Social Network Analysis Perspective Research Articles

Clustering Product Development Project Organization From the Perspective of Social Network Analysis

In product development (PD) organizations, coordinating technical dependencies among teams with different expertise in overlapping processes is a fundamental challenge. This article takes a more sophisticated approach than prior methodologies to improve coordination via organizational clustering, by accounting for both team structural and attribute similarity from the perspective of social network analysis. We built models to quantify the impact of the overlapping processes on the interaction strength among PD teams, which we then used to construct structural similarity by combining tie strength and social cohesion among teams via the design structure matrix. To evaluate the organization network, we propose social embeddedness-related centrality indices within (intracluster) and across (intercluster) team groupings. To facilitate knowledge sharing, we base team attribute similarity on product- and process-related expertise among teams. We integrate the modularity index and an improved silhouette index to find an optimal number of clusters, which we then incorporate with team similarity measures as inputs to a spectral clustering algorithm. An industrial example illustrates the proposed model. The clustering results reinforce several managerial practices but also yield new insights, such as how to measure similarity among teams based on organizational network characteristics and how structural and attribute similarities impact the optimal organizational structure.

Difficulties and challenges for admission to the position of schools inspector in Spain and early career development

This article presents research that analyzed the most significant needs, difficulties and problems for admission into Spain’s school inspectorates, the expectations of new inspectors and the challenges they face in their assessment of different school settings in the Spanish educational system. Firstly, the research addressed the central questions of school inspection and supervision in the European Union, then a methodology was applied based on virtual ethnography and the reticular-categorical approach to network analysis, with matrix representations and social graphs devised using UCINET and yED Graph Editor visor. This methodological approach was used to analyze the opinions of 140 students between 2017 and 2019 enrolled on the only Masters course in Spain dedicated to schools inspection and supervision, delivered by UNED (Spain’s National Distance Education University). Their open responses to a questionnaire, and course forum interaction, were analyzed from the Social Network Analysis perspective. The results show that the main difficulties, challenges and needs coalesced around four central nodes: the politicization of tribunals and the entrance exam format, the lack of training courses for potential inspectors, the absence of a national study pathway for potential inspectors as an entry requirement, and the need for training in supervision techniques to perform their functions as inspectors.

Research on the relevant characteristics of occupational disease diagnostic criteria in China from the perspective of social network analysis

Objective: To analyze the normative references in occupational disease diagnostic criteria and explore the relevant characteristics of occupational disease diagnostic criteria in China, aiming to provide the basis for improving the system of occupational disease diagnostic criteria. Methods: From January to March 2021, the text and normative references of occupational disease diagnostic criteria were retrieved, and the database was established with Excel 2013, and the data were analyzed with SPSS 22.0 software and Ucinet 6.0 software. The distributions of normative references were statistically analyzed by frequency analysis. The network density and centrality of occupational disease diagnostic criteria were analyzed by social network analysis. The network topology of relevant relationship network of occupational disease diagnostic criteria was drawn. Results: Among 115 occupational disease diagnostic criteria, 105 criteria cited 146 normative references, a total of 431 times. The normative documents cited more frequently were GB/T 16180 (91 times), GBZ 76 (37 times) and GBZ 73 (23 times). The number of normative references in GBZ 188 and GBZ/T 238 was large, 87 and 13 respectively. The results of social network analysis showed that the network density was 0.0281. The relative degree centrality was 3.089, and the top three criteria were GB/T 16180 (55.152), GBZ 188 (53.333) and GBZ 76 (23.636). The closeness centrality was 7.773 and the top three criteria were GB/T 16180 (8.735), GBZ 188 (8.730) and GBZ 76 (8.333). The betweenness centrality was 0.824 and the top three criteria were GBZ 188 (38.836), GB/T 16180 (38.301) and GBZ/T 238 (10.407). And GB/T 16180, GBZ 188, GBZ 76, GBZ 73 and GBZ 59 were at the core of the network topology of relationship network of occupational disease diagnostic criteria. Conclusion: The network density of occupational disease diagnostic criteria in China is low, and the relevant relationship is not close. GB/T 16180, GBZ 188, and GBZ 76 are node standards and should be the focus of the next standard implementation tracking.

On the Co-authorship network analysis in the Process Mining research Community: A social network analysis perspective

As a noticeable focal point in the field of analysis tools, Social Network Analysis (SNA) has received much interest to model real-world phenomena in a variety of domains, e.g., research collaboration and have a better perception of social events. Research collaboration refers to the main procedure of integrating disorganized capabilities and knowledge into novel research techniques and ideas. The invaluable analytical indicator of research collaboration is the outcome of analyses of scientific articles developed as its achievements. This article investigates collaboration and co-authorship in the Process Mining field based on the already published dataset consisting of 1278 papers which are selected by their keywords or snowball technique. According to crucial results, the co-authorship network developed among researchers features a number of the properties of the scale-free networks. Additionally, using mathematics, it has been proven that the acquired network is small world network. Besides, most central authors are determined by integrating four centrality measures include closeness, degree, eigenvector, and betweenness via TOPSIS. This network has been compared and reviewed in the absence/presence of such actors. In accordance with the obtained affiliation of the high-ranking authors, TU/e university plays the most pivotal role in Process Mining promotion.

Jumping the Gap: developing an innovative product from a Social Network Analysis perspective

The creation of new products from the bonding between science and industry incorporates aspects that can be reviewed based on the nature of the academy-business bonds, the structure of the science & technology systems, or the models of academy-industry articulation. This research proposes a novel approach based on the analysis of a case study and uses the perspective of social network analysis to reconstruct the academic-state-business links necessary for the generation of innovation. The main source of data was the narration of a key informant, taking the innovative product as the ego of the network. Knowledge circulation pathways were identified, as well as subgroups of nodes whose attributes are associated with the product's transfer, development, and financing actions. The actor with the highest degree of centrality in the network belongs to the academic sector, and he operated as a bridge that bonded the academic and state sectors. This could be an indication that the promotion of this type of profile within the academic sector could boost the development of innovative products based on scientific knowledge.

Participation and transdisciplinarity in Ecohealth: a social network analysis perspective

Resumo A Ecosaúde usa abordagens participativas e transdisciplinares com o intuito de compreender as inter-relações entre os componentes dos sistemas socioecológicos e como estas interações influenciam a saúde das populações humanas. O objetivo do artigo é usar a Análise de Redes Sociais (ARS) para entender o papel das relações de colaboração entre os diversos atores envolvidos nos processos participativos e transdisciplinares em projetos de Ecosaúde. Apresentamos um conjunto de indicadores de ARS para caracterizar a evolução e a equidade de participação e diferenciar a inter e a transdisciplinaridade. A análise foi feita com base na rede de colaboração entre os atores da Iniciativa de Liderança em Ecosaúde para as Enfermidades Transmitidas por Vetores (ETV) na América Latina e Caribe. O processo participativo ficou mais intenso ao longo do projeto, com mais sujeitos envolvidos e um número crescente de colaborações. A cooperação entre os atores das ciências sociais, ambientais e da saúde é pouco equitativa; assim, predominam as ciências da saúde. Os poucos cientistas ambientais presentes estão, porém, ativamente envolvidos em colaborações interdisciplinares. A abordagem tem aplicação ampla para estudar a participação e a transdisciplinaridade em projetos sobre saúde e meio ambiente.

How to identify key players that contribute to resilient performance: A social network analysis perspective

Although resilience benefits from social interactions, there is a gap regarding the identification of key players that contribute to it. This study uses social network analysis (SNA) to identify those players based on the modeling of interactions associated with four abilities of resilient systems: monitor, anticipate, respond, and learn. Networks are developed for each ability, and a score is proposed for each player, combining five indicators theoretically connected to resilience: in-degree, closeness, and betweenness, which are derived from SNA, and availability and reliability, which are non-network attributes assessed through Likert-style questions. The proposal was implemented using data on 133 professionals from an intensive care unit. Five semi-structured interviews supported the interpretation of survey data and analysis of contextual factors. The ranking of key players varied across ability-based networks, and none of them excelled in all dimensions of the proposed score. The proposal bridges the gap between the role of individual players in work systems and system resilience. That occurs as the score, while being attributed to individual players, reflects their interactions with others. SNA is thus an effective analytical approach for dealing with the resilience engineering tension between individual performance and context.

How to Transform Liability of Foreignness into Asset of Foreignness under the “Belt and Road” Initiative? A Case Study from the Perspective of Social Network

Under the “Belt and Road” Initiative （BRI）, Chinese companies’ “go-global” has gradually become an important strategy for industrial upgrading. However, many “go-global” companies have met the liability of foreignness （LOF）, including legitimacy problems and the threat of exit. How to overcome LOF has become an urgent problem for the overseas subsidiaries of “go-global” companies.We illustrate our arguments through a single case of Chinese multinational subsidiary Taiwenlong Cement Co., Ltd. in Cambodia. This paper studies from the perspective of social network analysis to identify the source of LOF, and discusses the mode of transforming LOF into the asset of foreignness （AOF）. The case company, Taiwenlong Cement Co., Ltd., is a joint venture between a Chinese company and a host-country company. As a representative of the successful transformation of LOF into AOF, this project experienced both the “honeymoon period” and the “setback period” in its construction and operation process and finally gained a foothold in Cambodia after various attempts.Based on the case analysis, we find that under the BRI, LOF of foreign subsidiaries of Chinese companies in countries along the BRI shows dynamic changes. This paper has several contributions: Firstly, under the BRI, the government-enterprise relationship and industrial chain relationship of the host country are important sources of LOF. Secondly, with the development of Chinese companies’ “go global”, the focus of overcoming LOF has gradually shifted from the national level to the industrial level. The key to the transformation of AOF and LOF lies in matching the adequate industry chain network. Finally, the home government support, technology transfer and industrial agglomeration can promote the transformation of LOF into AOF in the industry chain. Therefore, we construct three transformation routes: （1）Multi-agent centralization mode, through which foreigners can use different types of network resources including not only the government, shareholders, industrial partners in the home country, but also the subjects of local network in the host country, to obtain higher network status in a situation where foreigners can afford a high level of LOF.（2）Foreignness centralization mode, in which foreigners can establish a self-centered industrial chain network, occupying an intermediary role in the flows of information and resources in the case that they can dominate the allocation of network resources.（3）Industrial centralization mode, in which foreign companies can build network with a few industrial partners through the scale advantage of industrial clusters under the case of relatively scarce network resources. The conclusions of this paper have positive implications for the promotion of high-quality development of BRI and Chinese private companies to “go global”.

The Influence of Author Degree Centrality and L-Index on Scientific Performance of Physical Education and Training Papers in China Based on the Perspective of Social Network Analysis

With the increasing frequency of scientific cooperation, research on the impact of scientific cooperation on scholars’ scientific performance has become a hot topic in academic research. This paper mainly uses quantitative research methods such as bibliometrics and social network analysis to analyze the correlation between degree centrality, L-index, and scientific performance of the Chinese author of Physical Education and Training Science and draws the following conclusions: (1) degree centrality is positively correlated with the number of papers, average citations per paper, and H-index and (2) L-index is positively correlated with the number of papers, average citations per paper, and H-index. Unlike previous studies on scientific collaboration networks and scholars’ performance that focused on traditional network characteristics indicators, this study introduces a new network characteristics indicator, L-index, through which the degree of collaboration between authors and other important authors in the research field can be better assessed, which also provides a new direction for research related to research collaboration networks and scholars’ performance; at the same time, it also provides a theoretical basis for subsequent research on the utility of scientific collaboration, a reference for the assessment of the research performance of scholars in other disciplines, and a theoretical reference for more scientific and comprehensive prediction of scholars’ research performance in the future.

A bibliometric and social network analysis perspective of X-ray phase-contrast imaging in medical imaging.

IntroductionPhase‐contrast imaging (PCI) is a novel technology that can visualise variations in X‐ray refraction (phase contrast) in addition to differences in X‐ray attenuation (absorption contrast). Compared to radiography using conventional methods (i.e. absorption‐based imaging), PCI techniques can potentially produce images with higher contrast‐to‐noise ratio and superior spatial resolution at the same or lower radiation doses. This has led PCI to be explored for implementation in medical imaging. While interest in this research field is increasing, the whole body of PCI research in medical imaging has been under‐investigated. This paper provides an overview of PCI literature and then focusses on evaluating its development within the scope of medical imaging.MethodsBibliographic data between 1995 and 2018 were used to visualise collaboration networks between countries, institutions and authors. Social network analysis techniques were implemented to measure these networks in terms of centrality and cohesion. These techniques also assisted in the exploration of underlying research paradigms of clinical X‐ray PCI investigations.ResultsForty‐one countries, 592 institutions and 2073 authors contributed 796 investigations towards clinical PCI research. The most influential contributors and network collaboration characteristics were identified. Italy was the most influential country, with the European Synchrotron Radiation Facility being the most influential institution. At an author level, F. Pfeiffer was found to be the most influential researcher. Among various PCI techniques, grating interferometry was the most investigated, while computed tomography was the most frequently examined modality.ConclusionsBy gaining an understanding of collaborations and trends within clinical X‐ray PCI research, the links between existing collaborators were identified, which can aid future collaborations between emerging and established collaborators. Moreover, exploring the paradigm of past investigations can shape future research – well‐researched PCI techniques may be studied to bring X‐ray PCI closer to clinical implementation, or the potential of seldom‐investigated techniques may be explored.

Inter-team variability in high-level women’s volleyball from the perspective of Social Network Analysis: an analysis in critical game scenarios

ABSTRACT The present study analysed inter-team variability in critical game scenarios in high-level women’s volleyball, using Social Network Analysis. Ten matches of the Women’s Volleyball Nations League 2019 Finals (Brazil, USA, Poland, Italy, Turkey and China) were analysed considering all game complexes, with 622 plays. Six independent eigenvector centrality networks were created, with 668 nodes and 3724 edges. Results: (a) there were differences between the two best-ranked teams and the others in setting conditions and in the overall game patterns, that is, the 1st- and 2nd-ranked teams had better setting conditions than the non-finalists; (b) the game patterns were also different between the two best teams, with the highest levels of transition and the jump-float serve being presented by the United States, while Brazil exhibited high aggressiveness in the float-jump serve and strong attacks; (c) most teams, in ideal setting conditions, played quickly and using strong attacks; and (d) there were no differences in blocking patterns of the teams, and double block predominated. The main conclusions were: (a) within the same competitive level, there were differences in the game patterns of the teams, even between the two best-ranked teams; (b) possibly, the teams were modelled following with their players’ characteristics.

Associations between undergraduates’ interpersonal relationships and mental health in perspective of social network analysis

More and more studies found that mental health was closely related to interpersonal relationships. But it is a recent topic that utilizing social network analysis (SNA) to qualify individuals’ interpersonal relationships. Therefore, this study aimed to explore the relationships between undergraduates’ class interpersonal relationships and mental health from a perspective of social network analysis. 481 participants (165 males, 316 females) from the first, second and third year of bachelor’s degree completed the Mental Health Scale for College Students (MHS-CS) and the Social Network Questionnaire (SNQ). Data was analyzed in UCINET 6, Mplus 8.0 and IBM SPSS 25.0. The results of latent profile analysis (LPA) showed that undergraduates’ class interpersonal relationships can be classified into three types, which are the common type, the passive type and the active type. And the results of one-way ANOVA showed that the common group had the highest level of mental health than the other two groups (p = 0.001). In conclusion, SNA provides a new way to qualify undergraduates’ class interpersonal relationships. And the findings of the current study suggests that in the class interpersonal communications of undergraduates, only moderate activity and popularity were positively associated with mental health.

The Attack in Volleyball from the Perspective of Social Network Analysis: Refining Match Analysis through Interconnectivity and Composite of Variables

This study aimed to develop an instrument for analysing the attack in high-level volleyball considering the refined variables adjacent to the attack action, the interconnection between direct and indirect actions, the impact of the previous action, and the formation of composite variables. The game complexes were approached as interacting subsystems. The primary goal was to understand the influence of game actions adjacent to the attack. Three matches of a National Women’s 1st Division 2018/2019 (nine sets, 415 plays) were analysed, considering all game complexes (except attack coverage due to reduced occurrence). An Eigenvector Centrality network with 420 nodes and 7367 edges was created. The networks showed that ideal setting conditions, and strong attacks by the outside and opposite hitters without having received a perfect ball, were central in side-out. In transition, we highlight ideal setting conditions, preferences of the outside hitter, quick attacks in Z4, and high balls in Z2. This study is distinct because it considers different aspects related to the systemic review of the game by using composite variables and the actions prior to the attack. Of these results, we highlight that players attacked with slower tempos for the double action of receive-attack, and these were either preferably directed to the parallel or explored the block. Moreover, for the double defence-attack actions, attackers sought the soft spike in Z2, Z4, and Z8; and when two consecutive individual errors occurred, the players did not err but instead continued to attack to force the opponent’s error.

Analysis of academic performance based on sociograms: A case study with students from at risk groups

The present work analyzes the academic performance of students from at-risk groups from the perspective of Social Network Analysis (SNA), studying the academic and interaction information of 45 students belonging to at-risk groups who attended a pilot socio-academic course during one academic term. This information was used to create a sociogram, which served as the basis for determining the centrality metrics of the SNA. The relationships between these metrics and the academic variables were then studied by means of correlation analysis and linear regression with LASSO standardization. As a preview of the results, it was determined that the academic performance of the students in the pilot course was influenced, on the one hand, by their academic knowledge prior to being admitted to the university, represented by the score on the Mathematics and Geometry section of the diagnostic test, and on the other hand, by the dynamics of the social network in which they interacted in the classroom, represented by the eigenvector centrality. These results have significant potential for explaining the academic performance according to SNA metrics, and they provide evidence to support the implementation of practices that promote a healthy social environment in an academic context.

Opportunistic Behavior Governance in PPP Projects: An Analysis Based on Trust Networks

Stakeholders of PPP projects may induce opportunistic behaviors in long-term cooperation. Existing studies emphasized the inhibitory effect of trust on opportunistic behaviors, but most of them simplified the trust relationship into a two-subject perspective. From the perspective of social network analysis, this research constructs a network-level trust relationship between the stakeholders of PPP projects. The index analysis of the trust network shows that the PPP project stakeholders have obvious centrality and there are structural holes in the networks. From the perspective of the stakeholder alliance, different forms of alliances differ in the degree, betweenness, and closeness centrality of the trust network. On this basis, the analysis results of different trust network indicators match the corresponding preventive measures of opportunistic behavior, and this research provides comprehensive suggestions for project management.

Two centuries of Greek governments from a social network analysis perspective

Two hundred years after the Greek Revolution (1821), a large number of different administrations (governments) comprising of an even larger number of members of the implementing authority have serv...

Agronomy research co-authorship networks in agricultural innovation systems

Increasingly, Agricultural Innovation Systems, AIS, have been recognized as fundamentals pathways for agricultural science impact. This new thinking focuses on innovation, not as the end of pipe outcome of knowledge transfer, but as a continuous process ofsocial, technical and scientific collaboration at regional and higherlevel systems that impacts on productivity and innovation performance. This paper surveys the agricultural innovation system in Colombia. We analyze collaboration between authors, institutions and countries from the perspective of social network analysis to introduce a descriptive review of the scientific collaboration in terms of links (discipline structure) and nodes (actors). A mixed methodology is implemented based on co-authorship bibliometric mapping using VOS VIEWER and social network analysis based on the software UCINET. Whereas exogenous authors and institutions are the most connected in terms of interaction, they have lower influence than endogenous authors.

Personality and emerging adults' friend selection on social networking sites: A social network analysis perspective.

Personality affects how emerging adults select friends and how they are selected on social networking sites (SNSs). Big Five personality traits and frequency of contacts on SNSs were collected from 160 college freshmen (M = 18 years) under a round-robin design over 2 months. Using social network analyses, we examined how personality and dyadic similarity affect online friend selections among new acquaintances. Our results show that people with high extraversion, neuroticism, and agreeableness and low openness selected more friends, verifying both the social enhancement hypothesis and the social compensation hypothesis. People with low extraversion, conscientiousness, and neuroticism and high openness were selected as online friends more often. Only openness dissimilarity had a salutary effect. We discuss the role of personality in social networking friend selection.

The dynamics of global R&D collaboration networks in ICT: Does China catch up with the US?

The purpose of this study is to identify and characterize the structure and dynamics of global R&D collaboration networks in ICT by analyzing cross-country co-patents, with a special focus on the role of China. We employ a Social Network Analysis (SNA) perspective, using information on more than 77 thousand co-patents from 2001–2015. These co-patents are disaggregated by three time periods and four ICT subsectors. Global measures for the network as a whole, as well as local measures on the positioning of countries in the networks are interpreted. The empirical results are highly interesting. First, international R&D collaboration networks in ICT show a dynamic transformation in becoming larger in magnitude (more countries but also more inter-linkages), less centralized and more densely connected, though with varying degrees across ICT subsectors. Second, the powerful position of the US weakens relatively compared to other, increasingly connected countries, in particular China. While China has already surpassed the US in total patenting in ICT in 2015, China is now also catching up from a network perspective shown by its growing central position over the observed time period.

Network-Based Delivery and Sustainment of Evidence-Based Prevention in Community-Clinical Partnerships Addressing Health Equity: A Qualitative Exploration.

Background: Increased delivery of evidence-based preventive services can improve population health and increase health equity. Community-clinical partnerships offer particular promise, but delivery and sustainment of preventive services through these systems face several challenges related to service integration and collaboration. We used a social network analysis perspective to explore (a) the range of contributions made by community-clinical partnership network members to support the delivery of evidence-based preventive services and (b) important influences on the ability of these partnerships to sustain service delivery.Methods: Data come from an implementation evaluation of the Prevention and Wellness Trust Fund initiative, which supported nine Massachusetts communities to coordinate delivery of evidence-based prevention and address inequities in hypertension, pediatric asthma, falls among older adults, or tobacco use. In 2016, we conducted semi-structured interviews with (a) leadership teams representing nine community-level partnerships and (b) practitioners from four high-implementation partnerships (n = 23). We managed data using NVivo11 and utilized a framework analysis approach.Results: Key network contributions for delivery of evidence-based preventive services included creating referrals, delivering services, providing links to community members, and administration and leadership. Less emphasized contributions included wraparound services, technical assistance, and venue provision. Implementers from high-implementation partnerships also highlighted contributions such as program adaptation, creating buy-in, and sharing information to improve service delivery. Expected drivers of program sustainability included the ability to develop a business case, ongoing network facilitation, technology support, continued integrated action, and sufficient staffing to maintain programming.Conclusion: The study highlights the need to take a long-term, infrastructure-focused approach when designing community-clinical partnerships. Strategic partnership composition, including identifying sources of necessary network contributions, in conjunction with efforts from the outset to link systems, align effort, and build a long-term funding structure can support the required coordinated action around preventive services needed to improve health equity.