Social Networks Research Articles

Examining the Relationship Among Social Cognitive Theory-Based Constructs, Physical Activity, and Blood Pressure in Young- and Middle-Aged Adults Living With Hypertension.

Psychosocial factors significantly influence lifestyle changes in adults with hypertension. However, research focusing specifically on these factors in young- and middle-aged adults-especially those newly diagnosed within the first 5 years-is limited. This cross-sectional study aimed to examine the relationship between psychosocial factors guided by Social Cognitive Theory (perceived stress, self-efficacy, outcome expectancy, and functional and workplace support), physical activity, and blood pressure in young- and middle-aged Thai adults with hypertension. The analysis encompassed 400 adults with hypertension (Mage = 47.98 years; SD = 7.66), with nearly 60% being female from 25 primary care settings in a Thai province. Confirmatory factor analysis validated latent variables, followed by structural equation modeling with maximum likelihood and robust standard errors to analyze direct and indirect effects on physical activity and blood pressure. Findings highlight self-efficacy in physical activity as a significant predictor of moderate-to-vigorous physical activity, while functional support correlated with reduced systolic blood pressure. Moderate-to-vigorous physical activity mediated the relationship between self-efficacy or functional support and systolic blood pressure. Hypertension duration (diagnosis ≤12 months vs >12 months) moderated the relationship between moderate-to-vigorous physical activity or functional support and diastolic blood pressure. Our research presents a new, theory-driven perspective on how psychosocial factors could affect blood pressure levels through physical activity among younger adults newly diagnosed with hypertension. Nurses can leverage this insight by providing education to enhance confidence and engage patients' social networks in supporting their participation in physical activity, thereby improving blood pressure management.

Identifying scenarios for renewable energy development in Iran: the role of collaborative governance

ABSTRACT This study examines collaborative governance scenarios for renewable energy development in Iran, emphasizing the role of stakeholder engagement in overcoming development obstacles. Initially, we identified key actors and obstacles to renewable energy development through a literature review and expert interviews. Using expert questionnaires and a two-mode social network analysis, we identified the ideal situation for overcoming obstacles to renewable energy development. Then, we prioritized obstacles using the Fuzzy Delphi method. We also discussed collaborative governance scenarios in Iran based on the Cross-Impact Balances (CIB) method. The results indicated that the network comprises nine actors and eleven obstacles, organized into five layers, interconnected by 45 links. We construct eleven distinct scenarios illustrating pathways toward enhanced governance structures. Our findings highlight the need to enhance several key components of collaborative governance scenarios in new energy development. These include informing all stakeholders, encouraging private sector investment while reducing fossil fuel subsidies, and ensuring stakeholder participation in providing initial financial capital. The findings underscore the accelerating transition in oil-rich economies, necessitating targeted policy interventions. While Iran is the focal case, our study offers actionable insights for oil-rich economies transitioning toward sustainable energy systems. Our findings highlight that collaborative governance can enhance diversity among renewable energy actors in oil-rich countries with weak governance. Clear, scenario-based recommendations offer a roadmap for decision-makers, helping bridge existing governance gaps and enhancing renewable energy strategies.

Association between social capital and mortality among community-dwelling older adults in Myanmar 2018–2022: a prospective cohort study

BackgroundHealthy aging is crucial in Asia given its rapidly aging society. Social capital, which refers to the resources derived from social networks, norms, and trust that facilitate cooperation and collective action within a community or society, has demonstrated health benefits for older adults. However, its impact varies by country. Most research focuses on high-income countries, with little attention on low- and middle-income countries.MethodsThis prospective cohort study examined the effects of social capital on all-cause mortality among older adults in Myanmar from 2018 to 2022, using structured questionnaires based on the Japan Gerontological Evaluation Study. Multistage random sampling and face-to-face interviews were conducted with community-dwelling older adults aged 60 and above in Yangon and Bago in 2018. Subsequently, three waves of follow-up telephone surveys were conducted in 2020, 2021, and 2022. The questionnaires evaluated three components of social capital: civic participation, social cohesion, and social support, alongside baseline demographic information. Their impact on all-cause mortality was assessed using the Cox proportional hazards model with multiple imputations, adjusting for potential confounders including age, gender, body mass index, self-rated health, socioeconomic status, lifestyle, illness, and residential area.ResultsA total of 1200 individuals were followed for an average of 2.6 years (3123 person-years), with 143 all-cause deaths observed among 1031 participants. Bivariate analyses showed that participants who died were more likely to be older, underweight, have shorter daily walking times, live in Bago, and have less social support. Higher social support was significantly associated with lower mortality after adjusting for all covariates (HR = 0.80, 95% CI 0.69–0.94). Specifically, instrumental support, defined as the exchange of practical assistance, such as receiving or providing care during illness, was found to be protectively associated with mortality. When stratified by residential area, significant associations were found only in Bago, a rural area. Among older adults in Myanmar, instrumental support was a more prominent protector against all-cause mortality than emotional support, especially in rural areas.ConclusionsOur findings indicate that social support networks play an important role in the survival of older adults in Myanmar, even under unstable social conditions.

How Mega- and Micro-Influencers Strategically Manage Authenticity: Exploring Influencer Types and Content Differences Based on Social Network Theory

How Mega- and Micro-Influencers Strategically Manage Authenticity: Exploring Influencer Types and Content Differences Based on Social Network Theory

Убывающие города российской Арктики: публичный дискурс воркутинцев об идентичности места и о причинах оттока населения

The aim of the article is to identify the most significant causes of population decline in the regions of the Russian Arctic. The object of this study is the urban communities of Vorkuta, represented in social networks. The concept of the declining city, which has received various interpretations both in foreign and domestic scientific literature, and the concept of place identity have been chosen as the theoretical framework for comprehending the problem. The paper presents theoretical approaches to the definition of a shrinking city and provides a justification for the use of the concept of place identity. Shrinking cities are understood as the cumulative result of economic and demographic factors that cause population decline in the form of natural decline and migration outflow. The methodological basis of the work was the method of qualitative text analysis. The narrative analysis method was chosen as the main method of analyzing qualitative data. At the empirical level, a more detailed analysis of the subjective perception of the urban environment and the reasons for the population outflow from Vorkuta, reflected in the public discourse of the participants of the city’s online community in the VKontakte social network, was carried out. The initial analysis base included community posts and comments for 2022 (a total of 9032 posts and 191733 comments), the target sample was 64 posts and 366 comments to them. Using open and axial coding techniques, the dominant subdiscourses in the perception of place identity and a group of urban development problems that cause the outflow of population from the city were meaningfully identified. Quantitative analysis of the number of comments (under posts) and likes (under comments) made it possible to identify the most significant and persistent problems, which are certainly of increased interest to representatives of municipal and regional authorities.

Integrating a Care Supporter in Diabetes Self-Management Education to Enhance Health Outcomes: A Pilot Study.

PurposeThe purpose of this study was to evaluate the impact of a novel diabetes self-management education (DSME) intervention on self-reported behavioral and clinical outcomes.MethodsAdults over the age of 35 with type 2 diabetes mellitus (T2DM) were recruited to participate in a 3-month study to assess the impact of the Live in Control intervention, a 4-week care supporter-integrated DSME program. Forty-nine participants and their care supporters participated in the program in a community setting. A prospective, repeated measure, pretest and posttest research design was employed with assessments at week 0 (W0; baseline), 4 weeks (W4), and 3 months (W12). The primary measures were diabetes-related self-management behaviors, self-efficacy, autonomy support, social support, distress, and A1C.ResultsPaired t-test analyses revealed significant changes in study variables across different time points. The self-management scores significantly improved from W0 to W4 and from W0 to W12. Self-efficacy significantly increased from W0 to W4 and from W0 to W12. Autonomy support significantly increased from W0 to W12, and social support scores significantly improved over the same period. Findings indicate that participants experienced enhanced support for themselves and from their social networks throughout the study. Diabetes-related distress significantly decreased from W0 to W12. Although decreases in A1C were not significant for the total study sample, those with A1C ≥8 had significant decreases from W0 to W12.ConclusionsA care supporter-integrated DSME intervention can favorably impact diabetes self-care, perceived social support, and A1C, especially for those with higher A1C values, suggesting the positive impact of program participation.

The Debilitating Impact of Transphobia on Health Care Services: The Moderated Mediation Model of Transphobia, Minority Stress, Social Exclusion, and Access to Health Care among People Who Are Transgender.

Drawing on the perspective of minority stress theory, an elaboration of social stress theory, and the Social Exclusion Knowledge Network model, this study's aim is to develop and test the feasibility of a moderated mediation model in the context of Pakistan. This model investigates the roles that transphobia, minority stress, and social exclusion play in the transgender population's access to health care services by the individual's communities in Pakistan. By applying a time-lagged research design and collecting multisource data from public sector hospitals in the capital city of Pakistan, alongside conducting a single-source survey over 30 consecutive working days (N = 206), we explore these relationships in depth. The results reveal that transphobia is negatively related to health care access, with minority stress mediating this negative relationship. Furthermore, social exclusion not only moderates the connection between transphobia and minority stress but also amplifies the indirect association between leader transphobia and health care access via minority stress. This moderated mediation framework underscores the critical impact of transphobia on health care access and highlights the amplifying role of social exclusion. The findings from this study offer invaluable insights for future researchers and practitioners focused on mitigating transphobia's impact on health care access within transgender contexts.

Neural Patterns of Social Pain in the Brain‐Wide Representations Across Social Contexts

AbstractEmpathy can be elicited by physiological pain, as well as in social contexts. Although physiological and different social contexts induce a strong subjective experience of empathy, the general and context‐specific neural representations remain elusive. Here, it is combined fMRI with multivariate pattern analysis (MVPA) to establish neurofunctional models for social pain triggered by observing social exclusion and separation naturistic stimuli. The findings revealed that both social contexts engaged the empathy and social function networks. Notably, the intensity of pain empathy elicited by these two social stimuli does not significantly differentiate the neural representations of social exclusion and separation, suggesting context‐specific neural representations underlying these experiences. Furthermore, this study established a model that traces the progression from physiological pain to social pain empathy. In conclusion, this study revealed the neural pathological foundations and interconnectedness of empathy induced by social and physiological stimuli and provide robust neuromarkers to precisely evaluate empathy across physiological and social domains.

Social Network Analysis in Fashion Research: A Systematic Literature Review

Social Network Analysis (SNA), a research method that focuses on the perspective of networks consisting of interconnected entities (e.g., individuals, organizations, countries, concepts), has been applied widely in multiple disciplines and is particularly suitable for interdisciplinary research, including fashion research, in this digital era. The purpose of this study is to examine the application of SNA in fashion studies published between 2000 and 2023, focusing on the topics, SNA purposes, and research designs. A systematic literature review on eligible articles was conducted using bibliometric analysis and content analysis. Findings indicated that the SNA application in fashion research is in its initial stage, primarily used as an inductive approach with limited network types and relationships. Suggestions for future research for deepening theoretical contribution and broadening topic areas were proposed along with a research process to help fashion scholars apply SNA to its fullest potential and expand the research scopes.

Understanding Interindividual Social Networks in Mixed-Species Bird Flocks

Understanding Interindividual Social Networks in Mixed-Species Bird Flocks

Tracking Advanced Chinese Language Learners’ Oral Proficiency Development and Social Network Construction While Studying Abroad

Tracking Advanced Chinese Language Learners’ Oral Proficiency Development and Social Network Construction While Studying Abroad

The Mediating Role of Trust between Social Networking and Knowledge Sharing among Physicians in North Central Nigeria

Using quantitative research, the study examines the mediating role of trust between social networking and knowledge sharing of physicians in tertiary healthcare institutions in north-central Nigeria. The research methodology is practically a descriptive survey and a cross-sectional study using structured questionnaires. The study population was 2030 physicians at tertiary healthcare institutions in north central Nigeria and the sample size was 333. The sampling technique is the multi-stage sampling. Data were analysed using Smart-PLS 4.0. The results of the study show that social networking strongly influences knowledge sharing (β=0.592, t=16.479, p=0.000), trust is impacted by social networking (β=0.634, t=18.320, p=0.000), and trust significantly affects knowledge sharing. (β=0.304, t=7.224, p=0.000), trust strongly influences the link between social networking and knowledge sharing (β=0.188, t=6.368, p=0.000). With these findings, physicians are more likely to engage in knowledge sharing, leading to better diagnosis, treatment, and patient outcomes. The study recommends that further studies should take into consideration other sectors of the economy, such as the manufacturing, technological, and educational sectors. Again, a longitudinal study and mixed method should be carried out and other regions in the country should be studied to compare the results.

Network dynamics of social influence on e-cigarette use among an ethnically diverse adolescent cohort.

The objective of this study was to examine the mechanisms of social influence driving e-cigarette use in adolescent social networks and differentiate between the effects of exposure to friend behavior and social norms on individual use. Surveys on health behaviors and friendship networks from nine high schools in Southern California (N = 2,245; 48% Hispanic) were collected at three time points from Spring 2021 of grade 9, Fall 2021, and Spring 2022 of grade 10. Stochastic actor-oriented models for the co-evolution of social networks and behavior dynamics tested for friendship network social influences on e-cigarette use. Two mechanisms of social influence were estimated, exposure to friend behavior (e-cigarette use among friends) and pro-e-cigarette social norms (perceived peer approval and use of e-cigarettes), while controlling for social selection, individual covariates, and endogenous network effects. Results from the nine schools were combined in a meta-analysis. Findings revealed social influence effects through exposure to friend e-cigarette use and pro-e-cigarette social norms, which both had significant positive influences on individual e-cigarette initiation over time. Further, Hispanic/Latine individuals and females were more likely to initiate e-cigarette use compared to males and non-Hispanic/Latine students. The importance of these effects should be considered in tobacco prevention initiatives. Designing culturally tailored interventions that target youth social networks and e-cigarette social norms could be effective at curtailing adolescent use. Changing perceptions and social acceptability of e-cigarettes could be one way to slow or prevent the spread of e-cigarette use in adolescent networks. These findings demonstrate the role of social influence on adolescent e-cigarette use through two mechanisms, both friend behavior and social norms. A shift in prevention strategies toward addressing social dynamics and social norms rather than focusing solely on individual level factors may be effective in curtailing use. Changing social perceptions and reducing he social acceptability of e-cigarette use may help slow the spread in adolescent networks.

Mitigating opinion polarization in social networks using adversarial attacks

In recent years, the spread of social networking services (SNS) has made it easier to connect with people who have similar opinions. Accordingly, similar opinions are shared within a group, while the frequency of exposure to different opinions tends to decrease. As a result, the polarization of opinion among groups is more likely to occur. Some studies have been conducted to identify the conditions under which opinion polarization occurs by simulating opinion dynamics, but specific methods for mitigating it have been poorly understood. Recently, it was found that even a few artificial perturbations inspired by the adversarial attack reverse the result in voter models, where a minority opinion becomes dominant through these perturbations. In this study, we conducted numerical simulations to determine whether it is possible to mitigate opinion polarization by adding such perturbations to the network in opinion dynamics models. The results show that opinion polarization can be mitigated by strategically generating perturbations to the weights of network links, and the effect increases as the perturbation strength parameter increases. Moreover, our analysis reveals that the effectiveness of this polarization mitigating method is enhanced in larger networks. Our results propose an effective way to prevent polarization of opinion in social networks.

Health Misinformation in Social Networks: A Survey of Information Technology Approaches

In this paper, we present a comprehensive survey on the pervasive issue of medical misinformation in social networks from the perspective of information technology. The survey aims at providing a systematic review of related research and helping researchers and practitioners navigate through this fast-changing field. Research on misinformation spans multiple disciplines, but technical surveys rarely focus on the medical domain. Existing medical misinformation surveys provide broad insights for various stakeholders but lack a deep dive into computational methods. This survey fills that gap by examining how fact-checking and fake news detection techniques are adapted to the medical field from a computer engineering perspective. Specifically, we first present manual and automatic approaches for fact-checking, along with publicly available fact-checking tools. We then explore fake news detection methods, using content, propagation features, or source features, as well as mitigation approaches for countering the spread of misinformation. We also provide a detailed list of several datasets on health misinformation. While this survey primarily serves researchers and technology experts, it can also provide valuable insights for policymakers working to combat health misinformation. We conclude the survey with a discussion on the open challenges and future research directions in the battle against health misinformation.

Trust in Health Information Sources Among Patients with Systemic Lupus Erythematosus in the Social Networking Era: The TRUMP2-SLE Study.

The growing use of social networking services (SNSs) has impacted how patients with systemic lupus erythematosus (SLE) access health information, potentially influencing their interaction with healthcare providers. This study aimed to examine patients' preferences, actual use, and trust in various health information sources, along with the factors influencing the trust among patients with SLE. A multicenter cross-sectional survey was conducted from June 2020 to August 2021, involving 510 Japanese adults with SLE. Participants reported their preferred and actual sources of health information, including SNSs, and their level of trust in these sources. Modified Poisson regression was used to analyze factors influencing trust, including internet usage and health literacy (HL) (functional, communicative, and critical). Most respondents (98.2%) expressed trust in doctors, while trust in websites/blogs (52.0%) and SNSs (26.8%) was lower. Despite this, the internet was the most frequent initial source of health information (45.3%), encompassing medical institution websites, patient blogs, X (formerly Twitter), and Instagram. Longer internet usage periods were associated with a greater trust in websites/blogs and SNSs. Higher functional HL was correlated with an increased trust in doctors but decreased trust in websites/blogs and SNSs. Higher communicative HL was linked to a greater trust in doctors, websites, and blogs. Although many patients with SLE initially seek health information online, they prefer consulting rheumatologists. Internet usage duration and multidimensional HL influence trust in online sources. Healthcare providers should consider these factors when disseminating health information and engaging with patients.

GAWF: Influence maximization method based on graph attention weight fusion

Influence Maximization (IM) involves identifying a limited number of high-influence nodes within a network to maximize the number of influenced nodes. Although graph neural network-based IM methods have significantly improved generalization capability and propagation effect compared to traditional methods, they face challenges in capturing features of sparse graph networks and difficulties in computing gradient descent, leading to suboptimal diffusion effects and difficult model training. To address these issues, a Graph Attention Weight Fusion-based Influence Maximization method (GAWF) is proposed. First, the GAWF integrates adaptive weight decay optimization using AdamW with graph attention weight fusion. Second, inspired by the Beta-VAE in the CV field, an IM-VAE encoder method tailored for the IM problem is introduced. Finally, extensive comparative analysis experiments are conducted on four real datasets, including Jazz, Cora_ML and Power_Grid, to evaluate three traditional and four learning-based IM algorithms. Experimental results consistently show that the proposed GAWF method achieves a 0.1%[Formula: see text]6% improvement across various datasets, with more significant enhancements on sparser datasets, indicating that GAWF is reasonable and effective. Additionally, the proposed GAWF method holds promising applications in real-world scenarios such as social networks and public opinion analysis.

The Impact of Digital Technologies on Contemporary Education

The position of the student in today's educational process is significantly influenced by the influence of digital technologies, which can have both positive and negative effects. For students to be able to educate themselves effectively and successfully in today's digital society, there is a need to have knowledge of digital literacy, i.e. the ability to work with digital technologies so that they are not dependent on them, but on the contrary make their lives easier or enable them to have a good standard of living thanks to them. The functioning of the student within the teaching process is also significantly influenced by social networks, which often impact their life values and attitudes towards education.

Minimizing spread of misinformation in social networks: a network topology based approach

In the emerging landscape of online social networks (OSNs), the rapid dissemination of misinformation poses a significant challenge to the integrity of information shared among users. Hence, misinformation containment problem in OSNs has drawn significant attention nowadays. In this paper, given a fixed budget, the problem is formulated as minimizing misinformation spread (MMS) problem, which is shown to be an NP-hard problem. With the objective to combat the misinformation in real time, this paper explores a new direction to leverage the network topology to minimize the search space drastically. Based on the community structure of the OSN along with the trust relationship among nodes, a novel linear-time seed node selection algorithm is proposed here that is independent of the positions of the misinformed nodes. Once the set of seed nodes is selected, it can combat any situation of misinformation spread in the OSN, provided the community structure of the network does not change significantly. To the best of our knowledge, this work is the first where trust relationship among users is considered along with the community structure of the network, to control the spread of misinformation in real time. To analyze the diffusion dynamics pertaining to both true information and misinformation, competitive linear threshold model (LTM) with provision for belief switching is followed to provide a more realistic and comprehensive understanding of information diffusion dynamics. Extensive experimental studies on large scale OSNs demonstrate that in comparison to earlier works, the proposed technique obtains 47–74% improvements in performance parameters. Not only that, its parallel implementations also achieve around 51× speedup compared to the earlier algorithms, revealing that the proposed technique is scalable on large scale OSNs for real-time restraint of misinformation.

Group-based HIV awareness initiative for social work students in Malaysia

ABSTRACT This qualitative study evaluates the effectiveness of the “Group-Based HIV Awareness Initiative” in enhancing leadership skills and practical capabilities among social work students in Malaysia. Using a phenomenological approach, the study examined the experiences of 30 students who participated in group-oriented activities, including classroom sessions, site visits, and community outreach. Data collected through semi-structured interviews revealed that the group-based approach boosted students’ leadership abilities, confidence in stakeholder engagement, and understanding of HIV-related issues. The collaborative environment fostered interactive discussions, mutual learning, and the development of supportive social networks, all crucial for students’ personal and professional growth. The findings suggest that the Group-Based HIV Awareness Initiative provides a compelling model for using group work to equip future social workers with the essential skills and confidence needed to address complex social challenges like the HIV epidemic.