Trust In Social Networks Research Articles

Adaptive Reputation Promotes Trust in Social Networks

Trust has played a pivotal role in the evolution of modern human societies, and it continues to be an essential underpinning of our social interactions. It is therefore important that we develop rigorous mathematical foundations that will enable us to better understand what promotes and what erodes trust and how to best preserve trustworthiness. To that effect we here propose a trust game, wherein investors, trustworthy trustees, and untrustworthy trustees compete for assets subject to a third-party evaluation system that oversees and modifies each individual reputation. We use Monte Carlo simulations on social networks to determine critical values of the degree of rationality and the reputation threshold that warrant high levels of trust and social wealth. We show that if investors have access to the reputation scores of trustees, the fraction of untrustworthy trustees drops if only the degree of rationality is sufficiently large, and this irrespective of the reputation threshold that determines the cutoff for untrustworthiness. But even though investors are allowed irrational investments, trust can still proliferate if the reputation threshold is sufficiently high. Our results thus formalize essential mechanisms of trust in social networks, which also outline policies to diminish untrustworthiness that can be employed in real life.

Social Context-Aware Trust Network Discovery in Complex Contextual Social Networks

Trust is one of the most important factors for participants' decision-making in Online Social Networks (OSNs). The trust network from a source to a target without any prior interaction contains some important intermediate participants, the trust relations between the participants, and the social context, each of which has an important influence on trust evaluation. Thus, before performing any trust evaluation, the contextual trust network from a given source to a target needs to be extracted first, where constraints on the social context should also be considered to guarantee the quality of extracted networks. However, this problem has been proved to be NP-Complete. Towards solving this challenging problem, we first propose a complex contextual social network structure which considers social contextual impact factors. These factors have significant influences on both social interaction between participants and trust evaluation. Then, we propose a new concept called QoTN (Quality of Trust Network) and a social context-aware trust network discovery model. Finally, we propose a Social Context-Aware trust Network discovery algorithm (SCAN) by adopting the Monte Carlo method and our proposed optimization strategies. The experimental results illustrate that our proposed model and algorithm outperform the existing methods in both algorithm efficiency and the quality of the extracted trust network.

Media in Croatia: from freedom fighters to tabloid avengers

The article provides an overview of the Croatian media landscape and its transformation that has been driven by the processes of democratization, commercialization and digitalization.The main media-related concerns from 1990 to 2000 were freedom of the press, autonomy of journalism and censorship. The liberalization of the media market that started in 2000, led to proliferation of media outlets and galloping commercialization of media ownership and content. The next big change came with digitalization that fundamentally altered media habits of Croatian audiences. Television was preceded by online media as the main source of news while the press registers constant decline in readership, trust and advertising revenues. Radio remains the most trusted medium, as opposed to social media that are the least trusted source of information. Nevertheless, the level of trust in social networks in Croatia is considerably higher than the EU average.The data on media freedom and journalistic autonomy indicate that Croatia has made significant progress in this respect in the past thirty years. Although problems related to freedom, autonomy and political pressure persist, the biggest threat to journalism nowadays seems to come from within the profession. Commercialization, coupled with digitalization and merciless struggle for survival, eventually led news media to succumb to tabloid-style journalism and to radically downplay their professional standards. Although the role of the media as a social corrective remains undisputed, such media practices seem to cultivate ‘media fatigue’ and foster distrust in political institutions. In such an ethically challenging environment, the newsrooms and professional organizations remain for the most part silent about eroding professional standards.

SenseTrust: A Sentiment Based Trust Model in Social Network

Online social networks, as popular media and communications tools with their own extensive uses, play key roles in public opinion polls, politics, economy, and even governance. An important issue regarding these networks is the use of multiple sources of publishing or re-publishing news and propositions that can influence audiences depending on the level of trust in these sources between users. Therefore, estimating the level of trust in social networks between users can predict the extent of social networks’ impact on news and different publication and re-publication sources, and correspondingly provide effective strategies in news dissemination, advertisements, and other diverse contents for trustees. Therefore, trust is introduced and interpreted in the present study. A large portion of interactions in social networks is based on sending and receiving texts employing natural language processing techniques. A Hidden Markov Model (HMM) was designed via an efficient model, namely SenseTrust, to estimate the level of trust between users in social networks.

Does Social Capital Promote Garbage Classification? Evidence From China

A new round of garbage classification campaign is carrying out in China. Using Chinese General Social Survey (CGSS) Data in 2013, the study focuses on the influence mechanism of social capital on garbage classification in China and the difference between urban and rural areas. Descriptive analysis, Ordered Logit model and “Coefficient clustering method” were used in this study. The results show that social capital (online social capital, social network, social trust) can effectively promote garbage classification after controlling the relevant individual characteristic variables in China. China’s garbage classification is embedded in the Chinese social environment. Further analyzing the marginal effect of social capital found that online social capital has the large marginal effect. The effect of social network is greater than the influence effect of social trust. But the marginal effect of social trust is higher than the marginal effect of social network. And social trust has the largest marginal effect. This not only makes up for the previous literature’s neglect of online social capital, marginal effect, but also illustrates the importance of online social capital. And it proves the interaction between traditional Chinese social network and modern social trust. In addition, the influence of social capital on urban and rural garbage classification is heterogeneous in China. Both social trust and social network have influence on the urban classification garbage. However, only social network have a significant influence in rural areas, and social trust has not played a role. China’s garbage classification should focus on social factors, that is, the influence of social capital. It is necessary to follow the coupling between the top-down logic of government and the bottom-up logic of society, and realize the nationwide participation. It is of great significance for promoting the sustainable development of China and the sustainable development of the world.

The Mediating Role of Social Capital in Digital Information Technology Poverty Reduction an Empirical Study in Urban and Rural China

Widespread use of digital information technology is having a significant impact on economic growth and people’s well-being. This paper assesses the mediating role of social capital in the impact of digital information technology on multidimensional poverty. Due to differences in regional, industrial structure and other factors, digital information technology has different impacts on urban and rural residents. In this paper, the China Family Panel Studies (CFPS) database is used for data, and a mediating effect model is used to study the problem. The digital information technology use was found to enhance social capital from social network, social participation and social trust, and subsequently alleviates multidimensional poverty. The results indicate that social trust plays a more significant mediating role than social capital and social participation on the impact of digital information technology on multidimensional poverty. Furthermore, the results reveal that the use of digital information technology has varying effects on poverty reduction among different income groups, with a much higher effect on low-income groups. However, the mediating effect of social capital in high-income groups is higher than that in low-income groups. In particular, social capital in the top 25% of income groups has the highest mediating effect. In the heterogeneity analysis between urban and rural areas, it is found that the multidimensional poverty situation in urban areas is significantly better than that in rural areas, because urban residents have a higher use of digital information, and at the same time, the quality of social capital in urban and rural groups is different, leading to the difference in the effect of digital information technology on poverty reduction of multidimensional poverty. Based on the results of the study, we believe that the use of digital information technology has actually improved the multi-dimensional poverty status of all groups, and social capital plays a key mediating role in it. Relying on the progress of digital information technology, we can build more convenient social network. Establish more adequate channels of information communication, enhance social trust and social participation, and alleviate multidimensional poverty.

Fake News Reaching Young People on Social Networks: Distrust Challenging Media Literacy

Current societies are based on huge flows of information and knowledge circulating on the Internet, created not only by traditional means but by all kinds of users becoming producers, which leads to fake news and misinformation. This situation has been exacerbated by the pandemic to an unprecedented extent through social media, with special concern among young people. This study aims to provide significant data about the youngest generation in Spain (Generation Z) regarding their media and information consumption, their social network use, and their relationship with fake news, all in relation to the feeling of reliability/trust. Focusing on a convenience sample of 408 young Spanish students from Generation Z aged 18 to 22, a descriptive exploratory study is presented. Data collection was performed with an adapted questionnaire. Results show that young Spanish people use networks for information, showing a surprising lack of trust in social networks as the media they consume the most. The content they consume the most since the occurrence of COVID-19 is related to politics, entertainment, humor, and music. On the other hand, distrust of politicians, media, and journalists is evident. The conclusion is that media literacy is still more necessary than ever, but with the added challenge of mistrust: maybe it is time to rethink media literacy.

The relationship between social interactions, trust, business network, external knowledge access and performance: a study of SMEs in Ghana

PurposeThe purpose of this paper is to examine the role of social interaction ties, trust and business networks in the acquisition of foreign business knowledge and foreign institutional knowledge. It also assesses the effect of these types of knowledge on small and medium enterprises’ (SME) export performance. Furthermore, this study determines the moderating role of absorptive capacity in the relationship between foreign business knowledge, foreign institutional knowledge and export performance.Design/methodology/approachThis study used a survey research design using data from nontraditional SME exporters in Ghana. There were 257 respondents who were employees (managers/owners) of SMEs in Ghana. The model was analyzed using structural equation modeling.FindingsSocial interaction ties, trust and business networks have a significant effect on the acquisition of foreign business knowledge and foreign institutional knowledge. Furthermore, foreign business knowledge and foreign institutional knowledge have a significant positive effect on export performance. The path between foreign business knowledge and export performance is also moderated by absorptive capacity. However, the moderating role of absorptive capacity in the relationship between foreign institutional knowledge and export performance is not significant.OriginalityThis study uses social capital to explain how SMEs acquire foreign business knowledge and foreign institutional knowledge, and how both affect SMEs’ export performance. Furthermore, it tests the moderating role of absorptive capacity in the relationship between foreign business knowledge, foreign institutional knowledge and export performance.

The Role of Social Networks During the COVID-19 Lockdown: Real-Life Social Distancing Vs Virtual Interactions

Online social networks have become one of the most widely used sources of information in the world and also an important part of our daily life. A huge boost to their spreading came with the outbreak of the COVID-19 pandemic. As social distancing and lockdown orders due to COVID-19 health emergency grew more pervasive, individuals began to spend more time online and to use social networks (SNs) to keep up to date regarding the spread of pandemic and also to maintain communication with friends and family and reduce isolation. Given these evidences, the present study aims to investigate the social supporting role of SNs during the pandemic emergency. Specifically, it intends to analyze (a) the use of SNs as a means of interaction in the face of the social containment imposed by the COVID-19 spreading, and (b) the factors (homophily, trust, loneliness, and emotional instability) that affect such use. An online survey with a sample of 194 Italian people was conducted. Structural equation modelling was used to estimate the model proposed. Results revealed that sense of belonging to SNs had a strong impact on search for social support and is, in turn, positively influenced by trust in SNs and homophily. Emotional instability also increased the search for social support. The study contributes both theoretically and empirically to the understanding of the role of SNs in influencing individual behavior. As the use of SNs continues to spread around the world, understanding why consumers rely in SNs and what gratifications they receive from them is undoubtedly of interest for both academics and practitioners.

The critical role of trust in experiencing and coping with energy poverty: Evidence from across Europe

Trust is a fundamental ingredient of prosperous democracies. In Europe, trust in existing elected democratic institutions is fading while authoritarian nationalist movements grow. Experiences of neglect, ignorance, and inferiority are one explanation for this. This paper explores the link between the experiences of households in a state of energy poverty and their trust in institutions and social networks. Using qualitative data from ten different European countries, we show that a lack of trust in both public and private institutions is widespread among energy-poor households. Our interviewees show distrust in various dimensions. In their contacts with institutions, they report experiences of powerlessness, bad and unfair treatment, and feelings of inferiority. While some interviewees do trust single individuals within institutions, others trust only their own social networks and some have no trust in anyone. We further show how trust in networks or (people in) institutions can strengthen the coping capacities of energy-poor households while a lack of trust even cuts people off from the support they could attain and thus deepens their state of energy poverty.

Social Trust Driven Consensus Reaching Model With a Minimum Adjustment Feedback Mechanism Considering Assessments-Modifications Willingness

Social network group decision making (SNGDM) has emerged as a new decision tool to effectively model the social trust relationships among decision makers. The impact of the social trust relationships on assessments-modifications in the consensus reaching in the SNGDM is seldom considered. This study aims at addressing this issue. The main starting point is the assumption that a decision maker will not be willing to accept the assessments-modifications suggestions that significantly differ from his/her trusted decision makers’ assessments in a social trust network. Thus, this study proposes a social trust driven minimum adjustments consensus model (STDMACM) for SNGDM. Simultaneously, a social trust driven consensus maximum optimization model (STDCMOM) is proposed for maximizing the consensus level among decision makers under the above assumption. Based on both STDCMOM and STDMACM, an interactive consensus reaching process is presented, in which the assessments-modifications suggestions generated from the STDMACM are used, when the maximum consensus level obtained from STDCMOM is acceptable, as the references for guiding the consensus reaching; otherwise, assessments-modifications suggestions are generated from the designed STDCMOM. The validity of the social trust driven consensus reaching process with respect to its consensus convergence rate and consensus success ratio is verified with a simulation and comparison analysis.

Multi-attribute group decision making with opinion dynamics based on social trust network

Social trust network (STN) has facilitated information exchange between experts during interactions. Some feedback mechanisms have been used to provide advices for opinion change to improve their consensus levels. However, they do not consider the experts’ willingness and their self-confidence values. To analyze the influence of the relationship between experts on the decision-making results, this paper proposes a multi-attribute group decision making (MAGDM) with opinion dynamics based on STN. Three stages are included in the proposed approach: trust propagation, consensus reaching process and alternative selection. In the trust propagation stage, the social weight influence matrix and the weights of experts are obtained based on the complete social trust matrix which is constructed by trust aggregation and the given self-confidence values of experts. In the consensus reaching process, the consensus measure is used to determine the consensus between the experts or not, and the feedback mechanism based on opinion dynamics is used to adjust the opinions which do not reach consensus. The appropriate alternative is selected based on the assessable value of the alternative in the selection process. Finally, a numerical experiment about supplier selection is introduced to illustrate the efficiency of the proposed approach and comparison analyses show that the proposed approach can improve efficiency compared with the MAGDM in the social network.

Community Development from the Lens of Social Capital: A Sociological Study of Rupa Rural Municipality of Kaski, Nepal

Social trust and social networks are a common and more valuable phenomenon for the development activities of the rural community in the context of Nepal. However, the development activities of the community are not well perceived from the lens of social trust and social network as it is essential to sustain the development activities. Considering the landscape of social trust and social networks, this study focuses on the situation and effect of social trust and social networks on the development activities at the Rupa Rural Municipality in Kaski. The purpose of this study was to explain the situation of social trust and social networks and also explore interconnection with community-level development interventions. Employing a phenomenological qualitative research design, the primary informations were collected through indepth interviews and recorded informations were transcribed, coded, decoded, analyzed and interpreted. The major thematic aspects such as social trust and social networks of community development have linked with relevant theories. The finding indicate that the development activities of community with their desire and having social trust are found successful. The social networks have played further connective role by interlinking development aspects at community level for sustaining the intervetions of community development. Though the study is limited to Rupa Rural Municipality, it has established the importance of social trust and social networks for community development.

MODELING THE PROTECTION OF PERSONAL DATA FROM TRUST AND THE AMOUNT OF INFORMATION ON SOCIAL NETWORKS

The article analyzes the parameters of social networks. The analysis is performed to identify critical threats. Threats may lead to leakage or damage to personal data. The complexity of this issue lies in the ever-increasing volume of data. Analysts note that the main causes of incidents in Internet resources are related to the action of the human factor, the mass hacking of IoT devices and cloud services. This problem is especially exacerbated by the strengthening of the digital humanistic nature of education, the growing role of social networks in human life in general. Therefore, the issue of personal information protection is constantly growing. To address this issue, let’s propose a method of assessing the dependence of personal data protection on the amount of information in the system and trust in social networks. The method is based on a mathematical model to determine the protection of personal data from trust in social networks. Based on the results of the proposed model, modeling was performed for different types of changes in confidence parameters and the amount of information in the system.
 As a result of mathematical modeling in the MatLab environment, graphical materials were obtained, which showed that the protection of personal data increases with increasing factors of trust in information. The dependence of personal data protection on trust is proportional to other data protection parameters. The protection of personal data is growing from growing factors of trust in information.
 Mathematical modeling of the proposed models of dependence of personal data protection on trust confirmed the reliability of the developed model and proved that the protection of personal data is proportional to reliability and trust

Consensus reaching with the externality effect of social network for three-way group decisions

Three-way group decisions provide an efficient method to settle complex and high risk decision-making problems. To obtain reasonable decision results that satisfy different backgrounds and knowledge of decision makers, it is necessary to design a proper consensus reaching process (CRP) for loss functions of decision-theoretic rough sets (DTRSs). Unlike existing researches, this paper not only extends the group relationship among decision makers to the social network, but also considers the externality of social trust network in group decision making. In light of this idea, we design a new CRP with the externality of social network for three-way group decisions. In the CRP, the adjustment of a decision maker who is persuaded by the moderator can influence other decision makers to accordingly adjust evaluations. Thus, by using the linkage externality influence among decision makers, we establish a two-stage mixed 0–1 linear optimization consensus model for the determination of loss functions of DTRSs. Then, based on Bayesian decision procedure, we construct a complete decision procedure for three-way group decisions with social network. Finally, we apply our proposed method to assess desert locust invasion areas and verify its validity.

A Study to Understand Factors Affecting Social Network Usage

Users may join social networks (SNS) for many personal or professional purposes. While many individuals voluntarily join SNS, for some, this may also be a form of forced use. However, in both cases there are some factors that influence SNS use. This research uses Technology Acceptance Model and includes trust and satisfaction factors and the technical aspects of SNS. Data collected from university students by survey technique was analyzed. As a result; the research model has good fit indices, and the factors in the model have relationships of varying strengths and significance with each other. Trust in SNS positively affects the continuance intention to SNS. However, the relationship between trust in others and the continuance intention did not turn out as predicted. Informativeness affects both perceived usefulness and perceived enjoyment constructs in a positive and significant way. While interactivity significantly affects perceived usefulness, there is no significant relationship between it and perceived enjoyment. There are also positive and significant relationship between satisfaction, intention, perceived usefulness and perceived enjoyment.

An overlap graph model for large‐scale group decision making with social trust information considering the multiple roles of experts

AbstractSocial network analysis is an efficient tool to investigate the relationships of decision‐makers in large‐scale group decision making (LSGDM). Existing social network‐based LSGDM studies generally assumed that each decision‐maker has a single role or belongs to only one subgroup. The assumption that a decision‐maker has multiple roles or belongs to multiple subgroups is rarely taken into consideration. In this regard, this study proposes an overlap graph model (OGM) in which decision‐makers can participate in the decision‐making process in multiple roles to solve LSGDM problems with social trust information. In the OGM, decision‐makers are firstly divided into two types: multiple‐role decision‐makers and single‐role decision‐makers. Since it is unpractical for a decision‐maker to evaluate all others in a LSGDM problem, we then investigate how to construct a complete social trust network based on an Agent mechanism. A two‐stage consensus reaching process is proposed to reduce the discrepancies among decision‐makers: The first stage is for single‐role decision‐makers within a subgroup while the second stage is for Agents and multiple‐role decision‐makers. Finally, an illustrative example regarding selecting treatment plans for critical patients in COVID‐19 is provided to test the applicability and rationality of the proposed model.

Modal Sosial Kelompok Rentan Sebagai Upaya Disaster Risk Reduction (DRR)

Padang City has a low resilience for earthquake and tsunami disaster. Actually, social capital can be used as a strategy for overcoming impacts and efforts to reduce the level of risk of disaster. According to Siegler, social capital has four aspects, there are personal relationships, social network support, civic engagement, and trust and cooperative norms. The research objectives are: 1) Describe the knowledge and experience of vulnerable groups in dealing with disasters (earthquake and tsunami); 2) Identifying vulnerable groups' social capital as a disaster risk reduction (DRR) effort; 3) Describe the opportunities and obstacles/threats in the use of social capital as an effort to disaster risk reduction (DRR). The research method is qualitative with a case study. The location of this research in Pasie Nan Tigo, Koto Tangah District, Padang City. The determination of informants is a purposive sampling technique. This research has 22 informants. The criteria of informants are; 1) Have settled in a red zone area for at least 5 years; 2) The distance between the house and the beach is a maximum radius of 3 km. The results of the research are; 1) Vulnerable groups have the knowledge and experience about disasters; 2) Social groups already have social capital in 4 aspects of social capital such as personal relationships, social networking support, civic engagement, and trust and cooperative norm; 3) Social capital has opportunities and challenges from the internal and external side. Keywords: Social Capital, DRR

Opportunity Inequality, Social Capital and Subjective Well-Being of Rural Residents: Empirical Analysis Based on CGSS Data

Chasing happiness is the ultimate goal of economic development and people’s lives. For a country with 550 million farmers, improving farmers’ happiness is particularly important. However, economic growth does not seem to make people happier. Most studies have explained this phenomenon from the perspective of income inequality, but there is a lack of identification of the impact of opportunity inequality, especially the research on the mechanism of the impact of opportunity inequality on farmers’ happiness. Based on this, this paper uses multiple mediating effect models to explore the relationship between opportunity inequality, social capital and farmers’ subjective well-being with CGSS data in 2013 and 2015. The innovation of this paper is that, firstly, based on the research of Bjornskov（2006）, social capital is divided into two dimensions: social network and social trust, so as to reveal the relationship between opportunity inequality, social capital and farmers’ subjective well-being. More importantly, by dividing social capital into the two dimensions, we can identify which dimension plays a more important role. Secondly, we use a measurement of opportunity inequality which is different from previous studies. Previous studies have conducted a simple arithmetical average of income equity, educational opportunity and socioeconomic status to obtain the perceived index of opportunity inequality, which has two shortcomings: First, access to basic public services is particularly inadequate for rural residents, which has become one of the obstacles to equal opportunities. Therefore, if there is no evaluation of “access to public services”, the unequal level of rural opportunities cannot be fully and truly depicted. Second, the importance of each dimension is different, and a simple arithmetic average magnifies or diminishes the effects of each dimension. Therefore, we use the coefficient of variation method to weight each dimension. The main conclusions of this paper are as follows: （1）The expansion of unequal opportunities will reduce the subjective well-being of farmers, while social trust and social network will improve the subjective well-being of farmers.（2）When constructing the perception index of unequal opportunity, the negative impact of unequal opportunity on farmers’ subjective well-being will be underestimated if the dimension of “access to public services” and the weight of each dimension are not taken into account.（3）Opportunity inequality affects farmers’ happiness mainly through social trust, while the mediating effect of social network is not significant.

Association Between Public Knowledge About COVID-19, Trust in Information Sources, and Adherence to Social Distancing: Cross-Sectional Survey.

BackgroundThe success of behavioral interventions and policies designed to reduce the impact of the COVID-19 pandemic depends on how well individuals are informed about both the consequences of infection and the steps that should be taken to reduce the impact of the disease.ObjectiveThe aim of this study was to investigate associations between public knowledge about COVID-19, adherence to social distancing, and public trust in government information sources (eg, the US Centers for Disease Control and Prevention), private sources (eg, FOX and CNN), and social networks (eg, Facebook and Twitter) to inform future policies related to critical information distribution.MethodsWe conducted a cross-sectional survey (N=1243) between April 10 and 14, 2020. Data collection was stratified by US region and other demographics to ensure representativeness of the sample.ResultsGovernment information sources were the most trusted among the public. However, we observed trends in the data that suggested variations in trust by age and gender. White and older populations generally expressed higher trust in government sources, while non-White and younger populations expressed higher trust in private sources (eg, CNN) and social networks (eg, Twitter). Trust in government sources was positively associated with accurate knowledge about COVID-19 and adherence to social distancing. However, trust in private sources (eg, FOX and CNN) was negatively associated with knowledge about COVID-19. Similarly, trust in social networks (eg, Facebook and Twitter) was negatively associated with both knowledge and adherence to social distancing.ConclusionsDuring pandemics such as the COVID-19 outbreak, policy makers should carefully consider the quality of information disseminated through private sources and social networks. Furthermore, when disseminating urgent health information, a variety of information sources should be used to ensure that diverse populations have timely access to critical knowledge.