Network Centrality Research Articles

Identification of Research Trends Related to Marriage Values Using Keyword Network Analysis

The purpose of this study was to analyze research trends related to marriage values using keyword network analysis. To this end, 157 dissertations and academic journal papers related to marriage values published in Korea from 2001 to April 2024, along with 247 keywords were selected for analysis. Keyword network analysis was applied to the selected keywords using Microsoft Excel 365 and NetMiner 4.0. The results were as follows. First, research related to marriage values was low for the 10 years starting in 2001; however, the number of research materials gradually increased in the 2010s, and then increased significantly from the late 2010s. The 30 keywords that appeared most frequently were related to various personal psychological and socio-cultural variables that influence marriage values, and the keyword that appeared most frequently was 'family values'. Second, an analysis of keyword network centrality revealed that 'marriage intent' appeared in the connection centrality, 'sex role values' appeared in the proximity centrality, and 'generation' appeared in the mediation centrality. In terms of the overall centrality, 'child value' also exerted a relatively high influence. By identifying the various variables that affect marriage values, this study provides a wealth of information useful for the development of educational programs aimed at forming marriage values among adolescents, college students, unmarried men and women, prospective couples, prospective parents, and parents.

Mapping carbon emission networks in China: insights from province-level spatial differentiation

In the current global economic downturn and energy transition period, how to better coordinate the differences in carbon emission footprints among sub-regions has become an emerging issue. With the Gini decomposition method, social network analysis, and difference-in-differences estimation, this study explores the spatial differentiation of China’s province-level carbon emission footprint from 2000 to 2021. The findings of this study indicate that: (1) The Gini-based carbon emission footprint index shows an overall upward trend, revealing the constantly expanding differences among provinces. By comparison, the crude oil difference between the low-carbon pilot and non-pilot provinces is evident, reaching more than 0.15; (2) The carbon emission footprint spatial correlation network structure shows strong spillover characteristics. Provinces with higher network centrality have better structural holes, maintaining closer relationships with surrounding provinces. Those pilot provinces have a comparative advantage regarding social network position, as they have more effective mutual node connections; and (3) China’s low-carbon pilot policy can effectively reduce carbon emissions, with a certain reduction effect of -17.433 in comparison. Industrial rational transformation and green innovation performance are essential in this emission reduction process. At the crossroads of sustainable development, it will be incredibly beneficial to speed up the green transformation by enhancing the coordinated development of regional characteristics.

Higher eigenvector centrality in grooming network is linked to better inhibitory control task performance but not other cognitive tasks in free-ranging Japanese macaques.

The Social Intelligence Hypothesis predicts that complex social environments promote higher cognitive capacities. This hypothesis is often tested by comparing species or conspecific groups with varying group sizes or social structures. However, individual social environments differ not only among species or groups but also within the same group. We examined the relationship between social centrality and cognitive ability in wild Japanese macaques (Macaca fuscata). We created a grooming network using data from 196 adult macaques and calculated social centrality for each individual. We then tested the macaques with a cognitive test battery to assess their abilities in social, physical, and inhibitory control domains. Our findings revealed that social centrality was uniquely associated with inhibitory control performance, particularly in the behavioral inhibition task, but not with other cognitive domains. This suggests that inhibitory control, a key component of executive functions, plays a pivotal role in the social lives of wild Japanese macaques.

Comparative Analysis of Gene Networks in Humans and Model Organisms for Aging Studies

Aging is the cause of the loss of vitality on a day-to-day basis, a risk factor for developing chronic diseases and ultimately leading to death. This inevitable biological process is yet to be completely understood. A hypothesis states that manipulation of aging process can enable maintain physiological function and perhaps prevents age related diseases. Currently, model organisms are being used in the investigation of the genetic and molecular mechanism of the aging process. In this study, the adequacy of the major model system, the fruit fly (Drosophila melanogaster) and the rodent mouse (Mus musculus), was analyzed using Jepetto software through comparison of all the genomes of the model organisms with all the genomes of human genome by network statistics of string interactions. The software mapped the gene set of humans and the two model organisms on an interaction network and computed the gene properties by network density, centrality nodes and clustering coefficient. Of all three genomes, the human gene network is the largest and dense with the highest number of neighbors. On the other hand, the mouse and drosophila network are relatively smaller and in terms of density, the former is less dense, and the latter is sparse. The average number of neighbors of both model organisms are similar and approximately 25% of the human network. In the distance/shortest path length between the nodes, there was a decreasing order of connectivity in drosophila to mouse to human. The node with the path length 2 exhibited the highest frequency in all the organisms. In between centrality distribution, the nodes of the human network were observed to be closer. On comparison, mouse network is closer while the drosophila network is widely spread. The information spread between the nodes is measured by the closeness centrality distribution plot and the human network found to have highest closeness centrality than the other two species. Neighborhood connectivity distribution. The network clustering coefficient of genes of drosophila was much more widespread than the other two species.

Extended state infrastructure power in an age of networked competition: The cases of Thailand and Taiwan

Scholars have highlighted the emergence of infrastructure as a key domain in the struggle over network centrality in what some call the ‘Second Cold War’ between the U.S. and China. We qualify this ‘infrastructural turn’ by drawing attention to the contingent nature of state infrastructural power as depending on key domestic firms that often serve as intermediaries between domestic infrastructure and global supply chains or international partners. Utilising empirical case studies based on field research conducted between 2021 and 2023 in Thailand and Taiwan, we analyse the ways in which state infrastructure power is exercised through strategic negotiation between national politics of the state and territorial investment decisions of multinational and major domestic firms within global supply chains. The study highlights how outcomes of state projects to foster connectivity or centrality in networks are shaped by contingent and sometimes ad-hoc coalitions between state agencies and domestic and multinational companies with their own interests and agency. In the case of Taiwan, the centrality of Taiwan Semiconductor Manufacturing Company (TSMC) to global supply chains makes it an important player amidst continued U.S.-China tension. In Thailand, CP Group’s connections to China have afforded it a role as an interlocutor between Thailand and China, allowing it to obtain state infrastructure contracts. Through comparative case studies the paper complicates both ‘globalist’ and methodologically nationalist perspectives on the ‘infrastructural turn’, and introduces the concept of ‘ extended state infrastructural power’ to account for this complex, networked exercise of state authority.

Dangerous depths of bifurcation: the rise of “inter-national security narcissists” and undersea cable (dis) connections

ABSTRACT This article examines the rising bifurcation in global undersea cable networks amid growing U.S.-China tensions, building on the “weaponized interdependence” (WI) framework. While WI sheds light on how states leverage network centrality for strategic benefits, it falls short of capturing the proactive reshaping of network topologies for national security. We argue this bifurcation fosters parallel, redundant systems that, despite increased costs, enhance control and security. A sequential game model illustrates how U.S. and Chinese security-driven decisions contribute to network divergence, while a hierarchical Q-learning model explores how path dependency and lock-in effects sustain this split. Empirical cases, like the Cap-1 project, demonstrate the practical impact, emphasizing security’s role in reconfiguring global communications infrastructure.

Using complex systems to understand running-related injuries

ABSTRACT This study aims to investigate anthropometric and training characteristics associated with injuries in runners using a complex approach. We conducted a cross-sectional study with 97 Brazilian runners of both sexes (age: 39.1 ± 11.5 years; body mass index: 24.2 ± 4.2 kg/m2). A web survey was used for data collection, including age, sex, body weight, body height, training volume/frequency, session duration, running pace and injury information (yes or no; the number of injuries). The partial correlation parameter was used for network estimation, considering both sexes. For women, injury occurrence was positively and strongly associated with training frequency (r = 0.57) and the number of competitions (r = 0.64), while for men, a negative and strong association was found with age (r=-0.69), and positive associations were observed with BMI (r = 0.89) and training volume (r = 0.82). Network centrality showed that training session duration and the number of competitions/year presented a higher expected influence value for women (−1.47) and men (−1.31). Using a non-linear approach with Brazilian non-professional runners, training characteristics had a stronger influence on running-related injuries.

언어네트워크 분석을 통한 예비영유아교사의 수업시연 내용 연구: 멘토링 중심 수업시연대회에 따른 변화

Objectives In this study, we conducted a language network analysis of the content of the changing lesson demonstrations as pre-service early childhood teacher experienced mentoring-centered lesson demonstrations. Methods For this reason, after 264 chapters of the 1st Selection Tournament Warrior Materials and mentoring were conducted for 34 participants in the Class Trial Competition, 362 chapters of the 2nd Final Selection Tournament Warrior materials were analyzed. Data were compared by keyword frequency analysis, network structure analysis, centrality analysis, and CONCOR analysis using KrKwic and UCINET 6 programs. Results First of all, In the first round of competitions, Guys was mentioned most often after We, and in the second round of competitions, Teacher was mentioned after We. Second, the relationships between keywords in the utterances in the second round competition were more concentrated than those in the first round competition. In terms of degree centrality, betweenness centrality, and eigenvector centrality, Guys was ranked in the top 3 in the first selection competition, and Teacher was ranked in the top 2 in the second selection competition. Third, according to the CONCOR analysis, two main clusters appeared in the first round of competitions is teacher-centered interaction and explanation about the content of the activity. Two main clusters appeared in the second round of competitions is child-centered interaction and a method cluster was formed for young children to participate in activities. Conclusions The results of this study suggest that it is necessary to develop a curriculum in collaboration between universities and early childhood educational institution in order to improve the professional abilities of pre-service early childhood teachers.

The different impacts of functional network centrality and connectivity on the complexity of brain signals in healthy control and first-episode drug-naïve patients with major depressive disorder.

In recent years, brain signal complexity has gained attention as an indicator of brain well-being and a predictor of disease and dysfunction. Brain entropy quantifies this complexity. Assessment of functional network centrality and connectivity reveals that information communication induces neural signal oscillations in certain brain regions. However, their relationship is uncertain. This work studied brain signal complexity, network centrality, and connectivity in both healthy and depressed individuals. The current work comprised a sample of 124 first-episode drug-naïve patients with major depressive disorder (MDD) and 105 healthy controls (HC). Six functional networks were created for each person using resting-state functional magnetic resonance imaging. For each network, entropy, centrality, and connectivity were computed. Using structural equation modeling, this study examined the associations between brain network entropy, centrality, and connectivity. The findings demonstrated substantial correlations of entropy with both centrality and connectivity in HC and these correlation patterns were disrupted in MDD. Compared to HC, MDD exhibited higher entropy in four networks and demonstrated changes in centralities across all networks. The structural equation modeling showed that network centralities, connectivity, and depression severity had impacts on brain entropy. Nevertheless, no impacts were observed in the opposite directions. This study indicated that the complexity of brain signals was influenced not only by the interactions among different areas of the brain but also by the severity level of depression. These findings enhanced our comprehension of the associations of brain entropy with its influential factors.

Mining text for causality: a new perspective on food safety crisis management

The aim of the present study was to quantitatively analyze the importance of each risk factor in a food safety event, so as to fully elucidate the correlation between different risk factors and provide a reference for food safety governance. Text mining and complex network analysis methods were utilized to explore the causal mechanism of food safety incidents. By performing text mining on food safety event news reports, 15 major risk factors were identified based on high-frequency words. A causal network for food safety accidents was then constructed using strong association rules among these factors. Through network centrality analysis, the five core factors of food safety incidents and their associated sets were clarified. Based on text mining of 6,282 cases of food safety incidents reported by online media, 168 keywords related to food risk factors were extracted and further categorized into 15 types of food safety risk factors. Network analysis results revealed that microbial infection emerged as the most critical risk factor, with its associated sets including biotoxins and parasites, counterfeiting or fraud, processing process issues, and non-compliance with quality indicators.

Leveraging network analysis to improve navigability of design standards

The utility of building design standards is a growing concern amongst construction professionals. Design standards continue to swell with updates, which makes ensuring all requirements are satisfied increasingly complex for users. Few tools exist for authors of standards to improve navigation for users. This study investigates the use of network analysis to understand the relationship between the organization of a standard and navigational complexity. A case study is presented of the reorganization of American Concrete Institute’s (ACI) flagship design document, ACI 318. The standard’s networks before (ACI 318-11) and after (ACI 318-14) the reorganization are developed via rule-based text extraction. Networks are analyzed assuming that ACI 318-14 is the structurally superior document. Indicators of complexity are identified from each networks' characteristic features, centrality metrics, clustering tendencies, recurring motifs, and geodesic paths. Network analysis is found to be useful for identifying, understanding, and mitigating navigational complexity within a building design standard.

Impact of firm’s supply chain network position on digital transformation: evidence from China

Purpose Given the complexity and increasing interdependence of supply chain networks, a broader perspective beyond a simple binary relationship is needed to analyse the impact of supply chain networks on firms. Based on social network theory, this study aims to explore the relationship between firms’ network position in the supply chain network and digital transformation, as well as the moderating effects of structural holes and network partners’ digitalisation. Design/methodology/approach This study analyses a sample of Chinese A-share companies listed on the Shanghai and Shenzhen Stock Exchanges for the period 2011–2020 using regression analysis to test hypothesised relationships. Findings A firm’s centrality in the supply chain network is positively related to its digital transformation, and that the firm’s structural holes and the level of network partners’ digitalisation can both strengthen the positive influence of network centrality on digital transformation. Moreover, the heterogeneity analysis reveals that the positive effect of firms’ network centrality on digital transformation is more pronounced in non-SOEs and upstream firms. Practical implications In the pursuit of digital transformation, firms should recognise the significance of their position in the supply chain network and enhance their capability for information and resource acquisition by proactively strengthening their business cooperation with other network members. Moreover, firms should emphasise the value of open networks and their partners in supply chain networks. Originality/value This study applies social network theory to investigate the role of a firm’s external supply chain network in its digital transformation, clarifying the context and boundaries in which a firm’s position in the supply chain network influences digital transformation. The results extend the research and theoretical perspective on digital transformation and the consequences of supply chain networks.

Non-controlling shareholders’ network and the reliability of merger and acquisition performance commitments: Governance or collusion?

This study examines the effect of non-controlling shareholders’ network on the reliability of performance commitment (PC) agreements signed during merger and acquisitions (M&A), based on A-share listed companies in China during 2008–2022. Findings indicate that higher non-controlling shareholders’ network centrality is significantly associated with an increased PC reliability. Mechanism tests reveal that this correlation is driven by the network's embedded advantage to reduce M&A premiums and curb insider shareholding reduction. Furthermore, this study highlights that the networks of pressure-resistant institutional investors, non–state-owned legal entity shareholders, and individual investors play crucial roles in enchaining PC reliability.

Effects of simplicial centrality on robustness of higher-order multiplex world trade networks

Abstract World trade networks are exhaustively described by pairwise interactions, and overlook higher-order structure from the outcome of collective interactions at the level of groups of nodes like multilateral trade agreements. To address this limitation, we collect multiplex world trade networks, including the bilateral regional trade agreement network, which represents pairwise interactions; the multilateral regional trade agreement network, which naturally represents a higher-order network structure; and the import and export trade network, which represents pairwise interactions and additional complexities. The analysis of simplicial centrality, including degree, closeness, and subgraph at 0, 1, and 2-simplex levels, reveals that intra-level correlations are high, while inter-levels may exhibit significant disparities. Nodes with low centrality at higher-order levels could influence network robustness due to the diversity of interactions and higher-order dependencies. Simplicial centrality on robustness of multiplex world trade networks under random and targeted attacks reveals that the complex connectivity of higher-order levels renders them more vulnerable post-attack. An optimization strategy of the rebalancing of network centrality is proposed to enhance the robustness, and the simulation shows risks posed to central nodes are minimized and opportunities for peripheral nodes to partake in global trade are broadened.

Social Media Networks and Stock Price Synchronicity: Evidence from a Chinese Stock Forum

The widespread communication and interaction between small investors on social media in the capital market has resulted in the formation of a social media network specific to listed companies. Using a unique dataset from an active online stock forum in China, we construct a social media network of listed companies by assigning listed companies as nodes and common commenters who post in each of the subforums for two listed companies in a year as edges. Then, we investigate the relationship between the network centrality of the listed companies and stock price synchronicity. The results show that there is a significantly negative relationship between the social network centrality of listed companies and stock price synchronicity, indicating that social media networks can improve the price efficiency of capital markets. The mechanism analysis shows that social media networks can produce more corporate‐specific information and improve the efficiency of information dissemination, thus reducing stock price synchronicity.

Social Influence in Social-Ecological Systems: Collaborative Capacity and Inter-Organizational Networks in the U.S. Sagebrush.

Collaborative governance has become a prominent, if not dominant, framework for thinking about multi-scalar and cross-jurisdictional environmental management. The literature broadly and consistently suggests that collaborative capacity and inter-organizational networks provide the institutional framework for addressing social-ecological system challenges. Surprisingly little scholarship addresses processes of social influence (or contagion) in social-ecological systems writ large, or more specifically as it relates to collaborative capacity. In this study, we consider the relationship between network position and structure and "collaborative capacity". We use a linear network autocorrelation model to establish a quantifiable, statistical relationship between an organizational-level outcome (collaborative capacity) for organizations that are relationally connected in a network addressing conservation and management issues in the U.S. sagebrush biome. We test three general hypotheses: (1) that social position - operationalized as network centrality - is related to collaborative capacity, (2) that subgroup or community structure - operationalized as modularity - is related to collaborative capacity, and (3) that there is a social contagion effect of collaborative capacity. Our results identify a positive relationship between collaborative capacity and organizations in positions of brokerage as well as evidence of a "collaborative capacity" contagion effect. This work contributes to our understanding of the role of bridging organizations and networks for large-scale environmental management.

The Network Structure of School Principal Resilience: Gender Differences

ABSTRACTThe ability of school principals to demonstrate resilience enables them to effectively lead, adapt and thrive amidst the ever‐changing landscape of educational challenges and transformations. Despite its necessity, research on principal resilience remains largely underdeveloped and is still in its early stages. The current study aims to fill this gap using network analysis to examine the inter‐structural principal resilience network and gender differences in terms of network estimation, centrality indices, network stability and network comparison using a sample of 1274 principals from China. The results reveal a comprehensive understanding of the dynamic network and gender effects on school principal resilience at the dimension and item levels. It is noted that social resilience exhibits the highest strength, indicating the critical importance of social support networks and relationships. The gender analysis indicated that spiritual resilience emerged as a central dimension in the resilience network of female principals, while emotional and psychological resilience was the central dimension in the resilience network of male principals. This study advances the conceptual and practical understandings of school principal resilience by examining the interactions among different dimensions and items, thereby contributing to the maturity of knowledge production and intervention efforts in the field.

Predicting Landscape Conversion Impact on Small Mammal Occurrence and the Transmission of Parasites in the Atlantic Forest

ABSTRACTAimChanges in landscape configuration significantly impact ecosystems and the services they provide, including disease regulation for both humans and wildlife. Land use conversion usually favors disturbed‐adapted species, which are often known reservoirs of zoonotic parasites, thereby potentially escalating spillover events (i.e., the transmission of parasites to new hosts, including humans). Here we aimed to investigate how alterations in landscape use and configuration influence the distribution and co‐occurrence of potential hosts of zoonotic and epizootic parasites.LocationBrazilian Atlantic Forest.Time PeriodData collection spanned from 1997 to 2019.Major taxa studied small mammals.MethodsWe integrated ecological network metrics and joint distribution models while accounting for phylogenetic relationships and functional traits to answer two main questions: (1) do small mammal species considered central hosts in the transmission of parasites exhibit a higher probability of occurrence in landscapes with reduced native vegetation areas? (2) Do small mammal hosts that share a higher number of parasites have higher co‐occurrence probabilities?ResultsOur results demonstrated that species identified as significant hosts in our centrality network analysis displayed an increased probability of occurrence in landscapes that are both more fragmented and have a higher proportion of farming areas, hence fewer native vegetation areas. Regarding the relationship between species co‐occurrence and parasite sharing, our findings indicated that most strong co‐occurrences were prevalent within groups with higher parasite fauna similarity, but not all species sharing parasites had a higher probability of co‐occurring.ConclusionsHere we highlight the effects of landscape conversion on small mammal species, including how different configurations of land use can influence both central and non‐central host occurrences. Besides, our results also indicate that parasite transmission may be overestimated when the co‐occurrence probability of potential host species is not considered. We highly recommend incorporating co‐occurrence data to estimate zoonotic risk.

Node centrality based on its edges importance: The Position centrality

We propose a novel family of node centralities in social networks, named family of position centralities, which explicitly takes into account the importance of the links to assess the centrality of the nodes that support them through the Position value (Meessen, 1988). Our proposal shares with the family of Myerson centralities (Gómez et al., 2003) that it is a game-theoretic family of measures that allows to consider the functionality of the network modelled by a symmetric cooperative game. We prove that, like the Myerson centrality measures, every Position centrality measure also satisfies essential properties expected of a centrality measure. We analyse in detail the main differences between the Myerson and the position families of centrality measures. Specifically, we study the differences regarding the connection structures that share dividends and the fairness and stability properties. Along this analysis we consider the case of hub-and-spoke clusters, a prevalent model for studying transportation networks. Finally, a characterisation of the Position Attachment centrality is given, which is the Position centrality obtained when the functionality of the network is modelled by the attachment game. Some comparisons are made with the Attachment centrality introduced by Skibski et al. (2019), which is the analogue member of the family of Myerson centralities.

Supply chain network centrality and corporate greenwashing behavior

This paper examines the impact of supply chain network centrality on corporate greenwashing behavior. Using data from Chinese listed companies, we find that supply chain network centrality suppresses corporate greenwashing behavior, and the impact mechanism is that supply chain network centrality alleviates corporate financing constraints and inhibits managerial myopia. We also find that relationship between supply chain network centrality and corporate greenwashing behavior is more significant among corporations in heavily polluting industries, weaker industry competition, and higher transaction costs. This paper extends the governance factors of corporate greenwashing behavior to the level of supply chain network relationships.