Social Network Connections Research Articles

PENGARUH MODAL SOSIAL TERHADAP KAPASITAS MANAJERIAL PETANI JAGUNG DI DESA UMBA KECAMATAN NAPANO KUSAMBI KABUPATEN MUNA BARAT

This study aims to ascertain the social capital and managerial capacity of farmers, as well as to determine the influence of the social model on the managerial capacity of corn farmers in Umba Village, Napano Kusambi Subdistrict, West Muna Regency. The research population comprises all individuals engaged in the cultivation of corn in Umba Village, amounting to a total of 32 individuals. The sample was selected using the census method, resulting in a sample size of 32 respondents for this study. Data were collected through observation, surveys, and structured interviews, with the use of a questionnaire. This study employed a quantitative approach. The variables under investigation are divided into two categories: social capital and managerial capacity among farmers. The data were subjected to two distinct forms of analysis. Initially, a quantitative descriptive analysis was conducted utilising the class interval formula to delineate the prevailing conditions pertaining to social capital and managerial capacity among maize farmers. Subsequently, a multiple linear regression analysis was employed to ascertain the influence of social capital on the managerial capacity of maize farmers. The multiple linear regression analysis is comprised of three tests: the T-test, F-test, and determination test. The findings indicate that the utilization of social capital among corn farmers in Umba Village is classified as favorable. This is evidenced by the presence of a robust level of trust, a commendable application of norms, and a relatively strong network of social connections. The managerial capacity of maize farmers is categorized as good, as evidenced by their effective maize farm planning and organization. However, there are areas for improvement, particularly in the dimensions of maize farming implementation and supervision, which remain in the poor category. Social capital has a significant positive effect on the managerial capacity of maize farmers, amounting to 29.1%, with 70.9% influenced by other factors.

Misinformation Knowledge Synthesis: Using Meta-Analysis to Develop Interdisciplinary Interventions

Due to the disciplinary silo effect of academic research, there is the need to consolidate and synthesize theories for misinformation from multiple disciplines. While the call has been made for the integration necessary to qualify interdisciplinary research, there has been little progress nor substantial efforts made toward this goal. Current challenges include departmental dynamics, the lack of training and resources to support interdisciplinary research, or pressures made by the tenure-track promotion system. Therefore, we propose a method of consolidating top theories and frameworks derived from reviews of scholarly literature from multiple disciplines. This would require a systematic review of systematic reviews encompassing misinformation and its relevant derivations, being mindful that coming to a consensus using terminology remains one of the chief challenges of interdisciplinary work. In addition to identifying the top theories used in research, an overview of the epistemological origins as well as a relevant application could be used as a visual framework to bridge the vast gulfs dividing each school of thought. Another way to discover what disciplines are in collaboration is to visualize the social network connections formed through co-citation analysis. With this method of meta-analysis and subsequent synthesis, more comprehensive understandings will develop, improving both the automated detection methods for misinformation and interventions to mitigate its effects.

A Study on Linguistic Z-Graph and Its Application in Social Networks

This paper presents a comprehensive study of the linguistic Z-graph, which is a novel framework designed to analyze linguistic structures within social networks. By integrating concepts from graph theory and linguistics, the linguistic Z-graph provides a detailed understanding of language dynamics in online communities. This study highlights the practical applications of linguistic Z-graphs in identifying central nodes within social networks, which are crucial for online businesses in market capture and information dissemination. Traditional methods for identifying central nodes rely on direct connections, but social network connections often exhibit uncertainty. This paper focuses on using fuzzy theory, particularly linguistic Z-graphs, to address this uncertainty, offering more detailed insights compared to fuzzy graphs. Our study introduces a new centrality measure using linguistic Z-graphs, enhancing our understanding of social network structures.

Networking people for goal attainment: Psychosocial processes facilitating resilience of care-leavers in South Africa

This article aims to deepen and theorize our understanding of the psychosocial processes young people who are transitioning out of residential care engage in, specifically networking people for goal attainment. A qualitative approach was used to collect data from 31 South African residential care-leavers who were one to seven years out of care, aged 17–26 years. Using a grounded theory method of data analysis this study aims to fill the gap in theoretically informed studies by constructing indigenous theories to explain the care-leaving journey. This paper presents findings on (1) the need to elicit social connections; (2) honing networking skills in eliciting social connections; and (3) the strength in weak ties. The implications for practice point to the necessity of fostering a sense of community among care-leavers prior to their transition since this would eventually promote the development of youth resilience. Thus, to support young people’s reintegration, social workers and child and youth care providers should cooperatively assist them to cultivate and broaden their networks of social connections and work proactively on building social skills for those purposes.

Visualizing the Influence of Social Networks on Recovery: A Mixed-Methods Social Identity Mapping Study with Recovering Adolescents

Background: Social recovery capital (SRC) refers to resources and supports gained through relationships and is vital to adolescent addiction recovery. Much is known about how substance use relates to social networks, but little is known about how other dimensions of social networks influence recovery (e.g., network size/exposure, degree of conflict). Methods: This mixed-methods study sampled 28 adolescents who received treatment for alcohol and other drug (AOD) use disorder (14–19 yrs.: 71% male; M = 17.32 yrs., SD = 1.33; White 82%): 20 were recovery high school (RHS) students. Adolescents completed a social identity map for addiction recovery (SIM-AR), survey, and interview. Qualitative data were content analyzed and the data from the SIM-AR were quantified. Results: On average, participants reported belonging to five distinct groups within their network (Range, 2–9; SD = 1.63; M = 27.89 people, SD = 20.09). Of their social network connections, 51% drank alcohol and 46% used other substances, on average. Larger networks involved more conflict (r = 0.57). Participants were more likely to spend more time with groups that had greater proportions of non-substance-using members. These linkages were stronger for RHS than for non-RHS students. Qualitative analyses revealed that youth reported their recovery-oriented groups as supportive, but some reported that their substance-using friends also supported their recovery. Discussion: SIM-AR was a useful measurement tool, and, through qualitative interviews, we identified unique aspects of youths’ social networks important for further examination. Research with recovering youth should examine SRC-related elements within their networks including relationship quality, belonging, and conflict, alongside the substance use behaviors of network members.

Information and immigrant settlement

We study a randomly-assigned program providing information on U.S. settlement for new Filipino immigrants. The intervention, a 2.5-hour pre-departure training and an accompanying paper handbook, has no effect on employment, settlement, and subjective wellbeing, but leads immigrants to acquire substantially fewer social network connections. We rationalize these findings with a simple model, showing that information and social network links are substitutes under reasonable assumptions. Consistent with the model, the treatment reduces social network links more when costs of acquiring network links are lower. Offsetting reductions in the acquisition of social network connections can hence reduce the effectiveness of information interventions.

Социальный капитал и рынок труда

This article is devoted to the analysis of the role of social capital in the context of the labor market. The paper examines the conceptual apparatus and basic approaches to understanding the essence, features and functions of social capital. The article explores the influence of social capital on the labor market. Particular attention is paid to the study of networks of social connections that form social capital in the labor market in accordance with network theory.

Quantifying intragroup and intergroup connections in non-disjoint groups in social networks: A comprehensive analysis incorporating edges' and nodes' weights

In this paper, we propose generalizations of the EI index to quantify the distinction between intragroup and intergroup connections in social networks. These generalizations enable the analysis of interactions between non-disjoint groups, as large-scale disjoint groups are rarely found in many empirical networks. By expanding social network analysis, these measures facilitate the identification of actors with greater similarities or differences, generating previously untapped knowledge. Furthermore, we propose incorporating both edges' and nodes' weights in assessing the EI index. Intuitively, our approach classifies each network edge as internal or external, depending on the attribute groups that each node linked by the given edge belongs to. Since nodes can belong to more than one attribute group, three methods of classifying a network edge are proposed which depend on the number of shared groups by the pair of nodes. We evaluate the new measures in two distinct network contexts. The first context involves a co-authorship network, where researchers, acting as network actors, are categorized based on their respective areas of expertise in management engineering. The second network consists of trade relations among countries in the Americas, with countries grouped according to their participation in trade agreements. The analysis showed which area of management engineering is more independent by having more internal connections and made it possible to investigate the role of trade agreements in the actual trades made by countries. These proposals provide a more comprehensive and nuanced understanding of network dynamics, allowing for a more precise comprehension of interactions and patterns present in social systems.

Mapping the literature of social network ties in business and management field: A bibliometric study

In recent years, academics have focused increasingly on social network connections across different organisations. Social networking for businesses is a topic that crosses many disciplines, including social sciences, computer science, engineering, management, education, sociology, and psychology, so it's no surprise that definitions, methods, and approaches to social networks are constantly debated. Based on a data set of 3466 publications from the Scopus database, the goal of this study is to map the previous literature on social network ties of organisations to the business and management area. The data set was taken from the Scopus database to investigate the main authors, the number of publications, the most influential journals, the most used keywords and the top productive institutions and countries. The goal of this study is to map the previous literature on the social network ties of organisations to the business and management area. The most influential publications, authors, journals, and keywords are thus identified using four methods of bibliographic analysis, as follows: bibliographic coupling, analysis of co-occurrence of authors' keywords, and analysis of co-authorship (a) countries and (b) authors. According to the study’s findings, the USA is the most prolific country, having over 900 publications in the past five years, followed by China and the UK. The publication trend has increased over the last 5 years in the business and management field and will keep increasing because of the growing interest of researchers and practitioners in the given field. Knowledge-based systems are found to be the top productive journal and Hong Kong Polytechnic University is the most influential institution with the highest number of publications.

A Novel Influence Analysis-Based University Major Similarity Study

In the field of education, investigating the relationships between different majors in universities is an important topic in current educational research. The application of social networks from informatics provides new opportunities and potentials for the field of education. Due to the complexity of social interactions, the social network connections surrounding individuals exert a significant influence on their daily decision-making processes. This paper aims to introduce the social network and influence analysis theories from informatics into the field of education, regarding major as a variable, and comparing and analyzing the influence relationships between majors. An empirical study was conducted, involving the collection of questionnaire data on graduates’ evaluations of various aspects of their university experiences across different majors. The evolution of this model follows the DeGroot opinion dynamics with the inclusion of stubborn nodes. By defining leader majors and general majors based on the data and modeling the questionnaire data as the outcome of a discrete random process, an influence matrix is ultimately generated through the opinion dynamic model. Through this modeling approach, we revealed the underlying influence relationships between different disciplines (majors). These findings provide schools with insights to adjust the directions of discipline cultivation, and offer new perspectives and methods for the study of majors in higher education.

Spatial ecological gradients and non-equilibrium niche construction dynamics in the Levantine Middle-Upper Palaeolithic transition

This article revisits the Middle-Upper Palaeolithic (MP-UP) transition in the Levant (ca. 50–40 kiloanni calibrated before present, hereafter ka), explored here as a key case of spatially and temporally multiscalar niche construction and biocultural adaptation in recent human evolution. New chronometric and palaeogenomic data provide an opportunity to reconsider what actually changed in the MP-UP transition, not only in terms of Neanderthal-anatomically modern human (AMH) population turnover and biological adaptation, but also culturally transmitted technologies and cultural institutions that mediated interrelated changes in mobility and social-network connectivity. High-resolution satellite data on environmental variability, simulation studies of hunter-gatherer demographic fluctuations, and cross-cultural data on hunter-gatherer population density and social organization are evaluated to model baseline constraints and possibilities for long-term biocultural adaptation and niche construction in the region, across the Middle and Late Pleistocene more broadly (ca. 780–12 ka). This exploration adds theoretical support to a view of the MP-UP transition as evolutionary, rather than revolutionary, offering new avenues of inquiry about how shorter-term, local behavioural responses were affected by and—in turn—had ripple effects on geographically more widespread, longer-term trends involving intergenerational demographic dynamics, centennial or millennial-scale population turnovers, and major long-term technological shifts.

Motivating more people to engage in online green behavior: A multi-agent simulation study of Ant Forest

With the rapid development of Internet technology, people's lives are increasingly embedded in online communities. The implementation scenarios of green behavior are extended from offline to online, and individual decision-making is more likely to be influenced by others in the group. However, little is known about the decision-making process of group participation in online green behavior (OLGB). To fill this gap, we took the online environmental project Ant Forest as an example and constructed a multi-agent simulation model incorporating members' gratification types, social network connectivity, and external incentives. Then, we analyzed the decision-making characteristics of groups participating in OLGB. The results showed that: (1) When the ratio of members seeking entertainment, social, and achievement gratifications was 3:3:4, more people chose to accept OLGB and it has the most stable decision status; (2) Under low network connectivity, the group was more inclined to accept OLGB, and the decision status was more stable; (3) When high-intensity financial incentives and medium-intensity non-financial incentives were coupled, the number of people choosing OLGB was the largest, and the decision-making status was the most stable. These findings provide suggestions for policymakers and online green project operators on how to promote more people to engage in OLGB.

Research on the Impact of Heterogeneous Environmental Regulation on the Coordinated Development of China’s Water–Energy–Food System from a Spatial Perspective

Water resources, energy, and food are fundamental resources for ensuring human social development. The coordinated development of these resources contributes to improving the quality of the social environment, promoting harmony between humans and nature, and achieving economic, social, and ecological sustainability. This study utilizes panel data from 30 provinces in China from 2003 to 2020. Using a coupled coordination degree model, the coupling coordination degree of the Water–Energy–Food (WEF) system is calculated, and the spatiotemporal evolution and social network connections of WEF coupling coordination are analyzed. The spatial Durbin model is employed to investigate the spatial spillover effects of heterogeneous environmental regulation on the coordinated development of the WEF system. The mechanism model is used to explore the pathways through which heterogeneous environmental regulation influences the coordinated development of the WEF system. The results of this study demonstrate that the coupling coordination index of China’s provincial-level WEF system has shown a steady upward trend, except for a slight decline in a few years. Over the research period, there has been a significant improvement in regional coupling coordination levels. There are large differences in the level of WEF coupling coordination among different regions, with a distribution pattern of south > north and east > west. Both formal and informal environmental regulations have significant positive effects on the coupling coordination development of the WEF system, as well as significant positive spatial spillover effects. Formal environmental regulation has a stronger impact compared to informal environmental regulation. Foreign direct investment and industrial structural upgrading are important pathways for environmental regulation to promote the coordinated development of the WEF system. Both formal and informal environmental regulations can promote the coordinated development of the WEF system by facilitating foreign direct investment and industrial structural upgrading. This study not only provides important scientific evidence and decision-making references for policymakers in formulating environmental regulation policies but also offers new evidence support for the theory of regional development disparities.

CEO Social Network Connections and Management Forecasts

CEO Social Network Connections and Management Forecasts

Effect of Autonomy and Physical Activity on Self-Rated Health of Older Adults in India: Gendered Analysis Using Structural Equation Models

ABSTRACT The gendered expectations and responsibilities placed upon women can impede their ability to participate in social activities and engage in physical leisure pursuits, ultimately having a negative impact on their health. Our study investigates the mechanisms through which gender influences individuals’ engagement with physical activity during free time and how this relates to self-rated health outcomes among adults aged 45 years or older living in India. Using cross-sectional analysis and Structural Equation Modelling, we analyzed data stratified by gender and age from the Longitudinal Ageing Study of India to examine these conceptual pathways. We found that compared to men, women face greater limitations related to decision-making autonomy, experience more functional impairments, have weaker social networks that provide less support for engaging in leisure-time physical activity, leading them to report lower levels of overall wellbeing than men. Further analyses demonstrated distinct pathways through which each gender’s level of social network connectivity shapes behavior – strong connections increase opportunities for women specifically to engage positively with both peers and physically active pursuits supporting overall wellness goals.

COVID-19 Vaccination Messengers, Communication Channels, and Messages Trusted Among Black Communities in the USA: a Review.

Black and African American adults exhibited higher levels of mistrust and vaccine hesitancy and lower levels of vaccination throughout the COVID-19 pandemic. Vaccination and booster uptake remains disproportionately low among Black adults. We conducted a systematic review of empirical research published between February 2021 and July 2022 from five electronic databases and the grey literature. We screened studies that assessed COVID-19 vaccination information needs and preferences as well as communication strategies among Black adults in the USA. We extracted data, then analyzed and synthesized results narratively. Twenty-two articles were included: 2 interventions, 3 experimental surveys, 7 observational surveys, 8 qualitative inquiries, and 2 mixed methods studies. Studies reported credible and preferred COVID-19 vaccination information sources/messengers, channels, and content. Commonly trusted messengers included personal health care providers, social network connections, and church/faith leaders. Electronic outreach (e.g., email, text messages), community events (e.g., forums, canvassing), and social media were popular. Black communities wanted hopeful, fact-based messages that address racism and mistrust; persuasive messages using collective appeals about protecting others may be more influential in changing behavior. Future communication strategies aiming to increase vaccine confidence and encourage COVID-19 booster vaccination among Black communities should be developed in partnership with community leaders and local health care providers to disseminate trauma-informed messages with transparent facts and collective action appeals across multiple in-person and electronic channels.

1 Social Brain Network Connectivity Relates to Social and Adaptive Outcomes Following Pediatric Traumatic Brain Injury

Objective:Traumatic brain injury (TBI) is a prevalent cause of long-term morbidity in children and adolescents and can lead to persistent difficulties with social and behavioral function. TBI may impact brain structures that support social cognition, social perception, and day-to-day social interactions—termed the social brain network (SBN). We examined differences in links among the SBN and regions of interest from other neural networks thought to support social outcomes, i.e., the default mode network (DMN) and salience network (SN). Furthermore, we examined how differences in co-activation among the SBN and these other key networks were associated with ratings of social and day-to-day adaptive outcomes.Participants and Methods:Participants included children and adolescents with moderate to severe TBI (msTBI; n=11, Mage=11.78, 6 male), complicated-mild TBI (cmTBI; n=12, Mage=12.59, 9 male), and orthopedic injury (OI; n=22, Mage=11.69, 15 male). Participants underwent resting-state functional MRI on a 3Tesla Siemens Prisma scanner. Parents rated their child’s social and adaptive function on the Child Behavior Checklist (CBCL) and Adaptive Behavior Assessment System-Third Edition (ABAS-3). Resting-state connectivity was assessed using the CONN Toolbox, including preprocessing, denoising, and alignment to the participants’ processed T1 MPRAGE sequence followed by seed-to-voxel analysis using a SBN mask and targeted regions of interest within the DMN and SN. Individual-level r-to-z correlations were extracted from resulting clusters of co-activation with the SBN mask and exported into SPSSv28.0 for integration with behavioral data.Results:One-way ANOVAs used to examine group differences in social and adaptive outcome revealed significant group differences in CBCL Social Competence (F=4.49, p=.019) and all composite scores on the ABAS-3 (Fs=3.78 to 5.17, ps=.031 to .010). In each domain, children with msTBI were rated as having elevated difficulties relative to cmTBI or OI, whereas cmTBI and OI groups did not differ. Connectivity also differed significantly between groups, with children with OI demonstrating greater connectivity between the SBN and the anterior cingulate cortex of the SN (t=5.19, p(FDR)<.0001) and posterior cingulate cortex of the DMN (f=4.30, p(FDR)<.001) than children with msTBI. Children with cmTBI also showed greater connectivity between the SBN and left temporal pole of the DMN (t=7.45, p(FDR)<.000001) than children with msTBI. Degree of connectivity between the SBN and posterior cingulate was significantly positively correlated across all domains of adaptive function (rs=.451 to .504, ps=.010 to .003), whereas degree of connectivity between the SBN and left temporal pole was strongly positively related to Social Competence (a=.633, p=.006) and conceptual adaptive skills on the ABAS (A=.437, p=.037).Conclusions:Our findings provide insights into the neural substrates of social and adaptive morbidity after pediatric TBI, particularly msTBI, by linking alterations in connectivity among the SBN, DMN, and SN with measures of social and adaptive outcome. While the posterior cingulate was broadly associated with adaptive outcome, the temporal pole was particularly strongly associated with social competence. This may reflect the diverse functions and high degree of interconnectivity of the posterior cingulate, which contributes to various cognitive and attentional processes, relative to the strong amygdala/limbic connections of the temporal pole.

How convenience and informational tools shape waste separation behavior: A social network approach

Geopolitical risks such as energy crises and local or regional instability aggravate the growing conflict between limited natural resources and increasing consumption, making waste management—using waste as a resource—one of the most urgent agendas in the sustainability domain. Considering individuals' dual attributes (i.e., attitudes and behaviors), we develop an interaction model to investigate waste separation behavior that accounts for convenience and informational tools. Multiagent simulations are performed using data collected from 1056 residents in the top ten Chinese cities by volume of household waste. The results indicate that convenience tools can induce residents to separate waste. In particular, a 160% increase in the adoption rate is observed in response to decreasing (increasing) the distance to collection sites (accessibility to temporary storage facilities for recyclables) from 10 (0) to 0 (10). Publicity and education promote waste separation, as approximately 72% of individuals choose to separate waste when increasing the intensity of popular science propaganda from 0 to 0.2. Interestingly, social interaction appears to have a two-sided effect on waste separation behavior. The adoption rate of such behavior increases with the number of one's connections in sparse social networks, whereas the opposite is found in close social networks. The findings reveal the differentiated impacts of convenience and informational tools on waste minimization and provide new ideas for formulating customized strategies to promote waste separation in sparse (increasing individuals' number of connections) or close (monitoring rumors to achieve a tightly controlled intensity of interaction) social network scenarios.

Efficient Star-based Truss Maintenance on Dynamic Graphs

K-truss is a useful notion of dense subgraphs, which can represent cohesive parts of a graph in a hierarchical way. In practice, in order to enable various truss-based applications to answer queries faster, the edge trussnesses are computed in advance. However, real-world graphs may not always be static and often have edges inserted or removed, leading to costly truss maintenance of recomputing all edge trussnesses. In this paper, we focus on dynamic graphs with star insertions/deletions, where a star insertion can represent a newly joined user with friend connections in social networks or a recently published paper with cited references in citation networks. To tackle such star-based truss maintenance, we propose a new structure of AffBall based on the local structure of an inserted/deleted star motif. With AffBall, we make use of the correlation of inserted edges to compute the trussnesses of the inner edges surrounding the star. Then, we analyze the onion layer of k-truss and conduct truss maintenance for the edges beyond the star, which can be efficiently achieved with a time complexity related to the number of the edges that change the onion layer. Moreover, we extend star-based truss maintenance to handle general updates and single-edge insertions/deletions. Extensive experiments on real-world dynamic graphs verify the effectiveness and efficiency of proposed algorithms against state-of-the-art truss maintenance algorithms.

Returns to Relationships: Social Capital and Household Welfare in India

Sociological scholarship, economic theory, and empirical studies all indicate that interpersonal relationships are valuable productive assets and deserve to be formally incorporated into the study of human development. This paper employs the India Human Development Survey to examine, using OLS and logistic regressions, the impact of different dimensions of social capital on multiple proxies for household welfare. Social capital in the form of memberships in local community organizations and social network connections has a statistically and economically significant association with household consumption expenditures, physical asset ownership, and the probability of a household living in poverty. Households that are members of any formal community organization are expected to have higher monthly per capita consumption expenditures than households without any memberships. Estimates of a similar magnitude are observed when modeling a household’s stock of physical assets, a longer-term indicator of economic welfare. These indicators of social capital are also significantly associated with lower odds of a household living below the poverty line. Organizational memberships and social networks are also associated with considerably higher odds of a household assessing its own economic situation positively. Overall, social capital is a catalyst for increasing household welfare along multiple dimensions, and, therefore, a critical area of focus for economists, sociologists, development practitioners, and policymakers.