Types Of Social Networks Research Articles

Network topological determinants of pathogen spread

How do we best constrain social interactions to decrease transmission of communicable diseases? Indiscriminate suppression is unsustainable long term and presupposes that all interactions carry equal importance. Instead, transmission within a social network has been shown to be determined by its topology. In this paper, we deploy simulations to understand and quantify the impact on disease transmission of a set of topological network features, building a dataset of 9000 interaction graphs using generators of different types of synthetic social networks. Independently of the topology of the network, we maintain constant the total volume of social interactions in our simulations, to show how even with the same social contact some network structures are more or less resilient to the spread. We find a suitable intervention to be specific suppression of unfamiliar and casual interactions that contribute to the network’s global efficiency. This is, pathogen spread is significantly reduced by limiting specific kinds of contact rather than their global number. Our numerical studies might inspire further investigation in connection to public health, as an integrative framework to craft and evaluate social interventions in communicable diseases with different social graphs or as a highlight of network metrics that should be captured in social studies.

Not All Types of Social Networks Are Good: The Dual Effects of Social Networks on Courtesy Stigma

ABSTRACTWhen a firm is accused of serious misconduct, its executives, even those who are nonculpable, are stigmatized by the firm's stakeholders, a phenomenon known ascourtesy stigma. One research stream explores how executives’ social networks mitigate courtesy stigma, with an emphasis on the positive effect of social networks. From the perspective of a social network as an information pipe, we suggest that social networks are a double-edged sword in the context of courtesy stigma because of their distinctiveinsulationandexposuremechanisms. Our proposed hypotheses are supported via event history analysis using data collected from a Chinese sample of listed firms that demonstrated financial misconduct in the period 2007–2016. Our study contributes to the literature on social networks and courtesy stigma by revealing their complex links.

The Power of Networks: A Pre-Requisite to Social Network Analysis

Social network analysis has attained significant attention in recent times. It is a contemporary data driven technique which maps and measures social structures using network and graph theory for people analytics. A pre-requisite to social network analysis is to explore the network genesis and its evolution. Most of the social network studies in the past have focused primarily on the impact of social networks on employees but none of the studies have identified the reasons why do employees bond with specific network members in the first place and what are the different types of workplace social networks. For this reason we wanted to conduct a systematic literature review for identifying the reasons why specific workplace social networks exists, classify different types of workplace networks and highlight network ties which are beneficial for achieving organizational goals. By employing social network theory, this study investigates the intra-organizational networks of corporate business environment. Multiple databases were used to extract relevant papers for this review such as Science Direct, IEEE Xplore, Scopus and Web of Science databases and Directory of Open Access Journals. Some of the major trends identified from the 48 past papers included in this review are: (1) different types of workplace social networks are created based on specific employee interdependency; (2) strong and weak ties both are beneficial for fast information diffusion; (3) negative ties have a stronger impact on organizational outcomes then positive ties. This review will provide a new broader conceptualization of social networks and its influence on employees.

Multi‐agent modeling of hazard–household–infrastructure nexus for equitable resilience assessment

AbstractInfrastructure service disruptions impact households in an affected community disproportionally. To enable integrating social equity considerations in infrastructure resilience assessments, this study created a new computational multi‐agent simulation model, which enables integrated assessment of hazard, infrastructure system, and household elements and their interactions. With a focus on hurricane‐induced power outages, the model consists of three elements: (1) the hazard component simulates exposure of the community to a hurricane with varying intensity levels; (2) the physical infrastructure component simulates the power network and its probabilistic failures and restoration under different hazard scenarios; and (3) the households component captures the dynamic processes related to preparation, information‐seeking, and response actions of households facing hurricane‐induced power outages. We used empirical data from household surveys from three hurricanes (Harvey, Florence, and Michael) in conjunction with theoretical decision‐making models to abstract and simulate the underlying mechanisms affecting the experienced hardship of households when facing power outages. The multi‐agent simulation model was then tested in the context of Harris County, Texas, and verified and validated using empirical results from Hurricane Harvey in 2017. Then, the model was used to examine the effects of different factors—such as forewarning durations, social network types, and restoration and resource allocation strategies—on reducing the societal impacts of service disruptions in an equitable manner. The results show that improving the restoration prioritization strategy to focus on vulnerable populations is an effective approach, especially during high‐intensity events, to enhance equitable resilience. The results show the capability of the proposed computational model for capturing the dynamic and complex interactions in the nexus of households, hazards, and infrastructure systems to better integrate human‐centric aspects in resilience planning and assessment of infrastructure systems in disasters. Hence, the proposed model and its results could provide a new tool for infrastructure managers and operators, as well as for disaster managers, in devising hazard mitigation and response strategies to reduce the societal impacts of power outages in an equitable manner.

The effects of community contact on L1 maintenance: a study of New Zealand Japanese immigrants and sojourners

Abstract This paper explores the effects of social networks on the reported language proficiency of three groups of New Zealand Japanese children. Drawing on a quantitative analysis of data collected from questionnaire-based interviews, this study reveals that children of sojourner families and children of immigrant families of mixed and non-mixed backgrounds, each with their differing levels of reported Japanese proficiency, benefit from different types of social networks. The results found that sojourner networks are important for sojourner children’s Japanese language proficiency. For this group, wider types of contact with the New Zealand Japanese community show little positive effects. These findings contrast with that of Japanese immigrants where community social networks show a diverse range of positive effects on the reported Japanese proficiency of children from mixed and non-mixed family backgrounds. The findings suggest that researchers should give further consideration into the differing effects of social networks on different subgroups within diasporic communities.

Social networks and scientific communication: A Review study

This study aims to emphasize the importance of developing the scientific communication system in line with the successive technological developments. Thus, this theoretical study deals with the concept of scientific communication in regard to various related points. These points are: the elements of communication, the types and forms of scientific communication, the concept of social networks, the emergence and development of social networks, the types of social networks. It also considers the most popular social networking sites, the use of social networks in scientific communication, knowledge of the advantages of using social networks in scientific communication, the obstacles to scientific communication within social networks, ways to overcome these obstacles, the role of free access in developing the process of scientific communication in the digital environment, the role of social networks and the free access usag in supporting scientific communication during the pandemic of Covid-19. Finally, this study found a variety of social networking services that support the process of scientific communication, which must be used, and to overcome any obstacles that may result from the use of these networks.

Transitions in Social Network Types over Time among Older Adults

Objective: Network typology studies have identified heterogeneous types of older adults’ social networks. However, little is known about stability and change in social network types over time. We investigate transitions in social network types among older adults, aged 60 years and older, and factors associated with such transitions. Methods: We used data on 1,305 older adults, participating in 2 waves of a national, longitudinal survey, conducted in 2016–2017 and 2019, in Singapore. Latent transition analysis identified the distinct types of social networks and their transition patterns between the waves. Multinomial logistic regression examined the association of baseline and change in physical, functional, and mental health and baseline sociodemographic characteristics with network transitions into more diverse or less diverse types. Results: We found 5 social network types at both waves, representing the most to the least diverse types – diverse, unmarried and diverse, extended family, immediate family, and restricted. Between waves, about 57% of respondents retained their social network type, whereas 24% transitioned into more diverse types and 19% into less diverse types. Those who were older and less educated and those with worsening functional and mental health were more likely to transition into less diverse types versus remaining in the same type. Discussion: The findings capture the dynamics in social network composition among older adults in the contemporary aging society. We highlight sociodemographic and health disparities contributing to later life social network diversity.

Do subjective or objective cognitive measures better predict social network type among older adults?

ABSTRACT A large literature highlights the link between cognitive function and social networks in later life. Yet there remains uncertainty about the factors driving this relationship. In the present study, we use measures of subjective cognitive decline and clinical cognitive assessments on a sample of older adults to investigate whether the relationship between cognitive function and social networks is driven by psychosocial factors. We found a consistent link between clinical cognitive assessments and social network type, but no association between subjective concerns of cognitive decline and networks. Participants who exhibited signs of clinical cognitive impairment were more likely to have restricted networks (i.e., smaller networks consisting of fewer contacts, more interconnectivity, and less social diversity) compared to their cognitively normal counterparts, regardless of subjective measures of cognitive decline – both from the participant’s perspective and study partner’s perspective. These findings suggest that neither cognitively impaired older adults nor their network members appear to consciously dissolve social ties on the basis of perceived cognitive decline. However, it remains unclear whether the association between clinical cognitive impairment and social network type indicates the protective nature of social networks against cognitive decline or a subconscious process leading to social contraction.

Adolescent Involvement in Cybergossip: Influence on Social Adjustment, Bullying and Cyberbullying.

Gossip is a type of social behavior present in all types of social networks, and cybergossip is an emerging kind of online social behavior which can both promote and hinder relationships between peers. The aim of this study was to explore the relation between involvement in cybergossip and the development of behavior of social adjustment, bullying and cyberbullying (aggression and victimization), based on gender and age. A total of 510 secondary school students (49.4% girls) aged 12 to 17 years old (M = 14.01; SD = 1.38) were surveyed by self-report. Questionnaires validated with adolescents were used to measure bullying, social adjustment and cyberbullying. The results showed that a high prevalence of involvement in cybergossip was associated with bullying and cyberbullying behavior (aggression and victimization), with girls showing the greatest involvement in cybergossip. The discussion of the results focuses on the gender difference, as well as the importance of the need for training in the proper use of digital devices for social education and socialization.

Social networking sites in cultivating the reading habits of secondary school learners in Bulawayo, Zimbabwe

Technological developments, especially social networks, have brought about changes in social and educational conditions. These technological developments also apply to the reading habits of secondary school learners. The general purpose of this study is to examine the adoption of social networking sites in cultivating the reading habits of secondary school learners in Bulawayo Metropolitan province in Zimbabwe. The study employed a multiple-case study with 14 focus groups, consisting of 210 learners. Data was collected through interviews with eight school librarians and analysed thematically. The key findings revealed that learners are using different types of social networks, including WhatsApp, Facebook, Watt pad, Pinterest, and YouTube to connect with friends and family and keep abreast with the latest events. The study further revealed the positive effects of using social networking sites, such as the availability of up-to-date reading materials that can be easily shared amongst learners. However, these sites were not fully used by learners for reading. The findings also showed that some learners spend approximately five hours on social media for entertainment purposes and this has a negative effect on their reading habits. The study then concluded that learners are using social networks, but mainly for social engagement purposes. If guided, they could use social networking sites to cultivate and enhance their reading habits.

Learning Holistic Interactions in LBSNs with High-order, Dynamic, and Multi-role Contexts

Location-based social networks (LBSNs) have emerged over the past few years. Their exponential network effects depend on the fact that each user can share her daily digital footprints with different communities, in different places, and at different times (for example in the form of check-in activities). Unlike other types of social networks, activities in an LBSN can potentially be performed by several users in a collaborative way. Existing studies of representation learning for LBSNs often consider them as regular graphs and ignore these high-order, dynamic, and multi-role contexts, since their holistic interactions are quite difficult to capture. In this paper, we propose a model in which these holistic interactions can be learned and transferred into node embeddings derived from a hypergraph representation and a persona decomposition process. More specifically, the model learns from friendship edges, check-in hyperedges, and node personas at the same time, and devises multiple presentations for each user that reflects their multiple roles in a social context. The embedding learning process also exploits useful patterns such as user co-location and sequential effects through a carefully designed point-of-interest splitting step. Extensive experiments on real and synthetic datasets show that our model outperforms alternative state-of-the-art embedding methods on friendship and location prediction tasks.

Multidimensional Social Network Types and Their Correlates in Older Americans

Background and ObjectivesSocial support networks of older adults have been linked to their health and well-being; however, findings regarding the effects of specific network characteristics have been mixed. Additionally, due to demographic shifts increasing numbers of older adults live outside of traditional family structures. Previous studies have not systematically examined the resulting complexity and heterogeneity of older adults’ social networks. Our objectives were to examine this complexity and heterogeneity by developing a multidimensional typology of social networks that simultaneously considers multiple structural and functional network characteristics, and to examine differences in network type membership by sociodemographic characteristics, health characteristics, and birth cohort.Research Design and MethodsParticipants included 5,192 adults aged 57–85 years in the National Social Life, Health, and Aging Project at rounds 1 (2005–2006) and 3 (2015–2016). Data were collected on social relationships including network size, diversity, frequency of contact, and perceived support and strain in relationships. We used latent class analysis to derive the network typology and multinomial logistic regression to examine differences in network type membership by sociodemographic characteristics, health characteristics, and birth cohort.ResultsOlder adults were classified into 5 distinct social network types: (i) large, with strain; (ii) large, without strain; (iii) small, diverse, low contact; (iv) small, restricted, high contact; and (v) medium size and support. Membership in these network types varied by age, gender, marital status, race/ethnicity, education, mental health, and birth cohort.Discussion and ImplicationsNetwork typologies can elucidate the varied interpersonal environments of older adults and identify individuals who lack social connectedness on multiple network dimensions and are therefore at a higher risk of social isolation.

Risk factors of loneliness across the life span

Although loneliness is typically associated with adolescence and old age, research has revealed that it is prevalent across the life span. The present study contributes to the loneliness literature by investigating a broad range of risk factors in a Dutch sample ( N = 52,341) ranging from late adolescence to old age using a cross-sectional survey administered by the regional public health services in the province of Limburg in the Netherlands. Risk factors associated with higher levels of self-reported loneliness across the life span were being male, lower education levels, inadequacy of financial resources, mental health, informal caregiving that is experienced as burdensome, and limited social contact or network type. In addition, in early adulthood, having a non-western migration background and having a physical disability were associated with higher levels of loneliness, whereas living alone, having a non-western migration background, and not having a paid job were risk factors of loneliness in middle adulthood. In late adulthood, living alone and having a physical disability were associated with loneliness. The present study demonstrates that different stages of life are associated with different vulnerability factors of loneliness. Hence, the prevention of loneliness might require different interventions in different age groups.

Loneliness as a gender-specific predictor of physical and mental health-related quality of life in older adults

PurposeHealth-related quality of life (HRQOL) in older persons is influenced by physical and mental health, as well as by their social contacts and social support. Older women and men have disparate types of social networks; they each value social ties differently and experience loneliness in unique and personal ways. The aim of this study is, therefore, to determine the longitudinal association between loneliness and social isolation with HRQOL in older people—separated by gender.MethodsData stem from the third and fourth follow-up of the ESTHER study—a population-based cohort study of the older population in Germany. A sample of 2171 older women and men (mean age: 69.3 years, range 57–84 years) were included in this study; HRQOL was assessed by using the Short Form-12 questionnaire (SF-12). Data on physical and mental health, loneliness, and social networks were examined in the course of comprehensive home visits by trained study doctors. Gender-specific linear regression analyses were performed to predict physical quality of life (measured by the PCS, physical component score of the SF-12) and mental quality of life (measured by the MCS, mental component score) after three years, adjusted by socioeconomic variables as well as physical, mental, and social well-being.ResultsAt baseline, PCS was 41.3 (SD: 10.0) in women and 42.2 (SD: 9.6) in men (p = .04). MCS was 47.0 (SD: 10.2) in women and 49.6 (SD: 8.6) in men (p < .001). In both genders, PCS and MCS were lower three years later. Loneliness at t0 was negatively associated with both PCS and MCS after three years (t1) among women, and with MCS but not PCS after three years among men. In both genders, the strongest predictor of PCS after three years was PCS at t0 (p < .001), while the strongest predictors of MCS after three years were MCS and PCS at t0.ConclusionHRQOL in elderly women and men is predicted by different biopsychosocial factors. Loneliness predicts decreased MCS after three years in both genders, but decreased PCS after three years only in women. Thus, a greater impact of loneliness on the health of older women can be surmised and should therefore be considered in the context of their medical care.

Social network typology and health among parents of children with developmental disabilities: Results from a national study of midlife adults

ObjectiveThere is increasing interest in the role of contextual factors in promoting well-being among parents of children with developmental disabilities. This study aimed to examine whether social network types moderate the impacts of having a child with a developmental disability on parents' health. MethodsUsing cross-sectional data from the Midlife in the United States survey (MIDUS 2 and Refresher cohorts), we analyzed a sample of 363 parents of children with developmental disabilities and 4,919 parents of children without developmental disabilities. K-means cluster analysis was implemented to identify a social network typology. Modified Poisson and negative binomial regression models estimated the effect of having a child with a developmental disability and the typology on parents' physical health (self-rated health, number of chronic conditions) and mental health (self-rated mental health, major depression). ResultsThe cluster analysis revealed two social network types. Parents of children with developmental disabilities were more likely to have “restricted/unsupported” networks, whereas parents in the comparison group were more likely to have “diverse/supported” networks. Social support was more important for differentiating the network types of parents of children with developmental disabilities, while social integration was more salient for the comparison group. Parents of children with developmental disabilities fared worse on all outcomes relative to parents of children without disabilities. However, the typology had a compensatory psychological effect; the diverse/supported network type conferred greater mental health benefits to parents of children with developmental disabilities than to those in the comparison group. The diverse/supported network type was also associated with better physical health, but the associations did not differ between the two parent groups. ConclusionsThe results of this study emphasize the importance of social determinants of well-being for those with exceptional parenting responsibilities. Strengthening social networks may have a particularly positive impact on such parents' mental health.

EMPLOYEE MOBILITY AND INNOVATION: THE ROLE OF TURNOVER RATE AND NETWORK CENTRALITY

Innovation is crucial to a company’s competitive advantage and employees play an important role in generating innovation within a company. Based on social capital theory, we proposed a new type of social network: the employee mobility network, and explored the impact of employee mobility on innovation. Specifically, we examined the role of both employee turnover rate, and an organisation’s centrality in the employee mobility network in predicting innovation. We collected data from World Intellectual Property Organisation (WIPO), Talentale, and Forbes Global 2000 to test our hypotheses. The results showed that turnover rate had a significantly inverted-U curve relationship with innovation, and both degree and closeness centralities of an organisation in the employee mobility network had a significant positive relationship with innovation. Based on the results, we suggest that companies should find a balanced value for their turnover rate to get the highest return in innovation. Also, we suggest that companies should improve social influence in employee mobility networks in order to attract talent and increase company innovation.

Social networks and internal migration in China: A spatial autoregressive model

AbstractIndividual decisions such as migration can be influenced by different types of social networks. This paper examines strong and weak network effects on internal migration in China by distinguishing between first‐time migrants and experienced migrants. Strong networks are constructed by household members, while weak networks are determined by the village in which the individual resides. By employing spatial econometrics tools, we show that strong networks have a significant positive effect on the first‐time migration decision, while weak network effects vary across home provinces and are significant and positive only for some provinces. We also classify the sample to explore the network effects within the household and find that the effects are larger among siblings, especially among siblings of the same gender. In contrast, strong networks have a smaller impact, and weak networks appear to encourage migration after people have migration experience. Similar findings also apply to the choice of destination, months worked away from home, and migration earnings.

Social Network Types and Depressive Symptoms among Older Korean Men and Women.

This study explores the social network types of older Korean men and women, and the relationship of those networks to depressive symptoms. A population of 4608 older adults who participated in the Living Profiles of Older People Survey (LPOPS) were included in the study. Seven criterion variables—marital status, living arrangements, frequency of contact with children, close friends, and close relatives, participation in social activities, and total network size—were included in a K-means cluster analysis. Multivariable logistic regression analysis of the impact of social network type on depressive symptoms was conducted. We identified two “diverse type” social networks (diverse-married and diverse-unmarried) in women, and one diverse type and one “social-activity-focused type” network in men. Family focused type and two “restricted type” social networks (restricted-couple-focused, and restricted-unmarried) were identified in both men and women. The restricted-unmarried and restricted-couple-focused networks were associated with more depressive symptoms in both men and women. However, the family focused type was associated with more depressive symptoms only in women. The results indicated that social network types, and their impact on depressive symptoms, differ by gender. There is a need for further research on gender differences in the social network types of older adults across diverse cultures.

Social-spatial network structures and community ties of egocentric sex and confidant networks: A Chicago case study

Exploring how sexual and confidant networks overlap spatially and socially could facilitate a better understanding of sexually transmitted infection risk, as well as help identify areas for interventions. This study aims to examine how a sexual and peer-affiliate network is impacted or shaped by interconnected social relationships and spatial patterns. We used data collected from a sample of 618 young black men who have sex with men (YBMSM) and transgender women in Chicago (2013–2014) that includes partner and confidant links, geolocations, and pre-exposure prophylaxis (PrEP) awareness. We spatialize different types of social networks and examine joint social-spatial community ties to both identify and differentiate social-spatial behavioral patterns. We explore the spatial structures of the social network by comparing ego-alter network residence patterns, visualizing ego-alter community ties in aggregate, and grouping different types of dyad relationships based on their spatial structure. Findings showed overlapping social and sexual networks. Egos with partners residing in more resourced communities furthest away, with wider alter-ego power differentials, also tended to be at greatest risk. Identifying the social-spatial structures of community ties is critical to enhance our understanding of the spatial context of social relationships, and further distill risk heterogeneity in vulnerable populations within an equitable health framework.

The social organization of the commons and public policy design: A social network approach

Economics has recognized the importance of social networks for overcoming social dilemmas but has not yet developed a framework that allows to quantify its importance and define public policies in the presence of social interactions. This paper makes a first step in this direction by analyzing the influence that social networks and the state of a public good or common property resource have on compliance with social norms. The analysis signposts the maximal and minimal influence different types of social networks have for supporting a stable steady-state with full cooperation, thereby allowing policymakers to compare the effectiveness of legal (e.g., fines or subsidies) and informal (e.g., network-oriented) enforcement policies. The study also shows that social networks allow reducing the stringency of enforcement policies. Yet, cooperation is unlikely to prevail if the agents do not perceive the social dilemma as severe. We find that stable steady states where compliers and defectors coexist (partial cooperation) are supported and their stability depends on the type of functions representing social pressure and sanctioning costs. The analytical framework is employed for an empirical study of an aquifer in Spain. It reveals that subsidizing the compliers’ costs of social pressure may impede a stable steady state based on partial cooperation with a large area of attraction.