Trust levels in social networks

A Distributed Method for Trust-Aware Recommendation in Social Networks

This paper contains the details of a distributed trust-aware recommendation system. Trust-base recommenders have received a lot of attention recently. The main aim of trust-based recommendation is to deal the problems in traditional Collaborative Filtering recommenders. These problems include cold start users, vulnerability to attacks, etc.. Our proposed method is a distributed approach and can be easily deployed on social networks or real life networks such as sensor networks or peer to peer networks.

Trust and Trustworthiness in Social Recommender Systems

The prevalence of misinformation on online social media has tangible empirical connections to increasing political polarization and partisan antipathy in the United States. Ranking algorithms for social recommendation often encode broad assumptions about network structure (like homophily) and group cognition (like, social action is largely imitative). Assumptions like these can be naïve and exclusionary in the era of fake news and ideological uniformity towards the political poles. We examine these assumptions with aid from the user-centric framework of trustworthiness in social recommendation…

基于信任的依附（Trust based attachment）

Trust based attachment

本研究围绕间接互惠社会系统中流言传播对声誉的影响展开，提出基于信任的依附（TBA）社交网络生成算法，其生成网络具备真实网络的关键属性，且可通过三元闭包近似，为三元闭包提供了基于信任与信息传播的新解释。

Clarifying Trust in Social Internet of Things

A social approach can be exploited for the Internet of Things (IoT) to manage a large number of connected objects. These objects operate as autonomous agents to request and provide information and services to users. Establishing trustworthy relationships among the objects greatly improves the effectiveness of node interaction in the social IoT and helps nodes overcome perceptions of uncertainty and risk. However, there are limitations in the existing trust models. In this paper, a comprehensive model of trust is proposed that is tailored to the social IoT. The model includes ingredients such a…

A Framework to Support the Trust Process in News and Social Media

Current society is heavily influenced by the spread of online information, containing all sorts of claims, commonly found in news stories, tweets, and social media postings. Depending on the user, they may be considered "true" or "false", according to the agent's trust on the claim. In this paper, we discuss the concept of content trust and trust process, and propose a framework to describe the trust process, which can support various possible models of content trust.

Trust-SIoT: Towards Trustworthy Object Classification in the Social Internet of Things

The recent emergence of the promising paradigm of the Social Internet of Things (SIoT) is a result of an intelligent amalgamation of the social networking concepts with the Internet of Things (IoT) objects (also referred to as "things") in an attempt to unravel the challenges of network discovery, navigability, and service composition. This is realized by facilitating the IoT objects to socialize with one another, i.e., similar to the social interactions amongst the human beings. A fundamental issue that mandates careful attention is to thus establish, and over time, maintain trustworthy relat…

基于超图赋能的自监督对比学习实现社交IoT系统的精确信任评估与有效运行

Accurate Trust Evaluation for Effective Operation of Social IoT Systems via Hypergraph-Enabled Self-Supervised Contrastive Learning

本文提出超图赋能自监督对比学习（HSCL）方法，利用超图表示和融合设备间高阶社交关系，通过对比学习获取设备嵌入以准确计算信任值，实验证明其在区分受信任节点方面优于基线算法。

When Do People Trust Their Social Groups?

Trust facilitates cooperation and supports positive outcomes in social groups, including member satisfaction, information sharing, and task performance. Extensive prior research has examined individuals' general propensity to trust, as well as the factors that contribute to their trust in specific groups. Here, we build on past work to present a comprehensive framework for predicting trust in groups. By surveying 6,383 Facebook Groups users about their trust attitudes and examining aggregated behavioral and demographic data for these individuals, we show that (1) an individual's propensity to …

Trust transitivity in social networks

Non-centralized recommendation-based decision making is a central feature of several social and technological processes, such as market dynamics, peer-to-peer file-sharing and the web of trust of digital certification. We investigate the properties of trust propagation on networks, based on a simple metric of trust transitivity. We investigate analytically the percolation properties of trust transitivity in random networks with arbitrary degree distribution, and compare with numerical realizations. We find that the existence of a non-zero fraction of absolute trust (i.e. entirely confident tru…

Trust Assessment in Online Social Networks

Assessing trust in online social networks (OSNs) is critical for many applications such as online marketing and network security. It is a challenging problem, however, due to the difficulties of handling complex social network topologies and conducting accurate assessment in these topologies. To address these challenges, we model trust by proposing the three-valued subjective logic (3VSL) model. 3VSL properly models the uncertainties that exist in trust, thus is able to compute trust in arbitrary graphs. We theoretically prove the capability of 3VSL based on the Dirichlet-Categorical (DC) dist…

What Do We Mean When We Talk about Trust in Social Media? A Systematic Review

Do people trust social media? If so, why, in what contexts, and how does that trust impact their lives? Researchers, companies, and journalists alike have increasingly investigated these questions, which are fundamental to understanding social media interactions and their implications for society. However, trust in social media is a complex concept, and there is conflicting evidence about the antecedents and implications of trusting social media content, users, and platforms. More problematic is that we lack basic agreement as to what trust means in the context of social media. Addressing thes…

Extracting Implicit Social Relation for Social Recommendation Techniques in User Rating Prediction

Recommendation plays an increasingly important role in our daily lives. Recommender systems automatically suggest items to users that might be interesting for them. Recent studies illustrate that incorporating social trust in Matrix Factorization methods demonstrably improves accuracy of rating prediction. Such approaches mainly use the trust scores explicitly expressed by users. However, it is often challenging to have users provide explicit trust scores of each other. There exist quite a few works, which propose Trust Metrics to compute and predict trust scores between users based on their i…

Bridge the Gap: Measuring and Analyzing Technical Data for Social Trust between Smartphones

Mobiles are nowadays the most relevant communication devices in terms of quantity and flexibility. Like in most MANETs ad-hoc communication between two mobile phones requires mutual trust between the devices. A new way of establishing this trust conducts social trust from technically measurable data (e.g., interaction logs). To explore the relation between social and technical trust, we conduct a large-scale survey with more than 217 Android users and analyze their anonymized call and message logs. We show that a reliable a priori trust value for a mobile system can be derived from common soci…

Understanding the Trustworthiness Management in the Social Internet of Things: A Survey

The next generation of the Internet of Things (IoT) facilitates the integration of the notion of social networking into smart objects (i.e., things) in a bid to establish the social network of interconnected objects. This integration has led to the evolution of a promising and emerging paradigm of Social Internet of Things (SIoT), wherein the smart objects act as social objects and intelligently impersonate the social behaviour similar to that of humans. These social objects are capable of establishing social relationships with the other objects in the network and can utilize these relationshi…

Towards a Machine Learning-driven Trust Evaluation Model for Social Internet of Things: A Time-aware Approach

The emerging paradigm of the Social Internet of Things (SIoT) has transformed the traditional notion of the Internet of Things (IoT) into a social network of billions of interconnected smart objects by integrating social networking facets into the same. In SIoT, objects can establish social relationships in an autonomous manner and interact with the other objects in the network based on their social behaviour. A fundamental problem that needs attention is establishing of these relationships in a reliable and trusted way, i.e., establishing trustworthy relationships and building trust amongst o…

Providing Trustworthy Contributions via a Reputation Framework in Social Participatory Sensing Systems

Social participatory sensing is a newly proposed paradigm that tries to address the limitations of participatory sensing by leveraging online social networks as an infrastructure. A critical issue in the success of this paradigm is to assure the trustworthiness of contributions provided by participants. In this paper, we propose an application-agnostic reputation framework for social participatory sensing systems. Our framework considers both the quality of contribution and the trustworthiness level of participant within the social network. These two aspects are then combined via a fuzzy infer…

The Role of Social Networks in Online Shopping: Information Passing, Price of Trust, and Consumer Choice

While social interactions are critical to understanding consumer behavior, the relationship between social and commerce networks has not been explored on a large scale. We analyze Taobao, a Chinese consumer marketplace that is the world's largest e-commerce website. What sets Taobao apart from its competitors is its integrated instant messaging tool, which buyers can use to ask sellers about products or ask other buyers for advice. In our study, we focus on how an individual's commercial transactions are embedded in their social graphs. By studying triads and the directed closure process, we q…

Personalized multi-faceted trust modeling to determine trust links in social media and its potential for misinformation management

In this paper, we present an approach for predicting trust links between peers in social media, one that is grounded in the artificial intelligence area of multiagent trust modeling. In particular, we propose a data-driven multi-faceted trust modeling which incorporates many distinct features for a comprehensive analysis. We focus on demonstrating how clustering of similar users enables a critical new functionality: supporting more personalized, and thus more accurate predictions for users. Illustrated in a trust-aware item recommendation task, we evaluate the proposed framework in the context…

Extracting the trustworthiest way to service provider in complex online social networks

In complex online social networks, it is crucial for a service consumer to extract the trustworthiest way to a target service provider from numerous social trust paths between them. The extraction of the trustworthiest way (namely, optimal social trust path (OSTP)) with multiple end-to-end quality of trust (QoT) constraints has been proved to be NP-Complete. Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this challenging problem. However, existing solutions cannot guarantee the efficiency of searching, that is, they can hardly avoid obt…

Credibility Analysis in Social Big Data

The concept of social trust has attracted an attention of information processors/data scientists and information consumers / business firms. One of the main reasons for acquiring the value of SBD is to provide frameworks and methodologies using which the credibility of online social services users can be evaluated. These approaches should be scalable to accommodate large-scale social data. Hence, there is a need for well comprehending of social trust to improve and expand the analysis process and inferring credibility of social big data. Given the exposed environment's settings and fewer limit…

Threshold-Based Heuristics for Trust Inference in a Social Network

Trust among the users of a social network plays a pivotal role in item recommendation, particularly for the cold start users. Due to the sparse nature of these networks, trust information between any two users may not be always available. To infer the missing trust values, one well-known approach is path based trust estimation, which suggests a user to believe all of its neighbors in the network. In this context, we propose two threshold-based heuristics to overcome the limitation of computation for the path based trust inference. It uses the propagation phenomena of trust and decides a thresh…

Knowledge, Trust, Security and Covertness In Massively Distributed Social Platforms: An Epistemic Networks Approach

Social networks seeded, crystallized and structured by large-scale social platforms like Facebook, LinkedIn, Slack, Twitter, WhatsApp, Instagram and WeChat exhibit complicated epistemic structures and dynamics that arise from the nature of interactive knowledge that users/participants possess, share and shape. What users know about what other users know, about what other users know they know, and so forth, plays an important role in channeling user behavior on the platform as well as the structuring and dynamics of the social network the platform engenders. We use a novel approach to character…

Investigating the Effect of Attributes on User Trust in Social Media

One main challenge in social media is to identify trustworthy information. If we cannot recognize information as trustworthy, that information may become useless or be lost. Opposite, we could consume wrong or fake information with major consequences. How does a user handle the information provided before consuming it? Are the comments on a post, the author or votes essential for taking such a decision? Are these attributes considered together and which attribute is more important? To answer these questions, we developed a trust model to support knowledge sharing of user content in social medi…

Studying the Affecting Factors on Trust in Social Commerce

Recently, e-commerce has enjoyed the appearance of many novel opportunities created as a result of the increasing growth of social networks. Social commerce (s-commerce), an offspring of e-commerce, interconnects users and helps with the commerce process facilitated by social networks as well as other media. Uncertainty and trust are always an issue in any type of commerce and especially in s-commerce where, due to its nature, a higher level of risk and uncertainty exists. Despite the history for trust in virtual commercial transactions, there are a limited number of researches on the topic; a…

我们能否量化信任？迈向基于信任的弹性SIoT网络

Can we Quantify Trust? Towards a Trust-based Resilient SIoT Network

本文研究社交物联网中的信任量化问题，提出融合直接信任、间接推荐信任及社交相似性关系，并通过加权求和生成单一信任分数，以识别可信对象和信任相关攻击，构建弹性SIoT网络。

Social Trust Prediction via Max-norm Constrained 1-bit Matrix Completion

Social trust prediction addresses the significant problem of exploring interactions among users in social networks. Naturally, this problem can be formulated in the matrix completion framework, with each entry indicating the trustness or distrustness. However, there are two challenges for the social trust problem: 1) the observed data are with sign (1-bit) measurements; 2) they are typically sampled non-uniformly. Most of the previous matrix completion methods do not well handle the two issues. Motivated by the recent progress of max-norm, we propose to solve the problem with a 1-bit max-norm …

Towards Time-Aware Context-Aware Deep Trust Prediction in Online Social Networks

Trust can be defined as a measure to determine which source of information is reliable and with whom we should share or from whom we should accept information. There are several applications for trust in Online Social Networks (OSNs), including social spammer detection, fake news detection, retweet behaviour detection and recommender systems. Trust prediction is the process of predicting a new trust relation between two users who are not currently connected. In applications of trust, trust relations among users need to be predicted. This process faces many challenges, such as the sparsity of u…

A Matrix Factorization Model for Hellinger-based Trust Management in Social Internet of Things

The Social Internet of Things (SIoT), integration of the Internet of Things and Social Networks paradigms, has been introduced to build a network of smart nodes that are capable of establishing social links. In order to deal with misbehaving service provider nodes, service requestor nodes must evaluate their trustworthiness levels. In this paper, we propose a novel trust management mechanism in the SIoT to predict the most reliable service providers for each service requestor, which leads to reduce the risk of being exposed to malicious nodes. We model the SIoT with a flexible bipartite graph …

在线社交网络中信任量化建模的综述

A Survey on Quantitative Modeling of Trust in Online Social Networks

本文综述了在线社交网络中信任建模的最新发展，涵盖信任理论、算法分类、建模机制及应用实践，旨在为信任量化建模提供全面的参考和指导。

Trust as a Metric for Resiliency in Signed Social Networks

Recent technological advancements have resulted in a surge in online trading, raising severe concerns about theft and fraud, especially on platforms like Bitcoin OTC (over-the-counter), where users' identities remain anonymous. To mitigate the risk, it has become essential to capture the reputation of users based on their trade histories. The who-trusts-whom signed network of people has the capability to reflect the nature of such positive and negative relations between the users. It can be used to analyze linkage patterns, strength, and resiliency of such platforms. Due to the dynamic nature …

LinkMirage: How to Anonymize Links in Dynamic Social Systems

Social network based trust relationships present a critical foundation for designing trustworthy systems, such as Sybil defenses, secure routing, and anonymous/censorshipresilient communications. A key issue in the design of such systems, is the revelation of users' trusted social contacts to an adversary-information that is considered sensitive in today's society. In this work, we focus on the challenge of preserving the privacy of users' social contacts, while still enabling the design of social trust based applications. First, we propose LinkMirage, a community detection based algorithm for…

从自旋态到社会共识：意见形成中二聚体构型的Ising方法

From Spin States to Social Consensus: Ising Approach to Dimer Configurations in Opinion Formation

本文基于Trust-Distrust Model（TDM），结合二聚体构型和Ising模型，提出了一种新的意见动力学方法，通过数学模型和数值模拟探索信任与不信任的相互作用及外部刺激对社会意见形成的影响。

Social Networks and Collective Intelligence: A Return to the Agora

Nowadays, acquisition of trustable information is increasingly important in both professional and private contexts. However, establishing what information is trustable and what is not, is a very challenging task. For example, how can information quality be reliably assessed? How can sources? credibility be fairly assessed? How can gatekeeping processes be found trustworthy when filtering out news and deciding ranking and priorities of traditional media? An Internet-based solution to a human-based ancient issue is being studied, and it is called Polidoxa, from Greek "poly", meaning "many" or "s…

Central Server Free Federated Learning over Single-sided Trust Social Networks

Federated learning has become increasingly important for modern machine learning, especially for data privacy-sensitive scenarios. Existing federated learning mostly adopts the central server-based architecture or centralized architecture. However, in many social network scenarios, centralized federated learning is not applicable (e.g., a central agent or server connecting all users may not exist, or the communication cost to the central server is not affordable). In this paper, we consider a generic setting: 1) the central server may not exist, and 2) the social network is unidirectional or o…

SocialCloud: Using Social Networks for Building Distributed Computing Services

In this paper we investigate a new computing paradigm, called SocialCloud, in which computing nodes are governed by social ties driven from a bootstrapping trust-possessing social graph. We investigate how this paradigm differs from existing computing paradigms, such as grid computing and the conventional cloud computing paradigms. We show that incentives to adopt this paradigm are intuitive and natural, and security and trust guarantees provided by it are solid. We propose metrics for measuring the utility and advantage of this computing paradigm, and using real-world social graphs and struct…

Service Discovery and Trust in Mobile Social Network in Proximity

Service-oriented Mobile Social Network in Proximity (MSNP) lets participants establish new social interactions with strangers in public proximity using heterogeneous platforms and devices. Such characteristic faces challenges in discovery latency and trustworthiness. In a public service-oriented MSNP environment, which consists of a large number of participants, a content requester who searches for a particular service provided by other MSNP participants will need to retrieve and process a large number of Service Description Metadata (SDM) files, associated semantic metadata files and identify…

Social Trust as a solution to address sparsity-inherent problems of Recommender systems

Trust has been explored by many researchers in the past as a successful solution for assisting recommender systems. Even though the approach of using a web-of-trust scheme for assisting the recommendation production is well adopted, issues like the sparsity problem have not been explored adequately so far with regard to this. In this work we are proposing and testing a scheme that uses the existing ratings of users to calculate the hypothetical trust that might exist between them. The purpose is to demonstrate how some basic social networking when applied to an existing system can help in alle…

On the Troll-Trust Model for Edge Sign Prediction in Social Networks

In the problem of edge sign prediction, we are given a directed graph (representing a social network), and our task is to predict the binary labels of the edges (i.e., the positive or negative nature of the social relationships). Many successful heuristics for this problem are based on the troll-trust features, estimating at each node the fraction of outgoing and incoming positive/negative edges. We show that these heuristics can be understood, and rigorously analyzed, as approximators to the Bayes optimal classifier for a simple probabilistic model of the edge labels. We then show that the ma…

A decentralized trust-aware collaborative filtering recommender system based on weighted items for social tagging systems

Recommender systems are used with the purpose of suggesting contents and resources to the users in a social network. These systems use ranks or tags each user assign to different resources to predict or make suggestions to users. Lately, social tagging systems, in which users can insert new contents, tag, organize, share, and search for contents are becoming more popular. These systems have a lot of valuable information, but data growth is one of its biggest challenges and this has led to the need for recommender systems that will predict what each user may like or need. One approach to the de…

A blockchain based Secure and Trusted framework for Information Propagation on Online Social Networks

The online social networks facilitate naturally for the users to share information. On these platforms, each user shares information based on his or her interests. The particular information being shared by a user may be legitimate or fake. Sometimes a misinformation, propagated by users and group can create chaos or in some cases, might leads to cases of riots. Nowadays the third party like ALT news and Cobrapost check the information authenticity, but it takes too much time to validate the news. Therefore, a robust and new system is required to check the information authenticity within the n…

Who Will You Share a Ride With: Factors that Influence Trust of Potential Rideshare Partners

Ridesharing can save energy, reduce pollution, and alleviate congestion. Ridesharing systems allow peer-to-peer ride matching through mobile-phone applications. In many systems people have little information about the driver and co-riders. Trust heavily influences the usage of a ridesharing system, however, work in this area is limited. In this paper, we investigate the role of social media in shaping trust and delineate factors that influence the decisions of trust placed on a driver or co-rider. We design a ridesharing system where a rider can see the Instagram profile and 10 recent pictures…

Trust and Believe -- Should We? Evaluating the Trustworthiness of Twitter Users

Social networking and micro-blogging services, such as Twitter, play an important role in sharing digital information. Despite the popularity and usefulness of social media, they are regularly abused by corrupt users. One of these nefarious activities is so-called fake news -- a "virus" that has been spreading rapidly thanks to the hospitable environment provided by social media platforms. The extensive spread of fake news is now becoming a major problem with far-reaching negative repercussions on both individuals and society. Hence, the identification of fake news on social media is a problem…

Exploring Trust-Aware Neighbourhood in Trust-based Recommendation

Traditional Recommender Systems (RS) do not consider any personal user information beyond rating history. Such information, on the other hand, is widely available on social networking sites (Facebook, Twitter). As a result, social networks have recently been used in recommendation systems. In this paper, we propose an efficient method for incorporating social signals into the recommendation process by building a trust network which supplements the users' rating profiles. We first show the effect of different cold-start users types on the Collaborative Filtering (CF) technique in several real-w…

信任与摩擦：协商信息如何流经去中心化社交媒体

Trust and Friction: Negotiating How Information Flows Through Decentralized Social Media

通过对Fediverse 23名用户的半结构化访谈，研究了去中心化社交媒体中社区治理对隐私期望的影响，揭示了信任因素与社区间治理摩擦，并提出参与式决策的设计机会。

Understanding Co-evolution in Large Multi-relational Social Networks

Understanding dynamics of evolution in large social networks is an important problem. In this paper, we characterize evolution in large multi-relational social networks. The proliferation of online media such as Twitter, Facebook, Orkut and MMORPGs\footnote{Massively Multi-player Online Role Playing Games} have created social networking data at an unprecedented scale. Sony's Everquest 2 is one such example. We used game multi-relational networks to reveal the dynamics of evolution in a multi-relational setting by macroscopic study of the game network. Macroscopic analysis involves fragmenting …

探索数据的社会生命：寻找你可信赖的数据

Exploring the Social Life of Data: Finding Data You Can Trust

本文提出数据使用图作为科学数据基础设施新层，结合数据使用证据与多维度信息，在国家数据平台实现原型服务，以解决可信数据查找问题。

Bootstrapping Trust in Online Dating: Social Verification of Online Dating Profiles

Online dating is an increasingly thriving business which boasts billion-dollar revenues and attracts users in the tens of millions. Notwithstanding its popularity, online dating is not impervious to worrisome trust and privacy concerns raised by the disclosure of potentially sensitive data as well as the exposure to self-reported (and thus potentially misrepresented) information. Nonetheless, little research has, thus far, focused on how to enhance privacy and trustworthiness. In this paper, we report on a series of semi-structured interviews involving 20 participants, and show that users are …

Opinion Maximization in Social Trust Networks

Social media sites are now becoming very important platforms for product promotion or marketing campaigns. Therefore, there is broad interest in determining ways to guide a site to react more positively to a product with a limited budget. However, the practical significance of the existing studies on this subject is limited for two reasons. First, most studies have investigated the issue in oversimplified networks in which several important network characteristics are ignored. Second, the opinions of individuals are modeled as bipartite states(e.g., support or not) in numerous studies, however…

Online Social Deception and Its Countermeasures for Trustworthy Cyberspace: A Survey

We are living in an era when online communication over social network services (SNSs) have become an indispensable part of people's everyday lives. As a consequence, online social deception (OSD) in SNSs has emerged as a serious threat in cyberspace, particularly for users vulnerable to such cyberattacks. Cyber attackers have exploited the sophisticated features of SNSs to carry out harmful OSD activities, such as financial fraud, privacy threat, or sexual/labor exploitation. Therefore, it is critical to understand OSD and develop effective countermeasures against OSD for building a trustworth…

存在不信任关系的社会系统中的复杂传染

Complex contagion in social systems with distrust

该研究提出带符号单纯复形上的复杂传染模型，探究信任与不信任对社会传染动力学的影响，揭示了传播比例与连接数的非单调关系及社会平衡对传染的作用机制。

基于网络社区感知和社会信任以抵御女巫攻击的物联网访问控制

An Access Control for IoT Based on Network Community Perception and Social Trust Against Sybil Attacks

提出ELECTRON访问控制机制，利用设备社会相似性划分社区并评估社会信任，以抵御物联网中的女巫攻击，仿真显示其检测率和准确率均超过约90%。

社交网络中竞争性替代方案传播的有限信任研究

Limited-Trust in Diffusion of Competing Alternatives over Social Networks

本研究将有限信任均衡引入社交网络双替代方案传播的博弈论模型，分析其收敛特性并证明可转化为线性阈值模型，仿真验证信任行为能显著提升智能体长期效用。

利用人工智能与社交互动的力量恢复公众民意调查的信任

Leveraging the Power of AI and Social Interactions to Restore Trust in Public Polls

针对众包民意调查数据可信度不足的问题，本文提出基于人工智能的社交互动图结构分析方法，通过模拟不同不诚实行为并在真实数据集实验，在检测不合格参与上取得部分配置准确率超90%的成果，助力恢复公众对民意调查的信任。

人类与大语言模型集合的对抗性社会认识论

Adversarial Social Epistemology for Assemblies of Humans and Large Language Models

研究人类与大语言模型集合在密集互动交流场景中的信息问题，提出对抗性社会认识论，借助语言、机制及基于认知网络的 machinery 来分析、破坏信任并审计纠正信任违规。