Types Of Social Networks Research Articles

Polarization and consensus by opposing external sources

We introduce a socially motivated extension of the voter model in which individual voters are also influenced by two opposing, fixed-opinion news sources. These sources forestall consensus and instead drive the population to a politically polarized state, with roughly half the population in each opinion state. Two types of social networks for the voters are studied: (a) the complete graph of N voters and, more realistically, (b) the two-clique graph with N voters in each clique. For the complete graph, many dynamical properties are soluble within an annealed-link approximation, in which a link between a news source and a voter is replaced by an average link density. In this approximation, we show that the average consensus time grows as , with . Here p is the probability that a voter consults a news source rather than a neighboring voter, and is the link density between a news source and voters, so that can be greater than 1. The polarization time, namely, the time to reach a politically polarized state from an initial strong majority state, is typically much less than the consensus time. For voters on the two-clique graph, either reducing the density of interclique links or enhancing the influence of news sources again promotes polarization.

Functional and structural social support, substance use and sexual orientation from a nationally representative sample of US adults

Sexual minority (SM) populations experience higher rates of substance use disorder (SUD) associated with increased sexual orientation-related stress. Social support may moderate the impact of stress on SUD among SM adults. This study assessed associations between social support and DSM-5 SUD by sex and sexual minority identity. Cross-sectional study using data from the 2012-13 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC-III). A nationally representative cross-sectional sample of adults (n=36 309) in the United States. SUD were defined based on the DSM-5 criteria for alcohol use (AUD), tobacco use (TUD) and drug use (DUD) disorders. Structural social support was measured as the type and frequency of kin and non-kin contact, and functional social support was measured by the Social Provision Scale. SM adults had higher odds of all SUD compared to heterosexual adults [AUD=1.535, 95% confidence interval (CI)=1.782-1.844; TUD=1.512, 95% CI=1.234-1.854; DUD=1.520, 95% CI=1.139-2.028]; SM women experienced the highest proportion of all SUD (AUD=27.1%, TUD=29.1%, DUD=10.9%). Type of social support was differentially associated with SUD by sex and sexual identity status. Higher social provision was associated with lower rates of AUD [adjusted odds ratio (aOR)=0.771, 95% CI=0.705-0.844], TUD (aOR=0.747, 95% CI=0.694-0.804] and DUD (aOR=0.558, 95% CI=0.490-0.636). Marriage was associated with lower SUD among heterosexual men (AUD, aOR=0.500, 95% CI=0.432-0.579; TUD, aOR=0.603, 95% CI=0.521-0.699; DUD, aOR=0.504, 95% CI=0.369-0.689) and women (AUD, aOR=0.637, 95% CI=0.529-0.767; TUD=0.0.584, 95% CI=0.507-0.671; DUD, aOR=0.515, 95% CI=0.372-0.712). Compared to heterosexual adults, SM women with at least one child under the age of 18years had higher odds of TUD (aOR=1.990, 95% CI=1.325-2.988). SM-related discrimination was not associated with SUD among some SM subgroups, but discrimination among male heterosexually identifying individuals reporting same-sex attraction or behavior was associated AUD (aOR=4.608, 95% CI=1.615-13.14). In the United States there are significant associations between functional support (quality or provision of support) and structural support (type and frequency of social networks) and substance use disorder (SUD) which differ by sex and sexual identity status.

Network type, transition patterns and well-being among older Europeans.

Using SHARE data, this study was based on an earlier analysis that derived social network types among adults aged 65 and over in Europe. The current effort investigated the transitions that occurred across these network types after 4years (N = 13,767). Four general network transition patterns were identified according to network type (close-family networks and other networks) and whether a network transition occurred. The associations between network type, network transitions and well-being (depression and life satisfaction) were examined. We regressed depressive symptoms and a life satisfaction measure on the network transition patterns, controlling for socio-demographic background, health and country. The results revealed that a majority of older Europeans experienced a range of network transition, while close-family-based networks tended to prevail over time. Moreover, respondents who remained in or transitioned to close-family networks had fewer depressive symptoms and better life satisfaction than those in other network types. The study, thus, underscores the varied effects of network types and network changes on emotional well-being in late life. It also demonstrates that beneficial changes can be made in one's social network in old age, especially with regard to greater family closeness.

TYPES OF SOCIAL NETWORKS AND THEIR ASSOCIATION WITH MOBILITY AND DISABILITY IN LATE LIFE

Social networks are critical in maintaining late-life functional health, but, previous studies have focused on isolated dimensions of social networks. We examined whether network types, representing multiple interrelated network characteristics, are associated with mobility and disability among older adults in America. Data are from the National Social Life, Health, and Aging Project, a nationally representative study of 3,005 adults aged 57-85 years at baseline (2005-2006). In a previous analysis, five social network types were derived at baseline, based on nine observed network characteristics. Functional outcomes were examined during two follow-up waves in 2010-2011 and 2015-2016. Mobility-related function was assessed as the time (in seconds) to complete a 6-meter walk. Disability was defined as experiencing any difficulty in performing one of six activities of daily living (ADLs). We estimated the effect of network types on risk of ADL disability onset using logistic regression, and on mobility using generalized linear mixed models. Social network type was associated with mobility over time, such that older adults in the “restricted” network had significantly slower walking times than those in the “diverse” network. There was no association between network types and risk of disability onset in the primary analysis. However, sensitivity analyses showed a protective effect of the “partner-centered” network on a 5-year, but not a 10-year, risk of disability onset. Network types can elucidate older adults’ varied interpersonal and caregiving networks, and identify adults at risk of being socially isolated. However, the utility of network types in predicting late-life functional health may be limited.

Email Based Institutional Network Analysis: Applications and Risks

Social Network Analysis can be applied to describe the patterns of communication within an organisation. We explore how extending standard methods, by accounting for the direction and volume of emails, can reveal information regarding the roles of individual members. We propose an approach that models certain operational aspects of the organization, based on directional and weighted indicators. The approach is transferable to other types of social network with asymmetrical connections among its members. However, its applicability is limited by privacy concerns, the existence of multiple alternative communication channels that evolve over time, the difficulty of establishing clear links between organisational structure and efficiency and, most importantly, the challenge of setting up a system that measures the impact of communication behavior without influencing the communication behaviour itself.

HEALTH INFORMATION’S IMPACT ON OSTEOPOROSIS SELF-MANAGEMENT BEHAVIORS IN OLDER WHITE AND ASIAN WOMEN

Little is known about how health information obtained from different types of social networks affect health behaviors. This study aimed to explore the effect of health information on osteoporosis management behaviors among White and Asian women from a social capital (SC) perspective using a variety of SC measures (e.g. bonding: family, friends, coworkers; bridging: churches, clubs; linking: health providers). Semi-structured interviews were conducted with 10 White and 10 Asian women aged 50 and over in 2016. Through content analysis, we found that SC possession was different between older White and Asian women, and SC utilization to obtain health information corresponded with their possession of SC. Comparing to other diseases, health information relevant to osteoporosis was less frequently communicated. Health information from different types of SC interactively shaped participants’ behaviors. The findings suggest that culturally appropriate health interventions might improve older White and Asian women’s self-management behaviors of osteoporosis.

ASIAN OLDER ADULTS’ ONLINE AND OFFLINE HEALTH INFORMATION PREFERENCES AND BEHAVIORS

Older adults living in Asia or of Asian origin have unique preferences for information that require special attention. This symposium focuses on the health information preferences and behaviors of Asian older adults. Song et al. investigated the relationship between Internet use and perceived loneliness among Older Chinese using from survey data collected in the 2015 wave of the China Health and Retirement Longitudinal Study (CHARLS), a national study involving 12,400 households in Mainland China. Multiple regression results suggest that older Chinese Internet users perceived significantly less loneliness compared with their age peers who were non-Internet users. Zhang et al. investigated the role of information and communication technologies in supporting antiretroviral therapy (ART)-related knowledge seeking among older Chinese with HIV. Their cross-sectional survey data were collected from 2012 to 2013 in Guangxi, China. The results suggest that less than 5% of the participants sought HIV-related information via computers. Patients less knowledgeable about ART were more likely than those more knowledgeable to consult medical professionals about the disease via cell phones. Shiroma et al. report findings of a systematic literature review conducted in spring 2019 that examined Asian ethnic minority older adults’ preferences for end-of-Life (EOL) information seeking and decision making. The results suggest Asian ethnic minority older adults are understudied in the literature on EOL information and decision making, especially in terms of their unique cultural contexts. Du et al. examined how health information obtained from different types of social networks affect osteoporosis self-management behaviors among older White and Asian women.

A Novel Approach for Detecting Relationships in Social Networks Using Cellular Automata Based Graph Coloring

All the social networks can be modeled as a graph, where each roles as vertex and each relationroles as an edge. The graph can be show as G = [V;E], where V is the set of vertices and E is theset of edges. All social networks can be segmented to K groups, where there are members in eachgroup with same features. In each group each person knows other individuals and is in touch withthem. In this study, the main goal is introducing a new approach for detecting these groups andminimizing the number of these groups using a cellular automat algorithm. There are two types ofsocial networks, containing simulated social network and real social network. The results show thatthe introduced method has a great potential to signi cantly reduce the number of colors assignedand running time of the program.

Sociodemographic and substance use characteristics associated with typologies and composition of social support networks among youth experiencing homelessness in Los Angeles, USA

Youth experiencing homelessness are a vulnerable population with increased behavioural health risks. Social networks are a consistent correlate of youths' substance use behaviours. However, less is known about the reciprocal relationships among these constructs. This study classified youth experiencing homelessness according to their social support network type (e.g. instrumental, emotional, service) and composition (e.g. family, peers, service staff) and linked their membership in these social network classes to sociodemographic and substance use characteristics. Four waves of cross-sectional data were collected between October 2011 and June 2013 from youth experiencing homelessness, ages 14-29, at three drop-in centres in Los Angeles, CA (N=1,046). This study employed latent class analysis to identify subgroups of youth experiencing homelessness according to the type and composition of their social support networks. Multinomial logistic regression analyses were then conducted to identify the sociodemographic and substance use characteristics associated with social support network class membership. Five latent classes of youths' social support networks were identified: (a) high staff emotional and service support; (b) high home-based peer and family emotional, service and instrumental support; (c) moderate street- and home-based peer emotional support; (d) low or no support and (e) high home-based peer and family emotional and instrumental support. Multinomial logistic regression models indicated that race/ethnicity, gender, sexual orientation, literal homelessness, former foster care experience, depression, heroin and marijuana use were significant correlates of social support network class membership. Results indicate distinct classes of social support networks among youth experiencing homelessness, with certain sociodemographic and substance use characteristics implicated in youths' social networks.

The impact of trust and information networks on teachers’ job satisfaction

PurposeThe purpose of this paper is to provide an understanding of how two types of informal social networks – those related to instrumental purposes of information sharing and those related to expressive purposes of interpersonal trust – impact teachers’ job satisfaction.Design/methodology/approachThis paper uses social network analysis (SNA) degree and betweenness measures and job satisfaction scales from the Job Diagnostic Survey to collect longitudinal data from employees in one of the vocational schools in Saint Petersburg, Russia via structured interviews. Data on a total of 354 ties were analysed for 40 ego networks in 2018 and 33 ego networks in 2019.FindingsThe obtained results partially confirm the positive effect of teachers’ position in instrumental and expressive networks on job satisfaction. More centrally positioned teachers were more satisfied with peers and colleagues. They feel more secure in regard to job security, given the unique and multi-faceted knowledge they possess. Structural diversity of the network, as well as the category of a teacher (core subject or vocational subject), are found to explain the uneven evolvement of network size. The authors argue that the decrease in network size can be treated as a positive externality of changes in an informal network. The variation in teachers’ experience seems to explain both job satisfaction and network composition.Research limitations/implicationsThe paper is based on a case study and its findings are limited to one particular organization. Nonetheless, the proposed SNA application is of potential value for similar organizations in terms of enhancing their capacity to benefit from networks. This study uses a structured interview to collect network data and job satisfaction data. However, overt observation or secondary data on written communication (e-mail, reports) may provide additional insights about the sought impact in the context of school.Practical implicationsBoth teachers and managers benefit from the results of the paper. Educational policymakers and schools’ administration can exploit the bird’s eye view on an organization that SNA provides. By identifying focal employees and their attitude towards school, one receives an opportunity to prevent structural holes, organizational conflicts and uneven distribution of workload. Novice teachers can nurture their well-being by enhancing personal and instrumental social networks at the start of their careers. Experienced teachers benefit from social cooperation as it fosters the exchange of experience and skills, which is vital for job retention.Originality/valueThis research extends the understanding of the role of different kinds of social networks in teachers’ job satisfaction. The paper provides new insights into the SNA application to vocational schools and developing economies. Authors address teachers’ informal networks both from ego and complete network analyses to provide the holistic, yet detailed view. The use of longitudinal data advances the understanding of how personal and group networks develop over time.

Modeling social influence using sequential stated adaptation experiments: A study of city trip itinerary choice

This paper introduces a model that captures the effect of social influence on decision makers’ choice behavior in the context of sequential stated adaptation experiments, in which a decision maker first chooses the alternative he/she personally likes best from an experimentally varied choice set and then, after being informed about the choice of a certain social network member, chooses again from the same choice set. Social influence represents the effect of the choices of one or more social network members in the same choice situation on the choice behavior of a decision maker. It is assumed to depend on a decision maker’s socio-demographics and personality traits, and the strength of the relationship with the social network member. The concept of choice consistency is introduced to reflect a respondent’s tendency to stick with his/her original choice in completing the sequential stated choice tasks. By accounting for this effect, a less biased estimate of social influence is obtained. Similarly, the model accounts for the case that the first choice of the respondent and the social network member’s choice are identical by introducing a correction factor to further reduce the bias in the estimated social influence. To access the validity of the model, the choice of city trip itinerary was chosen as an example. Decision makers’ personality traits and their relationship with the social network member were treated as latent variables. Therefore, first, exploratory and confirmatory factor analysis was carried out to investigate the reliability and validity of the constructed scales. Then a sequential estimation approach was employed to avoid confounding between decision makers’ preferences towards attributes and the effects of social influence and choice consistency. In the first stage, the taste parameters were estimated and then in the second stage the composition of social influence effect and choice consistency effect were estimated simultaneously. Results show that the model reproduced the observed data well. Social influence has a modest but significant effect on decision makers’ choice behavior; decision makers’ socio-demographics and personality traits, social network type as well as the relationship with social network members all have significant effects on social influence. The effect of choice consistency is also significant.

Redes sociales: herramientas alternativas para el desarrollo de competencias ciudadanas

Este estudio tuvo como finalidad analizar las redes sociales como herramientas alternativas para el desarrollo de competencias ciudadanas y describir la tipología de éstas. Teóricamente se sustentó en planteamientos sobre competencias ciudadanas de Chaux, Lleras y Velázquez (2012) y conceptualización sobre redes sociales de Royero (2007, citado por Indova, 2011), Boyd y Ellison (2007), Ellison y Boyd (2013), Santamaría (2008). El contexto paradigmático fue positivista cuantitativo, la investigación descriptiva, con diseño no experimental de campo. La muestra poblacional fue deveintiún (21) estudiantes de básica secundaria de la Institución Educativa Distrital Beatriz Gutiérrez de Vives. Se aplicó un censo y una técnica de observación por encuesta mediante un instrumento de escalas con alternativas de respuesta siempre, casi siempre, casi nunca y nunca, validado por cinco expertos y con un coeficiente Alfa de Cronbach de 0.86. Se evidencia que los tipos de redes sociales constituyen una fortaleza para las escuelas, al posibilitar el implemento de acciones orientadas a las competencias ciudadanas.

Social networks and gender in organized youth sports

Sports are social, and the sociability of sports (e.g. individual experiences, group cohesion or generalised social trust) and its consequences (e.g. enjoyment, inclusion, or social capital) depends on the social networks in sports teams. In this study we investigate various types of social networks in sports—strong and weak—for boys and girls. We look at the number of social relations in each team (average degree), how centralised and hierarchical teams are, and how each team clusters and consists of subgroups. We hypothesise that: (i) Boys’ and girls’ teams differ in number of social relations, (ii) Boys’ social networks are more hierarchical than girls’ networks, and (iii) Girls’ teams are more clustered than boys’ teams. Network data from 387 adolescent athletes on 30 sports teams in football, handball, cross-country skiing and biathlon were collected with an electronic survey-questionnaire. The results reveal large differences in network structures between teams. We find that the total number of social relations is higher in girls’ teams, that there are small gender differences with respect to networks' hierarchies, and that girls’ networks cluster more than boys’ networks.

Online dynamic group-buying community analysis based on high frequency time series simulation

Group-buying often fails even when there are satisfactory quantities as not enough consumers join in the required time, which can waste seller, purchaser, and platform operator time resources; therefore, the group buying features require further research. Over a 3 weeks period, around 700 million click-stream records from 1,061,770 users from a stable and continuous time series were allocated to groups of 5 min frequency, and a hybrid neural network model developed to simulate group-buying behavior in four experiments, from which it was found that adding to the cart and adding as a favorite were significant group-buying behavior features, and shopping depth was the main demographic feature, but age was not. Compared with previous ambiguous online consumer feature conclusions on gender, the results revealed that the commodity feature was the main determinant for gender feature significance. The college student feature was found to be a pseudo feature, and should connect with other fixed effects such as low income or education level. This paper is the first to construct an online dynamic group-buying community, which is a new type of social network and could provide a new perspective for social commerce research. A big data neural network-based method for examining group-buying community behavior over time is proposed that can offer novel insights to online vendors for the development of targeted marketing campaigns.

The Influence of Social Networks and Norms on Breastfeeding in African American and Caucasian Mothers: A Qualitative Study.

Background: Social networks and subjective norms (individuals' perceptions of what other people think) can be influential in decision-making. Although there are data about the importance of support in initiation and duration of breastfeeding, no studies have explored the influence of women's social networks and the norms within those networks on breastfeeding. Research Aim: To investigate, through qualitative methods, the influence of mothers' social networks and subjective norms, both within and outside of her network, with regard to breastfeeding practices. Materials and Methods: Twenty-eight mothers participated in focus groups or individual interviews. Probing questions concerning breastfeeding intent, initiation, continuation, and support with regard to social networks and subjective norms were asked. Themes were developed in an iterative manner from coded data. Matrix coding queries assessed patterns in the data and compared quotes based on the respondents' race and social network type. Results: General themes that emerged were the importance of breastfeeding experience within one's social network, the influence of the infant's father, handling disagreement within one's network, and the effects of social norms that exist outside of one's network. Mothers described support for breastfeeding from network members as especially important when breastfeeding was not the norm within the network. There were no differences in themes by race or social network type. Conclusion: Breastfeeding behavior is influenced by a mother's social network, regardless of her race or social network type. Even when breastfeeding is not normative within one's social network, by relying on one network member to support them, mothers may be able to resist the opposing norms of their social network. Since breastfeeding is known to be beneficial to infants and mothers, education or interventions to improve breastfeeding rates may be more effective if they include individual network members who can provide strong support to new mothers.

Social Network and Functional Health Status among the Elderly

Background: In the absence of adequate public pension benefits, the older people in China have to rely on their social networks for old-age support. However, few empirical studies have been carried out to examine the pattern of social network and their impact on elderly health in China. Methods: Using the data set from two waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) conducted in 2008 and 2014, we examined the characteristics of social network types and their impacts on the health status among the elderly. The dependent variables included the measures of self-rated health (SRH), activities of daily living (ADL), instrumental activities of daily living (IADL), and cognitive score (MMSE). K-means clustering method was used to construct the social network type, which was the primary factor we were interested in examining for association with functional health status. A random-effect regression model was utilized to control for the clustering effects within the observations over time. Results: Four types of the social network were derived among the older people, and they were the diverse network (6.65%), family-focused network (32%), children-focused network (29.89%) and restricted network (31.45%). Compared with the restricted network, the diverse network was associated with the best functional health status and self-rated health among the elderly; the family-focused network was also associated with a better score of ADL, IADL, and MMSE but not significantly with SRH score; and the children-focused network was also associated with a better health status of all measures. Furthermore, social support from family members and friends positively influenced the health status of the elderly. In contrast, having social workers available when needed was associated with the reduced ADL, IADL, and SRH scores. This might be due to that those elderly with the worst health status are in a greater need for support from social workers, and hence, the reverse association may occur. Conclusion: family- and children-focused network were primary types among the older people in China. Consistent with previous studies, while the diverse network was most beneficial for the functional health status in multiple measures, it only accounted for a small proportion; people with the restricted network had the worst health status.

Land use discovery based on Volunteer Geographic Information classification

Nowadays, cities are dynamic ecosystems where urban changes occur at a very fast pace. Hence, social sensing has become a powerful tool to uncover the actual land-use of a metropolis. However, current solutions for land-use discovery based on user-generated data usually rely on an information retrieval mechanism applied on a textual corpus. This causes ad-hoc place labelling with limited semantic meaning. In this line, the present work introduces a novel data-driven methodology that extends existing solutions by means of a classifier based on a pre-defined hierarchy of land categories. Two types of social networks –text-based and venue-based platforms– are utilized to train the classifier, which is then applied to infer the use of the land based on text data in areas where venue data are not available. The approach has been evaluated by using large datasets comprising two large cities, showing an accuracy above 90% in predicting the land-use categories.

Social network types and cognitive decline among older Korean adults: A longitudinal population-based study.

Social network (SN) has been known to impact on cognitive function in late life. However, knowledge regarding the link between SN of various types and cognitive decline (CD) is limited. This study's aim was to investigate which types of SN are associated with reduced risk of CD 2 years later among community-dwelling older adults. Secondary analysis of data from 1960 cognitively intact adults 65 years of age or older who participated in the Korean Longitudinal Study of Aging (KLoSA) was employed. K-means cluster analysis was conducted to derive SN types using seven common SN characteristics (marital status, living with children, number of children, frequency of contact with children, frequency of contact with friends, frequency of participation in religious activities, and frequency of participation in social groups). Multivariable linear regression analysis regarding the effects of SN type on CD between 2012 and 2014 was conducted, controlling for covariates. K-means cluster analyses identified a model with five types of SN as being most optimal, and they were named diverse/couple, diverse/family, congregant, restricted/married, and widowed. The average CD 2 years later was most pronounced in those in the widowed network. Compared with the widowed, older adults in the diverse/couple network and the congregant network at baseline had a lower risk of CD 2 years after initial assessment. Findings show that older Korean adults embedded in widowed network types are at risk for CD and suggest the importance of having a spouse and religious group activities in maintaining cognitive function in later life.

Accuracy and availability modeling of social networks for Internet of Things event detection applications

As Social networks are widely used by the people around the world, if this infrastructure can be used for event detection systems like fire forest detection, the overall cost of the Internet of Thing event detection system cost may be considerably reduced. However, other parameters such as event detection accuracy and system availability may be affected as well. The present research investigates these parameters for famous social networks such as Instagram, Twitter and Facebook in different network sizes and server request submission limitations. A new web platform was implemented based on smart objects to produce the appropriate data for social network analysis tools such as NodeXL. A new simulator generated the data from the Drossel and Schwabl algorithm in various situations and types of social networks. Then the outputs created models by a multilayer perceptron artificial neural network for accuracy and availability. A cost analysis for each method was performed. The results showed that the produced models had good reliability and could be used to select the appropriate method before implementing the Internet of Things projects.

A blockchain‐based framework to secure vehicular social networks

AbstractVehicular social network is emerging as a new promising concept, combining two types of network paradigms, namely, vehicular networks and social networks. In order to manage efficiently the security and the control of the network, this paper proposes a new framework based on the emerging concepts of software‐defined vehicular network (SDVN) and blockchain. Using the SDVN makes the network more programmable, virtualized, and partitionable. However, on the other hand, it also creates a well‐known vulnerability of a single point of failure. Hence, we propose to introduce the blockchain paradigm that will enable the certification of transactions and ensure data anonymity in a fully distributed manner. To this end, three levels of controllers are needed: a principal controller (PC), roadside units (RSUs), and a local controller. In order to dynamically select miners, a distributed miners connected dominating set algorithm (DM‐CDS) has been proposed. The DM‐CDS is a single‐phase distributed algorithm that supports a dynamic topology based on a trust model and some other network parameters, such as the connectivity degree, the average link quality indicator, and the rank. The performance of the proposed DM‐CDS is evaluated throughout multiple scenarios using different parameters, such as trust metric, node density, node mobility, and radio range. The obtained results highlight the importance of such proposed architecture, especially in terms of number of required miners. For instance, when the density of nodes increases, the number of selected miners increases similarly to when the network length increases. The node mobility impacts also on the stability of the selected miners, in terms of withdrawing and joining, showing a variation between 0% and 10%. The trust metric has also an important impact on the selection of miners, as only nodes with a higher trust level are selected to endorse the roles of miners.