Intramural sports social networks and implications for college student physical activity, sense of community, and retention

Objective: This study examines associations between social networks developed through intramural sports and physical activity (PA), sense of community, and retention. Participants: College students participating in intramural sports at a large public university in the Southern United States (n = 250). Methods: Students self-reported PA, sense of community, retention, and social networks developed through intramural sports in Fall 2022. Logistic and linear regression determined significant individual and network factors associated with PA, sense of community, and retention. Results: Participants were significantly more likely to meet PA recommendations (Nagelkerke R²=.24) if they were younger, male, and reported more people in their networks were physically active often. Participants reported a greater sense of community (R² =.28) and retention intention (R² =.26) if they reported meeting PA recommendations, feeling closer to network members, and more relationships improving through intramurals. Conclusion: Results underline the importance of creating quality intramural experiences for college students.

Mapping sustainability reporting research with the UN's sustainable development goal

Non-financial reporting (NFR) has become crucial to corporate sustainability strategies as companies demonstrate their commitment to the environmental, social, and governance actions outlined in the United Nations Sustainable Development Goals (SDGs) Agenda 2030. Among the various mandatory NFR initiatives, Sustainability Reporting (SR) has emerged as a widely adopted practice by companies worldwide. A gap that the study addresses is the theoretical perspectives on SR in the context of SDG. Then we conduct a bibliometric and science mapping analysis of research trends on SR and precisely map SR research to SDGs which is also a gap in the current literature. We find an exponential increase in the number of publications and citations on SR, particularly after 2015, which coincides with increased public awareness and scrutiny of the SDGs. At the country level, Australia leads with a total of 13 SDGs, followed by the UK, Spain, and Italy, which each address 12 SDGs. Emerging economies such as Indonesia, Malaysia, and India have also increased their contributions since 2019. A keyword co-occurrence analysis identified three main clusters: stakeholder engagement, corporate governance, and accountability; sustainable development goals and climate change; and sustainability reporting and global reporting initiatives. All three clusters had highly cited publications related to SDG 8 (decent work), SDG 9 (industry innovation), and SDG 12 (responsible consumption). This highlights the interdisciplinary nature of SR and its relevance to multiple SDGs. The study is distinctive in that we utilized social network analysis to examine the SDG network based on SR publications, which also affirmed the centrality of SDG 9 and 12. We utilized the prominence percentile, which indicates the momentum of a particular topic, to identify future topics in SR that align with the SDGs. These include cause-related marketing, environmentally preferable purchasing decisions, environmental management systems, education for sustainability, and green computing.

Analysis of spatial correlation networks of carbon emissions in emerging economies

Studies have shown that energy consumption from economic development leads to an increase in carbon emissions. Emerging economies, as important sources of carbon emissions with high growth potential, play a crucial role in global decarbonisation efforts. However, the spatial pattern and evolution trend of carbon emissions in emerging economies have not been studied in depth. Therefore, this paper uses the improved gravitational model and carbon emission data from 2000 to 2018 to construct a spatial correlation network of carbon emissions in 30 emerging economies around the world, aiming to reveal the spatial characteristics and influencing factors of carbon emissions at the national level. The results show that the spatial network structure of carbon emissions in emerging economies is closely linked, forming a "big network" of interconnection. Amongst them, Argentina, Brazil, Russia, Estonia, etc. are at the centre of the network and play a leading role. Geographical distance, economic development level, population density, and scientific and technological level have a significant impact on the formation of spatial correlation between carbon emissions. Further use of GeoDetector shows that the explanatory power of two-factor interaction on centrality is greater than that of a single factor, indicating that a single economic development cannot well enhance the influence of countries in the carbon emission network, and needs to be combined with factors such as industrial structure and scientific and technological level. These results are helpful to understand the correlation between carbon emissions between countries from the perspective of the whole and part and provide a reference for optimizing the carbon emission network structure in the future.

Mapping analytical hierarchy process research to sustainable development goals: Bibliometric and social network analysis

The drive to achieve the Sustainable Development Goals (SDGs) becomes more urgent as the 2030 deadline draws near, increasing research in various sectors. Nevertheless, studies that systematically map Analytical Hierarchy Process (AHP) publications with the SDGs need to be more conspicuously lacking. Our study adds a new perspective to the field by creatively bridging this knowledge gap using the Elsevier SDG Mapping Initiative. To find research clusters, trends, and themes linked to SDGs and their connection to environmental sustainability, we thoroughly analyzed 29,897 publications from 2012 to 2022. The analysis showed that SDG 15, SDG 7, SDG 12, SDG 13, and SDG 11 were the top five SDGs, with an environmental focus among the 17 SDGs. These top SDGs had many clusters connected to them, illustrating various sustainability-related problems. The study also looked at connections between SDGs, the nations with the highest rates of productivity, the top contributors, and the journals with the highest citation counts. We discovered three separate SDG clusters using co-occurrence network analysis, each representing a different SDG. We discovered relevant SDGs using Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) analysis and centrality indicators like eigenvector and betweenness. This novel method for publishing analysis combines an AHP focus that aligns with the SDGs with social network analysis and centrality metrics. Our research advances knowledge of how the AHP technique can assess initiatives supporting the SDGs. We offer essential insights into prioritizing sustainable development measures by identifying research clusters, trends, and issues related to environmental sustainability. This study highlights the subject's most important SDGs, productive nations, helpful organizations, and significant journals.

Latent Profile Patterns of Network-Level Norms and Associations with Individual-Level Sexual Behaviors: The N2 Cohort Study in Chicago

Individual-level behavior can be influenced by injunctive and descriptive social network norms surrounding that behavior. There is a need to understand how the influence of social norms within an individual's social networks may influence individual-level sexual behavior. We aimed to typologize the network-level norms of sexual behaviors within the social networks of Black sexual and gender minoritized groups (SGM) assigned male at birth. Survey data were collected in Chicago, Illinois, USA, between 2018 and 2019 from Black SGM. A total of 371 participants provided individual-level information about sociodemographic characteristics and HIV vulnerability from sex (i.e., condomless sex, group sex, use of alcohol/drugs to enhance sex) and completed an egocentric network inventory assessing perceptions of their social network members' (alters') injunctive and descriptive norms surrounding sexual behaviors with increased HIV vulnerability. We used Latent Profile Analysis (LPA) to identify network-level norms based on the proportion of alters' approval of the participant engaging in condomless sex, group sex, and use of drugs to enhance sex (i.e., injunctive norms) and alters' engagement in these behaviors (i.e., descriptive norms). We then used binomial regression analyses to examine associations between network-level norm profiles and individual-level HIV vulnerability from sex. The results of our LPA indicated that our sample experienced five distinct latent profiles of network-level norms: (1) low HIV vulnerability network norm, (2) moderately high HIV vulnerability network norm, (3) high HIV vulnerability network norm, (4) condomless sex dominant network norm, and (5) approval of drug use during sex dominant network norm. Condomless anal sex, group sex, and using drugs to enhance sex were positively and significantly associated with higher HIV vulnerability social network norm profiles, relative to low HIV vulnerability norm profiles. To mitigate Black SGM's HIV vulnerability, future HIV risk reduction strategies can consider using network-level intervention approaches such as opinion leaders, segmentation, induction, or alteration, through an intersectionality framework.

Aligning social networks and co-designed visions to foster systemic innovation in the Alps

Mountain regions face substantial challenges and opportunities arising from global change. The capacity of mountain regions for (systemic) innovation will be determinant to the success of system transformations envisioned by social actors of mountain communities. By analysing the social networks of two regions in the Alps and relating them to desired future visions of sustainable regional development, we provide insights about innovative capacities in mountain regions and propose how to strengthen these capacities in order to support regional transformations. In particular, we analyse innovation systems' collaboration networks to evaluate the innovative capacity of communities, co-construct visions with mountain stakeholders, and assess innovation requirements to meet these visions. Accordingly, we propose changes to the collaboration networks for addressing regional innovation system (RIS) capacities to help achieve visions through systemic innovation. Our analysis furthers the understanding on the type and magnitude of regional innovation system changes required to more effectively address desired transformative visions in mountain regions. We close by discussing implications of our approach for the assessment of innovative capacity and the transformation of mountain regions.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s10113-023-02099-y.

Social network analysis of COVID-19 vaccine YouTube videos in Odisha, India: mapping the channel network and analyzing comment sentiment

India has reported more than 35 million confirmed cases of COVID-19 and nearly half a million cumulative deaths. Although vaccination rates for the first vaccine dose are quite high, one-third of the population has not received a second shot. Due to its widespread use and popularity, social media can play a vital role in enhancing vaccine acceptance. This study in a real-world setting utilizes YouTube videos in Odisha, India where the platform has deep penetration among the 18-35 target population, and secondarily their family and peers. Two contrasting videos were launched on the YouTube platform to examine how those videos operate within the broader recommender and subscription systems that determine the audience reach. Video analytics, algorithms for recommended videos, visual representation of connections created, centrality between the networks, and comment analysis was conducted. The results indicate that the video with a non-humorous tone and collectivistic appeal delivered by a female protagonist performed best with regard to views and time spent watching the videos. The results are of significance to health communicators who seek to better understand the platform mechanisms that determine the spread of videos and measures of viewer reactions based on viewer sentiment.

Examining thematic and emotional differences across Twitter, Reddit, and YouTube: The case of COVID-19 vaccine side effects

Social media discourse has become a key data source for understanding the public's perception of, and sentiments during a public health crisis. However, given the different niches which platforms occupy in terms of information exchange, reliance on a single platform would provide an incomplete picture of public opinions. Based on the schema theory, this study suggests a 'social media platform schema' to indicate users' different expectations based on previous usages of platform and argues that a platform's distinct characteristics foster distinct platform schema and, in turn, distinct nature of information. We analyzed COVID-19 vaccine side effect-related discussions from Twitter, Reddit, and YouTube, each of which represents a different type of the platform, and found thematic and emotional differences across platforms. Thematic analysis using k-means clustering algorithm identified seven clusters in each platform. To computationally group and contrast thematic clusters across platforms, we employed modularity analysis using the Louvain algorithm to determine a semantic network structure based on themes. We also observed differences in emotional contexts across platforms. Theoretical and public health implications are then discussed.

SNA: The Optimal Nodes to Raise Nurses' Infosec Awareness

Social Network Analysis (SNA) can promote Infosec awareness. A sample of 164 nurses selected the most trusted actors to get Infosec updates. UCINET 6 and NetDraw were used for mapping and PSPP 1.6.2 was used for data analysis. Nurses tend to trust managers, colleagues and IT professionals for retrieving Infosec updates.

Social network and genomic analysis of an OXA-48 carbapenemase-producing Enterobacterales hospital ward outbreak in Ireland, 2018-2019

Background

Nosocomial transmission and outbreaks of carbapenemase-producing Enterobacterales (CPE) represent a challenge to healthcare systems. In July 2018, a CPE hospital ward outbreak was declared. Our aim was to investigate transmission patterns, using social network analysis and genomics in a nosocomial CPE outbreak.

Methods

A retrospective descriptive analysis of all patients (cases and contacts) admitted to a ward experiencing a CPE outbreak (2018-2019) was undertaken. A case had a negative CPE admission screen, and subsequent positive test. A contact shared a multi-bed area and/or facility with a case (>4 hours). Social networks, including genomics data and ward locations, were constructed. Network metrics were analysed.

Findings

Forty-five cases and 844 contacts were analysed. The median age of cases was 78 years (IQR 67-83), 58% (n=26) were male and 100% had co-morbidities. The median outbreak ward length-of-stay (LOS) was 17 days (IQR 10-34). OXA-48 CPE was confirmed in all cases and from 26 environmental samples. Social networks identified clusters by time, gender and species/sequence type/plasmid. Network metrics indicated potential superspreading involving a subset of patients with behavioural issues.

Conclusion

Social networks elucidated high resolution transmission patterns involving two related OXA-48 plasmids, multiple species/genotypes and potential super-spreading. Interventions prevented intra-hospital spread. An older patient cohort, extended hospital LOS and frequent intra-ward bed transfers, coupled with suboptimal ward infrastructure, likely prolonged this outbreak. We recommend social network analysis contemporaneously with genomics (on case and environmental samples) for complex nosocomial outbreaks and bespoke care plans for patients with behavioural issues on outbreak wards.

Design and implementation of ParkinsonAKTIV: an interventional study to evaluate the effectiveness of a novel online platform to guide quickcard-based treatment decisions

INTRODUCTION

Patients with Parkinson's Disease (PD) require an all-encompassing and individualized care including pharmacological as well as non-pharmacological treatment approaches, such as physical therapy, occupational therapy and speech and swallowing therapy. ParkinsonAKTIV is an innovative, multidisciplinary, and comprehensive approach to guide this non-pharmacological PD treatment in northwestern Germany. Its online communication platform called JamesAKTIV has been developed to enhance and standardize PD healthcare professionals' communication. The implementation of ParkinsonAKTIV and JamesAKTIV is accompanied through a detailed process evaluation and to gather evidence on the impact on patient-related outcomes, such as health-related quality of life and healthcare costs for people with PD through an effectiveness evaluation.

METHODS

The study design contains two parts: (1) first, a quantitative effectiveness evaluation is conducted utilizing a prospective quasi-experimental approach with a control group which examines PD patient's health-related quality of life and physician-assessed PD patient's health status (Unified Parkinson Disease Rating Scale). Moreover, a health economic evaluation of the ParkinsonAKTIV intervention is conducted using patient-reported outcomes and cost data as well as routine data from a statutory health insurance. (2) Second, a mixed-methods process evaluation among healthcare professionals, which examines the feasibility and potential barriers and facilitators of ParkinsonAKTIV for routine care, is performed. Quantitative results from a social network analysis and a survey among healthcare professionals will be triangulated with data from qualitative stakeholder interviews and focus group discussions.

PERSPECTIVE

Findings are expected to provide evidence of an increase in quality of life of patients with PD, less severe PD symptoms, and a better ability to participate in activities of daily living. ParkinsonAKTIV has the potential of increasing PD patients' quality of care through sufficient and more tailored prescription of non-pharmacological therapies. It is anticipated that ParkinsonAKTIV will improve communication among health professionals. Results from the ParkinsonAKTIV study will provide first practice-oriented evidence and a roadmap for implementation of an online tool for a comprehensive, multidisciplinary care PD network for patients and their caregivers in routine care in Germany. Trial registration ClinicalTrials.gov: registration number NCT05251298 (retrospectively registered: https://clinicaltrials.gov/ct2/show/record/NCT05251298 ).

Mapping the Nanotechnology Patent Landscape in the Field of Cancer

BACKGROUND

Currently, cancer is still a significant disease that seriously endangers human health. Therefore, advanced diagnostic technology and treatment protocols are urgently needed. The rapid development of nanotechnology is expected to provide new ideas for cancer diagnosis and treatment.

OBJECTIVE

The research aims to comprehensively demonstrate the hotspots of nanotechnology applications in cancer.

METHODS

In this study, an International Patent Classification codes co-occurrence network is constructed to visualize the technology landscape by simultaneously locating and ranking technologies that play an integral role in nanotechnology diffusion and bridging in the field of cancer. In addition, community identification and topic modeling highlight the latent topics in patent documents.

RESULTS

The visualization results of the patent network yield five main clusters: Cluster 0 is a nanoparticle composition delivery system with liposomes as the primary carrier. Cluster 1 is mainly represented by nano-immunotherapy with immune checkpoint inhibitors. Cluster 2 is nano phototherapy based on photodynamic therapy and photothermal therapy. Cluster 3 is diagnostic imaging involving nanotechnology. Cluster 4 is a drug delivery system with nanovesicles and albumin nanoparticles as carriers.

CONCLUSION

It was found that carriers represented by liposomes, vesicles, and albumin nanoparticles are essential nanomaterials in the current anticancer drug delivery systems. Integrating next-generation immunosuppressants and nanotechnology will become an important development direction for future immunotherapy. Organic/inorganic nanomaterials are pivotal in cancer imaging diagnosis and phototherapy.

Exploring the organisational structure of networks for exercise oncology provision: a social network analysis of OnkoAktiv

BACKGROUND

Structured exercise programs provide considerable health benefits for cancer patients. Therefore, various OnkoAktiv (OA) networks were established in Germany with the aim to connect cancer patients with certified exercise programs. However, knowledge about the integration of exercise networks into cancer care systems and conditions of interorganisational collaboration is lacking. The aim of this work was to analyse the OA networks to guide further network development and implementation work.

METHODS

We used methods of social network analysis within a cross-sectional study design. Network characteristics were analysed such as node and tie attributes, cohesion and centrality. We classified all networks into their level of organisational form in integrated care.

RESULTS

We analysed 11 OA networks with 26 actors and 216 ties on average. The smallest network counted 12 actors/56 ties, the largest 52/530. 76% of all actors operated within the medical/exercise sector, serving 19 different medical professions. In smaller "linkage" networks, several individual professionals were linked "from service to service", whereas the more integrated networks revealed a core-periphery-structure.

DISCUSSION

Collaborative networks enable the involvement of professional actors from different operational fields. This study provides an in-depth understanding of underlying organisational structures that provides information for further development of exercise oncology provision.

TRIAL REGISTRATION

Not applicable, as no health care intervention was performed.

Mapping the distribution of health equity research and practice across a university: a network analysis

Introduction

Health equity research spans various disciplines, crossing formal organizational and departmental barriers and forming invisible communities. This study aimed to map the nomination network of scholars at the University of Rochester Medical Center who were active in racial and ethnic health equity research, education, and social/administrative activities, to identify the predictors of peer recognition.

Methods

We conducted a snowball survey of faculty members with experience and/or interest in racial and ethnic health equity, nominating peers with relevant expertise.

Results

Data from a total of 121 individuals (64% doing research on extent and outcomes of racial/ethnic disparities and racism, 48% research on interventions, 55% education, and 50% social/administrative activities) were gathered in six rounds of survey. The overlap between expertise categories was small with coincidence observed between education and social/administrative activities (kappa: 0.27; p < 0.001). Respondents were more likely to nominate someone if both were involved in research (OR: 3.1), if both were involved in education (OR: 1.7), and if both were affiliated with the same department (OR: 3.7). Being involved in health equity research significantly predicted the centrality of an individual in the nomination network, and the most central actors were involved in multiple expertise categories.

Conclusions

Compared with equity researchers, those involved in racial equity social/administrative activities were less likely to be recognized by peers as equity experts.

Enhancing decision-making support by mining social media data with social network analysis

This paper explores the use of social network analysis (SNA) on airlines' online social networks (OSNs) to extract valuable information for decision support, by analyzing interactions and discursive exchanges between users. The research is focused on fostering customer service of an airline company during a strike period, namely by detecting influential customers (whether satisfied or dissatisfied), address pending requests, and enhancing customer satisfaction, thus promoting issue-solving, and increasing responsiveness. The methodology involves analyzing data from the Facebook account of an airline company, using SNA to structure the data, and calculating metrics to detect possible situations to be addressed by customer service. The research concludes that it is possible to extract valuable information for decision support by analyzing the metrics that were built over the interactions and discursive exchanges between OSN users. SNA metrics enable to measure airline's call-center performance in terms of speed of answer and customer satisfaction, to identify active users requiring additional support, as well as highly influential customers who may impact on the overall customer satisfaction, thus helping to resolve issues more efficiently. This study provides both theoretical and practical implications: it contributes to the existing literature by integrating social interaction and SNA for decision support in airline's service context; and it provides practical insights into how companies can use SNA metrics to improve customer service. The research also highlights and corroborates the importance of monitoring social media interactions for decision-making and improving customer service.

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.

Spatial association network of PM2.5 and its influencing factors in the Beijing-Tianjin-Hebei urban agglomeration

In this paper, we empirically study the spatial association network of PM_2.5 and the factors influencing those correlations using the gravity model, social network analysis (SNA), and the quadratic assignment procedure (QAP) based on data from the Beijing-Tianjin-Hebei urban agglomeration (BTHUA) in China from 2005 to 2018. We draw the following conclusions. First, the spatial association network of PM_2.5 exhibits relatively typical network structure characteristics: the network density and network correlations are highly sensitive to efforts to control air pollution, and there are obvious spatial correlations within the network. Second, cities in the center of the BTHUA have large network centrality values, while cities in the peripheral region have small centrality values. Tianjin is a core city in the network, and the spillover effect of PM_2.5 pollution in Shijiazhuang and Hengshui is the most noticeable. Third, the 14 cities can be divided into four plates, with each plate having obvious geographical location characteristics and linkage effects. The cities in the association network are divided into three tiers. Beijing, Tianjin, and Shijiazhuang are located in the first tier, and a considerable number of PM_2.5 connections are completed through these cities. Fourth, differences in geographical distance and urbanization are the main drivers of the spatial correlations of PM_2.5. The greater the urbanization differences, the more likely the generation of PM_2.5 links is, while the opposite is true for differences in geographical distance.

Current status of digital humanities research in Taiwan

Purpose

Review the current research status of the theory, techniques, and practice of digital humanities in Taiwan.

Methods

Select the 8 issues of the Journal of Digital Archives and Digital Humanities from its inception in 2018-2021, and the papers of the 5-year International Conference of Digital Archives and Digital Humanities from 2017 to 2021 as the research data, and conduct text analysis of the collected 252 articles.

Results

From the statistical analysis results, the number of practical articles is the largest, followed by tools and techniques, and the least number of theoretical articles. Text tools and literature research are the most concentrated aspects of digital humanities research in Taiwan.

Limitations

It still needs to be further compared with the current research status of digital humanities in Mainland China.

Conclusions

Digital humanities in Taiwan focuses on the development of tools and techniques, and practical applications of literature and history, and focuses on Taiwan's native culture to form its own digital humanities research characteristics.

Unbalanced global vaccine product trade pattern: A network perspective

Mass vaccination is the most cost-effective intervention in response to public health events. Thus, equitable access to vaccine products is essential to ensure global human health. Based on the global vaccine product trade data from 2000 to 2018 and employing social network analysis, this paper explores the unbalanced pattern of global vaccine product trade and assesses the sensitivity interdependence between countries. Overall, the analysis shows that global vaccine product trade links have long been highly concentrated within developed countries in Europe and America. Nevertheless, with the rise of global and regional hub countries, the global vaccine product trade network has begun to evolve from a unipolar structure with the U.S. as the sole core to a multipolar structure with the U.S. and Western European countries as the core. Meanwhile, emerging countries, represented by China and India, are increasingly participating in the global vaccine product trade network and are beginning to play an important role. The formation of this multipolar pattern has provided countries in the Global South with more options for cooperation in the vaccine product trade and reduces the sensitivity interdependence of network periphery countries on core countries, which consequently reduces the global supply risk of vaccine products.

Evaluation and analysis of leading position in hydrogen fuel cell vehicle innovation network and the influential factors: a case of patent citations in China

Hydrogen fuel cell vehicle industry is of great significance for China to achieve carbon neutrality by 2060 and enhance the international competitiveness in the new energy vehicle industry. We propose a framework to evaluate the leading position in the innovation network of hydrogen fuel cell vehicles and analyze the influential factors of the leading position. First, we construct China's hydrogen fuel cell vehicle innovation network and its two sub-networks through 3528 patents registered in China and applied by 254 Chinese and foreign innovators. Second, the positions of Chinese and foreign innovators in the network are evaluated. Last, the influential factors of the leading position are tested through regression analysis. The main results show that (1) China has formed a hub-and-spoke mode of innovation cluster in hydrogen fuel cell vehicle innovation network, but the inter-provincial innovation cooperation has not been formed in the industrial chain. (2) Universities and research institutes are important innovators in China's hydrogen fuel cell vehicle innovation network. Firms obtain knowledge through collaboration with them, which form an industry-university-research cooperation mode. (3) The number of Chinese leaders in hydrogen fuel cell vehicle network is increasing. Foreign innovators occupy the leading position in fuel cell sub-network, while Chinese innovators are the leaders in hydrogen infrastructure sub-network. (4) The leading position of Chinese innovators in hydrogen infrastructure sub-network is promoted by the patent applications of the universities, the development of equipment manufacturing, the government subsidies, and the competition of electric vehicles, while they are hindered by the scale of traditional automobile industry.

The journey to overdose: Using spatial social network analysis as a novel framework to study geographic discordance in overdose deaths

INTRODUCTION

Drug overdose deaths are often geographically discordant (the community in which the overdose death occurs is different from the community of residence). Thus, in many cases there is a journey to overdose.

METHODS

We applied geospatial analysis to examine characteristics that define journeys to overdoses using Milwaukee, Wisconsin, a diverse and segregated metropolitan area in which 26.72 % of overdose deaths are geographically discordant, as a case study. First, we deployed spatial social network analysis to identify hubs (census tracts that are focal points of geographically discordant overdoses) and authorities (the communities of residence from which journeys to overdose commonly begin) for overdose deaths and characterized them according to key demographics. Second, we used temporal trend analysis to identify communities that were consistent, sporadic, and emergent hotspots for overdose deaths. Third, we identified characteristics that differentiated discordant versus non-discordant overdose deaths.

RESULTS

Authority communities had lower housing stability and were younger, more impoverished, and less educated relative to hubs and county-wide numbers. White communities were more likely to be hubs, while Hispanic communities were more likely to be authorities. Geographically discordant deaths more commonly involved fentanyl, cocaine, and amphetamines and were more likely to be accidental. Non-discordant deaths more commonly involved opioids other than fentanyl or heroin and were more likely to be the result of suicide.

CONCLUSION

This study is the first to examine the journey to overdose and demonstrates that such analysis can be applied in metropolitan areas to better understand and guide community responses.

Racial Discrimination Experiences and Friendship Network Dynamics Among Black and Latinx Youth

Despite a robust volume of evidence documenting adverse effects of racial discrimination experiences on adolescent adjustment outcomes, relatively little is known about the relational consequences of racial discrimination experiences for adolescent friendship networks. To address this gap, this study examines how racial discrimination experiences shape and are shaped by friendship network dynamics in early and middle adolescence. The current study's goals were to explicate whether relational consequences of racial discrimination experiences for friendship network selection differed between interracial and intraracial friendships among Black and Latinx youth, and how these adolescents were influenced by their friends' racial discrimination experiences. Longitudinal social network analysis was used among a sample of predominantly Latinx and Black middle school students from the southwestern U.S. (n = 1034; 50.1% boys, Mage = 12.1, 13.8% White, 18.6% Black, 53.1% Latinx, 14.4% Other race and multiracial). The results showed that Black and Latinx youth preferred intraracial friends. Above and beyond that, Black youth were more likely to have intraracial friendships when the focal individual reported lower levels of general racial discrimination experiences and higher levels of adult-perpetrated racial discrimination experiences. Black and Latinx adolescents reported increases in general racial discrimination experiences over time, as a function of their friends reporting higher levels of racial discrimination (e.g., peer influence). These findings advance developmental research by showing that racial discrimination experiences are consequential for friendship network dynamics by increasing the likelihood of intraracial friend selection among Black youth and through peer influence processes.

Burnout and network centrality as proxies for assessing the human cost of resilient performance

The extra effort of healthcare professionals to provide care is a manifestation of resilient performance (RP), usually going unnoticed due to successful outcomes. However, it is not clear how the human cost of RP can be assessed. This study addresses this gap by investigating the relationships between proxies of RP and its human cost. The proposed approach was tested in a 29-bed intensive care unit (ICU). The centrality of each professional in the advice-seeking social network was considered as the proxy of their contribution to system resilience. A resilience score was calculated for each professional as the product of three network centrality metrics (in-degree, closeness, and betweenness) and two non-network attributes, namely their availability and reliability. Professionals' burnout was the proxy of the human cost of RP, assessed through the Maslach Burnout Inventory, composed of 22 items divided into a triad of emotional exhaustion, depersonalization, and personal accomplishment. Both questionnaires, for social network analysis and burnout, included socio-demographic questions and were answered by 99.0% of the professionals. Results indicated a weak correlation between emotional exhaustion and the resilience score (p = 0.008). This score was also weakly correlated with working overtime (p = 0.005). Overall, findings provided initial evidence that RP as measured in our study matters to burnout, and that the two proxies are exemplars of applying a more general reasoning that might be valid for other proxies.

A comprehensive review of greenhouse gas based on subject categories

Greenhouse gas (GHG) concentrations have continued to increase in the atmosphere and unequivocally warmed the climate system, and human activities contribute significantly to the growth impact. Various research puzzles and potential mitigation evidence involving GHG related research (GRR) need to be explored and deciphered from large-scale literature records to provide a whole picture and clear scientific view on the current state of GRR to promoting action on climate change. By combining Bibexcel-based bibliometrics with Pajek's social network analysis, we explore the literature statistics and interdisciplinary characteristics of GRR, and identify frequently debated topics in interdisciplinary by going deep into the texts of those classical literature. We found the trend of GRR's publications in the Environmental/Ecology group increased exponentially with an annual growth rate of 47.3 % and continue to expand in 13 subject categories. There are four types of relationships in the author cooperation, which gradually promote the cross-study of GHG in different subject categories, and the regional cooperation relations are relatively stable involving North America, Asia, Europe, Oceania, and South America. Those classical literature are widely distributed in six interdisciplinary categories, specifically 'Agronomy, Forestry and Zoology', 'Biodiversity Conservation and Ecology', 'Engineering, Environmental and Green & Sustainable Science & Technology', 'Geography and Remote Sensing', 'Limnology, Marine & Freshwater Biology and Water Resources', and 'Public, Environmental & Occupational Health'.

The Value of Interpersonal Network Continuity for College Students in Disruptive Times

The COVID-19 pandemic-related social distancing practices that colleges implemented in Spring 2020 disrupted the typical mechanisms of propinquity (physical proximity) and homophily (shared characteristics) that physical institutions rely on to help students build and maintain relationships critical to learning and wellbeing. To explore how social distancing shaped students' academic and social networks and associated educational outcomes, we conceptualized it as a "network shock" and collected unique ego network data in April 2020. For participating students, maintaining interactions with the same set of individuals before and after social distancing was related to more positive outcomes across a range of self-reported wellbeing and learning indicators. On average, students experienced a loss of frequent academic contacts, while they maintained or replaced social interactions in their interpersonal networks after social distancing. Our investigation of the ways students experienced changes in their social and academic networks after a loss of physical proximity points to the role of interpersonal interaction network continuity for fostering wellbeing and learning in times of disruption, as well as the potential need for support in maintaining or rebuilding academic networks.

Effectiveness of hierarchical medical system policy: an interrupted time series analysis of a pilot scheme in China

The Chinese healthcare system faces a dilemma between its hospital-centric approach to healthcare delivery and a rapidly aging population that requires strong primary care. To improve system efficiency and continuity of care, the Hierarchical Medical System (HMS) policy package was issued in November 2014 and fully implemented in 2015 in Ningbo, Zhejiang province, China. This study aimed to investigate the impact of the HMS on the local healthcare system. We conducted a repeated cross-sectional study with quarterly data collected between 2010 and 2018 from Yinzhou district, Ningbo. The data was analysed with an interrupted time series (ITS) design to assess the impact of HMS on the changes in levels and trends of three outcome variables: primary care physicians' (PCPs') patient encounter ratio (i.e., the mean quarterly number of patient encounters of PCPs divided by that of all other physicians), PCP degree ratio (i.e., the mean degree of PCPs divided by the mean degree of all other physicians, with the mean degree revealing the mean activity and popularity of physicians, which reflected the extent to which he/she coordinated with others in delivering health services), PCP betweenness centrality ratio (i.e., the mean betweenness centrality of PCPs divided by the mean betweenness centrality of all other physicians; the mean betweenness centrality was interpreted as the mean relative importance of physicians within the network, indicating the centrality of the network). Observed results were compared with counterfactual scenarios computed based on pre-HMS trends. Between January 2010 and December 2018, 272,267 patients visited doctors for hypertension, a representative non-communicable disease with a high prevalence of 44.7% among adults aged 35-75 years, amounting to a total of 9,270,974 patient encounters. We analysed quarterly data of 45,464 observations over 36 time points. Compared to the counterfactual, by the fourth quarter of 2018, the PCP patient encounter ratio rose by 42.7% (95%CI: 27.1-58.2, p<0.001), the PCP degree ratio increased by 23.6% (95%CI: 8.6-38.5, p<0.01), and the PCP betweenness centrality ratio grew by 129.4% (95%CI: 87.1-171.7, p<0.001). The HMS policy can incentivize patients to visit primary care facilities and enhance the centrality of PCPs within their professional network.

Social network characteristics of Black African and Caribbean people with psychosis in the UK

Poorer social networks predict more coercive pathways to care and other adverse outcomes in people with psychosis. People from Black African and Caribbean backgrounds have more negative experiences within UK mental health care systems and family relationships often breakdown. This study aimed to examine the social network characteristics of Black African and Caribbean people experiencing psychosis and associations between network characteristics and severity of psychosis, negative symptoms, and general psychopathology. Fifty-one participants completed social network mapping interviews (a gold standard approach to assessing social network composition) and the Positive and Negative Syndrome Scale. This is the first study to explicitly measure social network size amongst Black people with psychosis living within the UK and results showed that participants' social network size (mean = 12) was comparable to that of other psychosis samples. Networks were of moderate density and comprised disproportionately more relatives than other relationship types. Poor network quality was related to more severe psychosis symptoms suggesting that social network quality may be an important factor in influencing the severity of psychosis. Findings highlight the need for community-based interventions and family therapies to mobilise sources of social support for Black people with psychosis within the UK.

Research on the promotion of new energy vehicles based on multi-source heterogeneous data: consumer and manufacturer perspectives

Under the background of green development, new energy vehicles, as an important strategic emerging industry, play a crucial role in energy conservation and emission reduction. In the post-epidemic era, steadily promoting the promotion of new energy vehicles will be a hot topic. Based on multi-source heterogeneous data, combined with the latent Dirichlet allocation topic model, social network analysis, and econometric methods, this paper explores whether individual purchase decisions and company-level cooperative research and development will promote the promotion of new energy vehicles. The results show that whether it is battery electric vehicles, hybrid electric vehicles or plug-in hybrid electric vehicles, users are more concerned about space dimension, power performance, and design style. Patent collaboration network analysis indicates that new energy vehicle enterprises are establishing close partnerships, which will urge the promotion of new energy vehicles. An interesting test result found that for short-term innovation, new energy vehicles enterprises should invest more patent research and development in battery electric vehicles and hybrid electric vehicles models to better accelerate the promotion of new energy vehicles.

Social network position, trust behavior, and neural activity in young adolescents

Our social interactions take place within numerous social networks, in which our relationships with others define our position within these networks. In this study, we examined how the centrality of positions within social networks was associated with trust behavior and neural activity in 49 adolescents (M_age = 12.8 years, SD_age = 0.4 years). The participants played a trust game with a cartoon animation as a partner, which showed adaptive behavior in response to the participant and was generally untrustworthy. Social network positions were obtained in secondary school classrooms where the participants and their classmates reported on who their friends were. Using social network analysis, a score was calculated that indicated the centrality of everyone's position within the friendship network. The results showed that more central social network positions were associated with higher levels of initial trust behavior, although no evidence was found for a relationship between network position and the adaptation of trust behavior. The results of the functional MRI analyses showed that the centrality of the network positions was positively associated with caudate activity when making trust decisions. Furthermore, the adolescents with more central network positions also showed stronger increases of caudate activity when the partner's return was processed compared to the adolescents with less central network positions. The current study provides initial evidence that social network positions in friendship networks relate to socio-cognitive behavior and neural activity in adolescents.

Uncovering four domains of energy management in palm oil production: a sustainable bioenergy production trend

This study aims to identify current and future research trends in sustainable bioenergy production. The systematic review is conducted using a social network analysis method. The data were collected from the Web of Science and Scopus database (2010-2021). Out of the 1747 articles reviewed, 100 were found to be relevant for thematic analysis. The results uncovered four domains of palm oil biodiesel production for sustainable energy management: (1) renewable energy, (2) biodiesel, (3) bioenergy, and (4) life cycle assessment. This study has proposed a sustainable bioenergy production framework based on the four main domains. The framework sheds light on the future of sustainable bioenergy production. The findings indicate the potential growth of the research topic, including sustainable bioenergy, palm oil biodiesel, energy management, and carbon emissions reduction. Future research must incorporate the energy management framework to design a sustainable energy management ecosystem strategy. In addition, the industry must comply with the international sustainability standard and sustainable development goals to manage the energy supply chain and consistency of palm oil biodiesel production.

Chimpanzee communities differ in their inter- and intrasexual social relationships

Male and female human social bonding strategies are culturally shaped, in addition to being genetically rooted. Investigating nonhuman primate bonding strategies across sex groups allows researchers to assess whether, as with humans, they are shaped by the social environment or whether they are genetically predisposed. Studies of wild chimpanzees show that in some communities males have strong bonds with other males, whereas in others, females form particularly strong intrasex bonds, potentially indicative of cultural differences across populations. However, excluding genetic or ecological explanations when comparing different wild populations is difficult. Here, we applied social network analysis to examine male and female social bonds in two neighbouring semiwild chimpanzee groups of comparable ecological conditions and subspecies compositions, but that differ in demographic makeup. Results showed differences in bonding strategies across the two groups. While female-female party co-residence patterns were significantly stronger in Group 1 (which had an even distribution of males and females) than in Group 2 (which had a higher proportion of females than males), there were no such differences for male-male or male-female associations. Conversely, female-female grooming bonds were stronger in Group 2 than in Group 1. We also found that, in line with captive studies but contrasting research with wild chimpanzees, maternal kinship strongly predicted proximity and grooming patterns across the groups. Our findings suggest that, as with humans, male and female chimpanzee social bonds are influenced by the specific social group they live in, rather than predisposed sex-based bonding strategies.

Risk identification and analysis for the green redevelopment of industrial brownfields: a social network analysis

The green redevelopment of industrial brownfields (GRIB) is an important means to solve the shortage of urban land resources and realize sustainable urban renewal and green development. The identification and analysis of risk factors in GRIB projects are of immense significance for completing construction tasks and ensuring the planned benefits. In this study, work and risk breakdown structures and expert interviews are used to construct the risk network model of a GRIB project, based on three dimensions: process, subject, and system sources. The software package UCINET is used to conduct social network analysis and determine the key risk factors and relationships. The results of this study suggest that the four risk factors with the most brokerage roles and the highest node betweenness centralities are located at the core of the network; the six risk relationships with the highest line betweenness centralities are those with the strongest transmission capacities; the key risk factors are mostly response and stress risks; the main source is the design unit; and the key risk relationships are the influence of the decision-making stage on the design stage and of the design stage on the construction stage. Surpassing the limitations of traditional linear research, this study explains the internal relationship among the risk factors of GRIB projects and identifies the risk factors that play a brokerage role and the risk relationship that plays a conductive role, providing a theoretical basis for introducing social network analysis tools into the risk assessment of such complex construction projects.

Macaque progressions: passing order during single-file movements reflects the social structure of a wild stump-tailed macaque group

Inferring the latent structures of social organisations is a central theme in animal ecology. Sophisticated theoretical frameworks underpin the study of various primate social systems. Single-file movements, defined as serially ordered patterns of animals, reflect intra-group social relationships and provide a key to understanding social structures. Here, we analysed automated camera-trapping data on the order of progression of single-file movements in a free-ranging group of stump-tailed macaques to estimate the social structure of the group. The sequence of single file movements showed some regularities, particularly for adult males. Social network analysis identified four community clusters (subgroups) corresponding to the social structures reported for these stumptailed macaques, i.e. males that had copulated more frequently with females were spatially clustered with females, but males that had copulated less frequently were spatially isolated from females. Our results suggest that stumptailed macaques move in regular, socially determined patterns that reflect the spatial positions of adult males and are related to the social organisation of the species.

Social isolation of unfamiliar cattle by groups of familiar cattle

Domestic herbivores show a strong motivation to form associations with conspecifics and the social dynamics of any group is dependant on the individuals within the group. Thus, common farm management practices such mixing may cause social disruption. Social integration of new group members has previously been defined as a lack of aggressive interactions within the group. However, a lack of aggression among group members may not represent full integration into the social group. Here we observe the impact of disrupting groups of cattle via the introduction of an unfamiliar individual, on the social network patterns of six groups of cattle. Cattle contacts between all individuals in a group were recorded before and after the introduction of the unfamiliar individual. Pre-introduction, resident cattle showed preferential associations with specific individuals in the group. Post-introduction, resident cattle reduced the strength of their contacts (e.g., frequency) with each other relative to the pre-introduction phase. Unfamiliar individuals were socially isolated from the group throughout the trial. The observed social contact patterns suggest that new group members are socially isolated from established groups longer than previously thought, and common farm mixing practices may have negative welfare consequences on introduced individuals.

Network Governance at the Margin of the State: Rural Drinking Water Communities in Chile

We focus on the relationship between the network structure of Chilean rural drinking water associations (APRs) and effective governance outcomes regarding the provision of infrastructure and drinking water to peripheral rural communities in the Valparaiso region. Based on a comparative regional multi-method case study, we assess the coherence of differences in the governance network structure with the corresponding governance outcomes. Using qualitative interviews, participant observation, and a network survey of collaboration and legitimacy relationships among leaders of local APRs, we find that when isolated APRs establish collective organizations, they can generate better governance outcomes even without support from the state. We demonstrate that higher levels of collaboration as well as a more integrative distribution of legitimacy relations in the network are coherent with more effective governance outcomes. The findings suggest to strengthen social and organizational capacity at the local level of water governance in order to overcome the challenges of megadroughts and of a lack of public infrastructure in peripheral rural areas.

A wicked environmental challenge: collaboration network for free-ranging dog management in an urban environment

Invasive species possess wide-ranging social and ecological impacts globally. Although the ecological impacts are well studied, social aspects especially in developing countries are often poorly understood. Free-ranging dogs (FRDs) (Canis familiaris) are the most abundant carnivore on earth with a high level of invasion. Recently, the presence of FRDs in the Jiroft city in southern Iran has increased, and local managers have not yet developed a coherent management plan. Given the high rate of human bites by FRDs in this region, a principled management plan with integrated collaboration between the relevant organizations is necessary. To better understand collaboration networks, we interviewed employees of three relevant governmental organizations about their collaboration with other organizations toward FRD management. Our objective in this study was to (1) assess the collaboration between the municipality, provincial offices of veterinary medicine, and health network and (2) predict the behavioral tendencies of network actors based on their current position in the FRD management network. Although most employees have never worked together to manage FRDs, our results showed that most of the interviewees did not evaluate the role of other organizations in FRD management as beneficial. Moreover, the current assessment of the employees of the two municipal and health organizations affects their current collaboration in the management of FRDs. Also, the current collaboration has a significant impact on their intention to collaborate in the future. We make suggestions for improving collaboration in managing FRDs in this region.

Data-driven evaluation framework for the effectiveness of rural vitalization in China: an empirical case study of Hubei Province

Rural vitalization (RV) has attracted more and more attention in China, especially since the Rural Vitalization Strategy (RVS) was proposed to restrict rural decline in 2017. The evaluation of RV is an effective means to objectively identify the characteristics and problems of rural development, so exploring scientific and rational evaluation methods is important for sustainable rural development. Therefore, this study builds a data-driven evaluation framework from a "bottom-up" perspective, and selects Hubei Province as the object to evaluate the effectiveness of RV. The evaluation index system is formed based on the concept and connotation of RV, which contains six dimensions, namely thriving businesses (TB), pleasant living environments (PLE), social etiquette and civility (SEC), effective governance (EG), living in prosperity (LP), and organization system (OS). The empirical results indicate that there is a low level of variation of the total scores but an obvious disparity in the dimensional scores in 13 prefecture-level and 83 county-level regions. At county-level, the regional development stage has an impact on the effectiveness of RV, and regions with a higher economy or endowed with better resources perform better. The results of spatial analysis further reveal that there is regional agglomeration as well as differences in various dimensions, and regions with characteristic industries or policy support perform better. Compared with the traditional evaluation method, differentiated evaluation objectives and diversified data are considered in the evaluation process of this study. The results and discussion shown in this study could provide empirical evidence for policymakers to effectively promote RV in the future.

Revealing the Relational Mechanisms of Research for Development Through Social Network Analysis

Achieving impact through research for development programmes (R4D) requires engagement with diverse stakeholders across the research, development and policy divides. Understanding how such programmes support the emergence of outcomes, therefore, requires a focus on the relational aspects of engagement and collaboration. Increasingly, evaluation of large research collaborations is employing social network analysis (SNA), making use of its relational view of causation. In this paper, we use three applications of SNA within similar large R4D programmes, through our work within evaluation of three Interidsiplinary Hubs of the Global Challenges Research Fund, to explore its potential as an evaluation method. Our comparative analysis shows that SNA can uncover the structural dimensions of interactions within R4D programmes and enable learning about how networks evolve through time. We reflect on common challenges across the cases including navigating different forms of bias that result from incomplete network data, multiple interpretations across scales, and the challenges of making causal inference and related ethical dilemmas. We conclude with lessons on the methodological and operational dimensions of using SNA within monitoring, evaluation and learning (MEL) systems that aim to support both learning and accountability.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1057/s41287-023-00576-y.

The Helping Networks of Transgender Women Living with HIV

Transgender women living with HIV face significant barriers to healthcare that may be best addressed through community-centered interventions holistically focused on their HIV-related, gender-related, and other important needs. Community health ambassador (CHA) interventions (education and training programs designed to engage communities and community leaders in health promotion) may be an effective option, though information about the natural helping networks of this vulnerable population is too limited to inform the implementation of this approach. This study uses social network analysis to describe the natural helping networks of transgender women living with HIV, their help-seeking patterns for HIV-related, gender-related, and ancillary resources, and the characteristics of potential network ambassadors. From February to August 2019, transgender women living with HIV in the US (N = 231) participated a 30-min online survey asking them to describe their natural helping networks (N = 1054). On average, participants were embedded within natural helping networks consisting of 4-5 people. They were more likely to seek help from informal network members vs. formal service providers (p < .01), and from chosen family and partners/spouses (p < .05) above other social connections. Older network members (p < .01), other transgender women (p < .05), and those with whom they regularly engaged face-to-face (p < .01) (vs. social technology) were identified as potential network ambassadors for HIV-, gender-related, and other important issues. These findings suggest an opportunity to develop CHA interventions that leverage existing help networks and potential network ambassadors to promote equitable access to HIV, gender-affirming, and other crucial resources among this medically underserved group.

Discourse about higher education on Twitter in early phases of COVID-19: A crisis management social network analysis

The emergence of the COVID-19 pandemic brought changes and efforts for adaption to the new environment in every industry, including higher education. The present study, drawing on crisis management theory as a framework, aimed to understand information and communication sharing behaviors of the higher education community during the pandemic by exploring patterns and discourse on social media. Such analysis provides insight into how information is gained, shared, and used. Tweets including the hashtag #highered were retrieved at five time points in March and August 2020-M1 (retrieved on March 3), M2 (March 17), A1 (August 4), A2 (August 11), and A3 (August 18). Using a social network analysis tool, NodeXL, the collected tweets were analyzed by social network structure, topic, and influencer. Results showed that #highered was used widely in the early stages of the pandemic. The relevant conversation rapidly evolved, as did the prominent influencers. Over time, the conversation centered on the pandemic, the implications of the sudden shift to online learning, and then the subsequent effect on universities, students, faculty, and staff. A crisis preparation phase continued through August 2020, but drivers of information transitioned from well-known news outlets prior to the pandemic to individuals directly experiencing the pandemic. Future research should analyze the validity of information shared by individuals during key decision points of the pandemic and whether higher education is susceptible to the growing spread of disinformation through social media when formulating policy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10639-023-11590-2.

The Diffusion of Smoking: Association Between School Tobacco Policies and the Diffusion of Adolescent Smoking in 38 Schools in 6 Countries

Social network research has evidenced the role of peer effects in the adoption of behaviours. Little is known, however, about whether policies affect how behaviours are shared in a network. To contribute to this literature, we apply the concept of diffusion centrality to school tobacco policies and adolescent smoking. Diffusion centrality is a measure of centrality which refers to a person's ability to diffuse a given property-in our case, smoking-related behaviours. We hypothesized that stronger school tobacco policies are associated with less diffusion centrality of smoking on school premises and of smoking in general. A whole network study was carried out in 2013 and 2016 among adolescents (n = 18,805) in 38 schools located in six European cities. Overall, diffusion centrality of smoking in general and of smoking on school premises significantly decreased over time. Diffusion centrality of smoking significantly decreased both in schools where the policy strengthened or softened over time, but for diffusion of smoking on school premises, this decrease was only significant in schools where it strengthened. Finally, stronger school tobacco policies were associated with lower diffusion centrality of smoking on school premises and of smoking in general, though to a lesser extent. With such policies, smoking may, therefore, become less prevalent, less popular, and less clustered, thereby lowering the risk of it spreading within networks in, and even outside the school.

An integrated framework for industrial symbiosis performance evaluation in an energy-intensive industrial park in China

Industrial symbiosis (IS) is an important tool to achieve green development for industrial parks. It is necessary to evaluate the IS performance for monitoring and managing the development of IS system. This study proposed an integrated framework to assess the IS performance based on the energy-intensive industrial park. Firstly, we established a Conceptual model of symbiotic coupling of three industries (iron and steel, thermal power, and cement). Then, the conceptual model was applied to extend the existing IS system in the energy-intensive industrial park. Finally, the IS performance of the extended IS system was evaluated. We verified this framework in Red flag cannel park (RFCP). The IS performance assessment in RFCP found that the existing IS activities produced significant multiple benefits and environmental impact reduction. For example, the existing IS activities produced 970.20 kt of low-carbon benefits, which accounted for 19% of the CO₂ emissions in RFCP. However, after extending the existing symbiotic system combined with the conceptual model proposed in this study, we found that there still was a large amount of symbiotic potential (the reuse of waste heat, BF slag, gypsum) waiting to be developed in RFCP. In addition, we also found that the resilience of existing IS network in RFCP was weak and need to be further perfected. In general, in the further development and perfection of IS system in RFCP, the manager should not only focus on the development of IS activities among energy-intensive enterprises but also strive to foster more influential enterprises to enhance the anti-risk ability of IS network. The result indicates the integrated framework can provide support for the development and perfection of IS system in energy-intensive industrial parks.

How can Chinese metropolises drive global carbon emissions? Based on a nested multi-regional input-output model for China

Given metropolises' participation in complex regional and global trade networks, they have huge demands for vast carbon-embodied intermediate and final goods. To clarify embodied carbon transfers of metropolises in regional and international trade, a metropolis-centered model was constructed by nesting the World's multi-regional input-output table and China's multi-regional input-output (CMRIO) table. Based on this model, we analyzed the multi-scale impact of two typical Chinese metropolises, namely Beijing and Shanghai, on global carbon emissions. Structural decomposition analysis and social network analysis (SNA) were used to explore the driving factors of consumption-based carbon (CBC) and the roles of metropolises in the carbon networks. Results showed that both Beijing and Shanghai are net embodied carbon consumers, which respectively drove 231.19 and 219.52 Mt global carbon emissions in 2017. These figures were underestimated by 12.54 % and 15.41 % when using the CMRIO. After China's economy entered a new normal, instead of technological progress, structural adjustment became the prominent factor driving the CBC reduction of metropolises. During 2012-2017, the consumption structure optimization reduced 18.87 and 32.48 Mt CBC in Beijing and Shanghai, respectively. Compared with other domestic regions, the CBC of Beijing has continued to increase, whereas that of Shanghai has declined. At the international scale, the combined net carbon emission imported by the two metropolises was 88.43 Mt in 2017, equivalent to 18.09 % of China's total carbon deficit. This indicates that metropolises have become pioneering regions for China to alleviate the carbon deficit in international trade. By using SNA, we further found that both metropolises are crucial carbon consumers in the global carbon network, with strong stability and obvious hub roles. Furthermore, various urban functions and geographical locations form the heterogeneous structural characteristics of CBC in the two metropolises, highlighting the need for different strategies for embodied carbon mitigation in these metropolises.

Mining and analysing online social networks: Studying the dynamics of digital peer support

In recent years, the rapid growth of user-generated content has led to much research evaluating the patterns of online information exchange. These studies demonstrate that online communities are valuable data sources which provide rich, longitudinal data that would otherwise be difficult, if not impossible to access. Given the increased research interest, mining and analysing online social networks has become an important research domain, encompassing a variety of approaches. To analyse the large number of observations commonly found in online communities, we propose to first mine the data using a so-called Webscraper and then combine Social Network Analysis (SNA) with Sentiment Analysis to explore both content and relationships. The hands-on approach described in this article is targeted at researchers without a background in technical disciplines. Instead of focusing on some of the specific algorithms that facilitate the mining and analysis of online data, we describe how to use and combine out-of-the-box solutions to collect and analyse the online network data. Moreover, we document the steps taken and present important lessons learnt throughout the process of collecting and analysing data from an online health community with 108,569 registered users who contributed to 197,980 discussions with a total of 484,250 replies. In sum, our method proposes to:•Extract all relevant data from an openly accessible online community using a Webscraper.•Determine and visualise the relationships between users and the properties of the social network as a whole using Social Network Analysis.•Conduct Sentiment Analysis to detect the emotional tone of the online contributions, and to possibly infer further variables from the text such as the personality characteristics of users.

Spatial correlation network characteristics of embodied carbon transfer in global agricultural trade

Agricultural carbon emission is an important cause of climate change, and the carbon transfer caused by agricultural trade is a key area related to carbon emissions of all countries. Based on the Eora database, this paper aims to constructs a multi-region input-output database of 185 countries or regions, analyzes a spatial correlation network of embodied net carbon transfer in global agricultural trade by using UCINET, selects multi-dimensional network measurement indicators, and comprehensively studies the global evolution characteristics and functional features of network plate role of embodied carbon transfer in the global agricultural trade. The result shows that the embodied net carbon transfer network of global agricultural trade is densely connected, the spatial correlation spillover effect is significant, and the edge of the network core structure is clear. On the one hand, the top four countries or regions in terms of embodied carbon outflow in agricultural trade are the USA, Australia, Vietnam, and China. On the other hand, the top four countries or regions of embodied carbon inflow are Malaysia, Central Africa, Singapore, and Serbia. From the perspective of outdegree, indegree, proximity centrality, and intermediary centrality, Cambodia, the Netherlands, Vietnam, Ghana, and South Africa, with the high frequency of the shortest path of the globally embodied net carbon transfer network, have a strong influence and linking facility in spatial correlation and have a strong control ability to the spatial correlation of other countries or regions. The embodied carbon emission network of global agricultural trade can be divided into four sectors: main spillover, two-way spillover, broker, and main benefit. The main spillover segment, constituted by the USA, India, Germany, and China, has significant embodied carbon spillover effects on the internal segment and other segments. It is the main embodied carbon spillover sector of embodied net carbon transfer of global agricultural trade. Countries should reasonably allocate the responsibility of carbon reduction according to the trading embodied carbon transfer and made efforts to optimize the export structure of agricultural products.

Social network analysis of Twitter interactions: a directed multilayer network approach

Effective employment of social media for any social influence outcome requires a detailed understanding of the target audience. Social media provides a rich repository of self-reported information that provides insight regarding the sentiments and implied priorities of an online population. Using Social Network Analysis, this research models user interactions on Twitter as a weighted, directed network. Topic modeling through Latent Dirichlet Allocation identifies the topics of discussion in Tweets, which this study uses to induce a directed multilayer network wherein users (in one layer) are connected to the conversations and topics (in a second layer) in which they have participated, with inter-layer connections representing user participation in conversations. Analysis of the resulting network identifies both influential users and highly connected groups of individuals, informing an understanding of group dynamics and individual connectivity. The results demonstrate that the generation of a topically-focused social network to represent conversations yields more robust findings regarding influential users, particularly when analysts collect Tweets from a variety of discussions through more general search queries. Within the analysis, PageRank performed best among four measures used to rank individual influence within this problem context. In contrast, the results of applying both the Greedy Modular Algorithm and the Leiden Algorithm to identify communities were mixed; each method yielded valuable insights, but neither technique was uniformly superior. The demonstrated four-step process is readily replicable, and an interested user can automate the process with relatively low effort or expense.

Comment on the article: The state of social science research on COVID‑19

A well-written and interesting article was published on November 21, 2021. Future relevant studies, however, may be improved by implementing (1) a framework that outlines the overall research; (2) an author-weighted scheme (AWS) that accurately quantifies the contributions of entities to articles; and (3) a more appropriate size for the nodes representing the proportional counts for each entity in social network analysis (SNA). VOSviewer was used to construct and visualize the scientometric networks and the relation-based analyses included three categories: (1) citation relations, (2) word cooccurrences, and (3) coauthorship relations. Nevertheless, the counts for each topical entity have not been consistently integrated. As a result, the nodes of the keyword co-occurrence network are large when compared to the number of connections between the entities or terms (i.e., the total number of relationships between co-occurring terms or entities). Additionally, all weighted counts in keywords (or the total link strength of a country/region) should equal the total number of documents (e.g., n = 9954 in that article). This would lead to biases in the calculation of publications (or citations) for entities, as is common in traditional SNA. This node illustrates a study framework and a couple of AWSs (i.e., equal and nonequal AWSs) to improve the article, and discusses the need to understand the requirement that the total centrality degree in SNA equals the total number of documents (or citations).

Exploring Korean adolescent stress on social media: a semantic network analysis

Background

Considering that adolescents spend considerable time on the Internet and social media and experience high levels of stress, it is difficult to find a study that investigates adolescent stress through a big data-based network analysis of social media. Hence, this study was designed to provide basic data to establish desirable stress coping strategies for adolescents based on a big data-based network analysis of social media for Korean adolescent stress. The purpose of this study was to (1) identify social media words that express stress in adolescents and (2) investigate the associations between those words and their types.

Methods

To analyse adolescent stress, we used social media data collected from online news and blog websites and performed semantic network analysis to understand the relationships among keywords extracted in the collected data.

Results

The top five words used by Korean adolescents were counselling, school, suicide, depression, and activity in online news, and diet, exercise, eat, health, and obesity in blogs. As the top keywords of the blog are mainly related to diet and obesity, it reflects adolescents' high degree of interest in their bodies; the body is also a primary source of adolescent stress. In addition, blogs contained more content about the causes and symptoms of stress than online news, which focused more on stress resolution and coping. This highlights the trend that social blogging is a new channel for sharing personal information.

Conclusions

The results of this study are valuable as they were derived through a social big data analysis of data obtained from online news and blogs, providing a wide range of implications related to adolescent stress. Hence this study can contribute basic data for the stress management of adolescents and their mental health management in the future.

An employee retention model using organizational network analysis for voluntary turnover

Contemporary research of employee social network analysis has grown far beyond the conventional wisdom of network and turnover theory; however, what is missing is a comprehensive review highlighting new perspectives and network constructs from a retention viewpoint. Since turnover is a concurrent component of retention, the analysis of the factors of quit propensity can result in a pre-emptive strategy for retention. This paper aims to capture the current state of the field and proposes a conceptual model for retention by exploring network position, centrality measures, network type, and the snowball effect. We identified 30 papers exploring voluntary turnover in social network constructs. Findings show that central network position is not always associated with negative turnover. Eigenvector, structural holes, and K-shell also prove to be a strong predictor of turnover. The snowball turnover of employees in similar network positions is pronounced in scenarios where employee sentiment is negative with poor group efficacy, entrepreneurship, and group values. This paper focuses on several themes to coalesce different determinants of an organizational network to demonstrate how social network theory has evolved to predict employee turnover. The resulting conceptual model suggests how to identify star performers and propose retention strategies.

Calling for justice with #JusticeforBreonnaTaylor: a case study of hashtag activism in the evolution of the black lives matter movement

Taking a stage-based approach, before and after the release of the 15-h audio recording files of the grand jury's inquiry on the Breonna Taylor case on October 2, 2020, this study examined the #JusticeforBreonnaTaylor Twitter networks. By employing multimethodology, including natural language processing, social network analysis, and qualitative textual analysis, I examined keys connectors of the two Twitter networks and investigated major themes conducting thematic analysis of network discourses and highly associated hashtags with the hashtag #JusticeforBreonnaTaylor. In both networks, several key stakeholders, such as Benjamin Crump, Danial Cameron, and Black women activists were identified as key connectors along with social activists and ordinary participants. Demanding justice to the case was the core agenda of the hashtag activism. The findings of the study revealed that the participants not only shared breaking news and important information but also organized protests and routinely tagged people to spread messages about the Taylor's case on Twitter. The participants conversed major issues about the Taylor case and set the agendas for the next action, such as encouraging to take part in voting for the 2020 presidential election. The thematic analysis concurrently demonstrated that the network participants strongly demanded legal prosecution to the three Louisville cops that involved in the act of killing Breonna Taylor during the botched raid in her apartment.