research method in this study is the Social Network Analysis (SNA) approach and descriptive meaning to get the results of the formulated goals.
 Findings – The results of this study showed that pre-pandemic e-health users in Indonesia were more dominant in utilizing psychologist and psychiatric consultations and buying easy and practical medicines. During the pandemic, customers more often used doctor consultations related to symptoms and treatment of Covid-19, drugs and vitamins for self-isolation, supported by online payments. 
 Research implication – This research contributes to e-health companies in Indonesia regarding suggestions for utilizing SNA through customer interaction on social media to improve the performance and competition of e-health services and determine superior strategies. 
 Limitations – This research explores data only from social media Twitter, based on the material for data visualization is only in text. The scope of the study is only in the health business, so it can further develop in other sectors.

A new governance model for the conservation and enhancement of Italian ancient transhumance routes

Transhumance routes mark the natural path followed by herds during their seasonal movements. These routes are disappearing in many European countries. In Italy, a few fragments survive in Molise, in southern Italy, called Tratturi and run along grassy paths. The Tratturi are considered to be of archaeological, economic and landscape interest, sources of cultural and environmental attraction, protected by a national law. However, the landscapes connected to the Tratturi are disappearing both as a consequence of non-use and as a consequence of the advancement of wooded areas, and this poses a problem related to the governance system that involves many stakeholders, both at international, national and local level. The study, through the use of the combined approach of Stakeholder Basic Analysis and Social Network Analysis, identifies the role of the stakeholders involved, their power, their interest and their ability to support the decision-making system. Furthermore, the paper uses multivariate statistical analysis to detect the key stakeholders. A new model of governance, allowing to preserve the Tratturi and to enhance the services they can provide, is introduced, and it is named Authority for the Conservation and Enhancement of Tratturi (ACET). This study can help to identify appropriate management models for ancient routes based on all stakeholders involved, and more generally to implement shared and co-responsible planning choices in socio-ecological systems.

Diagnosis of Rural Development Processes Based on the Stock of Social Capital and Social Networks: Approach from E-I Index

Europe’s rural areas have suffered a continuous loss of human and economic capital from the beginning of the 20th century to the present day. In an attempt to alleviate the effects of this dynamic, the European Union has implemented the LEADER rural development programme since the 1990s (Liaisons Entre Actions de Développement de L’Economie Rurale). Among the many objectives of this policy, the social articulation of its populations stood out as a way of strengthening development processes. This article aims to provide a methodological approach to analyse and quantify the stock of social capital (SC) present in the social networks of rural areas after more than thirty years of European rural policy. Based on 160 interviews with stakeholders linked to rural development processes in rural areas of Spain and England from institutional, economic, social and technical sectors. The methodological approach of Social Network Analysis (SNA) has been used, and within this, the study of SNA indicators and the analysis of the E-I index have been integrated in order to analyse the stock of internal (bonding) and external (bridging) SC. The conclusions of this study clarify the role of stakeholders and their contribution to the stock of SC. The studied rural areas present a balance in internal and external relations, which shows a high stock of SC and an encouraging scenario for the development processes and, thus, for the success of the LEADER programme. Nevertheless, the participation of the actors in the LEADER programme in Spain still shows a worrying project class.

A Study on Chinese Collaborative Governance System of Public-Private Partnership (PPP): Using the Social Network Analysis Approach

A Study on Chinese Collaborative Governance System of Public-Private Partnership (PPP): Using the Social Network Analysis Approach

Curtailing fake news creation and dissemination in Nigeria: Twitter social network and sentiment analysis approaches

Influencers create and facilitate dissemination of information in a network and can shape the attitudes and beliefs of members of a social network. Identifying the influencers and their relations, as well as the sentiment of tweets being disseminated in the network on some selected keywords can help curtail fake news creation and dissemination in the network. This study uses a sequential mixed-methods design with a quantitative method followed by qualitative methods. The quantitative data were collected using Mozdeh big data analysis software. Mozdeh software was used to collect tweets through Twitter’s Streaming application programming interface to build a corpus of tweets, collected from 1 January 2016 to 30 June 2021. The study found two major actors/influencers involved in the creation and dissemination of fake news on the tweeter social network studied. The study further found overall Av. Pos. − Av. Neg. was −0.9935. Data collected were on some specific trending keywords on a particular region in Nigeria. Identifying and monitoring the tweets of influencers in a network can aid in debunking fake news immediately after dissemination and discourage the use of offensive words in tweets. The results revealed major influencers responsible for creating and disseminating fake news on some trending issues in Nigeria.

Historical Co-offending Networks: A Social Network Analysis Approach

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

Digital Innovation Ecosystem on Digital Entrepreneur

This study aims to produce a network structure in the digital innovation ecosystem to determine the position of each actor involved in it as an effort to support digital innovation in digital startups in West Java. This study uses a mixed method with an exploratory sequential strategy involving digital startup actors in West Java. To get the network structure in the digital innovation ecosystem in order to find out the actors who play the most important roles, the research uses a social network analysis approach by utilizing the Gephi application. The network structure is based on four dimensions of centrality. The results of this study confirm that the actor with the most connections (degree centrality), as well as the most important actor (Eigen centrality), in the digital innovation ecosystem in West Java is PT. Sharing Vision. A framework of digital innovation ecosystem is developed to explain the importance of actor positions in the digital innovation ecosystem.

Cold supply chain of leafy green vegetables: a social network analysis approach

PurposeCold supply chain technology is critical for extending the shelf life of perishable leafy green vegetables. This study aims to investigate the concept of managing leafy green products using cold supply chain technology and visualise the findings.Design/methodology/approachUsing expert interviews and data visualisation approaches, this study examines how organisations deal with the complexity of cold supply chain processes and networks. Thematic data analysis was conducted. Two types of software were used to accomplish the research objectives. The first software used AntConc version 3.5.8 with word frequency (N-gram) analysis, whereas the second software, VOSViewer offered co-occurrence network visualisation and cluster analysis.FindingsThe findings show that the appropriate design of cold chain technology is critical in ensuring the freshness and quality of leafy green vegetables. The primary goal of managing the complexity of the cold supply chain is to achieve product freshness and energy efficiency. Regardless of the importance of energy efficiency, cold supply chains require warehouse management solutions for transportation and storage.Practical implicationsThis study found that proper design and selection of appropriate technology in the cold supply chain have driven the companies to improve the firms’ competitive advantage while delivering the best quality of perishable leafy green food products. In addition, the freshness, quality, safety, and health of leafy green vegetables will be determined by the company’s capacity to handle long-distance transportation and select the appropriate distribution channels and storage. Warehouse management system technology was found to be secondary compared to cold chain technology, although distribution and warehousing practices are critical for supply chain performance.Originality/valueThis study has established the conceptual indicators based on best practices and outcomes for the cold supply chain. This study argued that cold supply chain management and performance should be monitored independently. Furthermore, the theory of technological adoption can be expanded to include product nature as a driver. Finally, this study has established cold chain best practices based on a perishable supply chain perspective. The findings of this study can promote healthy foods to solve zero hunger and achieve sustainable development goals. Although this study demonstrates that technology improves supply chain practises, cold storage and logistics benefit the most from technological advancements. In contrast, non-cold supply chains benefit from technology-driven improvements in performance.

Assessing athlete leadership and cohesion using a social network analysis approach.

The study of athlete leadership has gained momentum over the past 15 years and is recognized as a vital component of team performance. Specifically, athlete leadership has been most studied with regards to its impact on the outcome of cohesion. As a result, a current gap in this area of research is the analysis of attribute data, such as tenure and self-reported athlete leadership, and how this attribute data is related to outcomes, such as cohesion. However, much of current research examining this relationship has utilized traditional statistical methods, limiting interpretation of data because team members are inherently interdependent. One approach that considers the interdependence of team members is social network analysis (SNA). SNA facilitates the study of social structures within networks of people, such as a sports team, as well as individual attributes influencing or being influenced by the network. The present study used SNA to examine athlete leadership and cohesion within a sports team of 22 female professional hockey players. Participants self-reported tenure, completed a self-rated athlete leadership questionnaire, and rated each of their team members on network variables of athlete leadership and cohesion. The results showed that high network density and low degree centralization was found for both athlete leadership and cohesion networks, with high indegree centralities for each team member. Further, a strong correlation was found between the athlete leadership and cohesion networks (p < 0.001), indicating a positive relationship between the athlete leadership ties and the cohesion ties. Lastly, significant correlations were found between self-rated athlete leadership and the networks of athlete leadership and cohesion. Together these data suggest that a cohesive team shares leadership responsibilities with many ties between teammates.

Using social network analysis approach in developing rural psychiatrist workforce

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

Analisis Sentimen dan Jaringan Komunikasi Respon Ketua BPOM Peny Lukito Kasus Gagal Ginjal Akut Pada Anak dalam akun Youtube Kompas.com

A crisis can endanger the reputation and performance of an institution or agency, especially government property. One of the causes of a crisis is the emergence of unexpected events with wide-reaching impacts that occur quickly. This also elicited various responses from various circles. Facing the development of information technology, especially social media, crisis situations can also be influenced by various responses from netizens that appear on social media. Indonesia is experiencing a crisis situation related to the phenomenon of health problems in the form of acute kidney failure that occurs in children which is allegedly caused by the dangers of cough syrup-type drugs by the dangerous chemicals ethylene glycol and deethylene glycol. Responding to this phenomenon, Chairperson of the Food and Drug Supervisory Agency (BPOM) Mrs. Peny Lukito held regular press conferences with the main agenda related to the current situation in handling this case. This study aims to look at the formation of a communication network and sentiment analysis from netizens towards the response of the BPOM leadership using a social media network analysis approach on the Youtube channel with the Kompas.com account broadcast live online. The findings in this study are that Peny Lukito as the head of BPOM received negative responses from netizens because they considered him negligent and transferred responsibility to other parties.

Identifying influential countries in air pollution control technologies: A social network analysis approach

Clarifying the spatial correlation network of country–level air pollution control technology (APCT) is essential for transregional collaborative emission reduction in global warming. Previous research mainly focused on identifying the network structures of green technology linkages in a single country or region. In reality, cross–border technological cooperation has become a strategy for countries to achieve technological breakthroughs, and non–adjacent countries can be interconnected. Based on 217,392 patents, this study uses the Social Network Analysis method and Quadratic Assignment Procedure to discuss the spatio-temporal evolution and influence mechanisms of 57 countries’ APCT spatial correlation network from 1990 to 2020. The results indicate the following: (1) The network density in APCT decreased from 0.428 to 0.355 between 1990 and 2020, and the overall network presents prominent core–periphery structural features. The developing countries accounted for 44.44% of the core area countries. (2) The United States and Canada, the United Kingdom, Germany, China, and Japan are at the center of the Americas, Europe, and Asia. (3) Narrowing the gap in greenhouse gas emissions in manufacturing industries and construction contributes to forming potential routes of multinational cooperation; however, the role of geographical distance becomes insignificant (0.282). Lastly, a multicenter knowledge flow network should facilitate global knowledge transfer, absorption, and sharing.

Leadership and contagion by COVID-19 among residence hall students: A social network analysis approach

University students have changed their behaviour due to the COVID-19 pandemic. In this paper, we describe the characteristics of PCR+ and PCR- nodes, analyse the structure, and relate the structure of student leaders to pandemic contagion as determined by PCR+ in 93 residential university students. Leadership comes from the male students of social science degrees who have PCR +, with an eigenvector centrality structure, β-centrality, and who are part of the bow-tie structure. There was a significant difference in β-centrality between leaders and non-leaders and in β-centrality between PCR+ and non-leaders. Leading nodes were part of the bow-tie structure. MR-QAP results show how residence and scientific branch were the most important factors in network formation. Therefore, university leaders should consider influential leaders, as they are vectors for disseminating both positive and negative outcomes.

ANALYSIS OF "MIXUE" COMMUNICATION NETWORK AS ELECTRONIC WORD OF MOUTH (E-WOM) USING SOCIAL NETWORK ANALYSIS

Netizens upload the keyword "Mixue" on Twitter, which can become an electronic word of mouth (E-WoM). E-WoM is one of the dominant factors influencing purchase demand for a product. Using the keyword "Mixue" to become a trending topic creates a communication network to disseminate information related or not to Mixue. This study aimed to determine the distribution of the "Mixue" network as a medium for electronic word of mouth using Social Network Analysis (SNA). The theory used is computer-mediated communication. The research method is quantitative with the SNA approach. Researchers crawled data on 10,000 tweets on December 27, 2022, when the keyword "Mixue" became a trending topic. The researcher used the application. The results showed that the "Mixue" communication network involved 7,702 actors and 8,391 conversations. @handokotjung became an important actor after posting a humorous tweet about Mixue's expansion in Indonesia. The tweet achieved 3.3 million views, 2,277 replies, 13.6K retweets, 2,682 excerpts retweeted, and 67.5K likes. The other actors also got into the conversation regarding Mixue. The perpetrators communicate with each other by replying, retweeting, retweeting quotes, or uploading their tweets, which can be electronic word-of-mouth (E-WoM) media accessed by anyone without exception. Mixue can use social media and impoertant actors to increase people's buying interest in Mixue