Leveraging Users’ Trust and Reputation in Social Networks

In on line communities, where there is a huge number of users that interact under anonymous identities, it has been observed that e-word of mouth is a very powerful influence tool. So far, this technology is well known in on-line marketplaces, such as Amazon, eBay or travel based platforms like Tripadvisor or Booking. However, these trust based approach can be leverage in other scenarios from e-democracy to trust based recommendations on e-health context and e-learning systems. The purpose of this contribution is to analyse the main existing trust and reputation mechanisms and to point out new research challenges that needs to be accomplished with the objective of fully exploiting these systems in real world on-line communities.The authors would like to acknowledge the financial support from the EU project H2020-MSCA-IF-2016- DeciTrustNET-746398 and FEDER funds provided in the Spanish project TIN2016-75850-P

TRHIOS: Trust and reputation in hierarchical and quality-oriented societies

In this paper we present TRHIOS: a Trust and Reputation system for HIerarchical and quality-Oriented Societies. We focus our work on hierarchical medical organizations. The model estimates the reputation of an individual, RTRHIOS, taking into account information from three trust dimensions: the hierarchy of the system; the source of information; and the quality of the results. Besides the concrete reputation value, it is important to know how reliable that value is; for each of the three dimensions we calculate the reliability of the assessed reputations; and aggregating them, the reliability of the reputation of an individual. The modular approach followed in the definition of the different types of reputations provides the system with a high flexibility that allows adapting the model to the peculiarities of each society

Sequential Decision Making with Untrustworthy Service Providers

In this paper, we deal with the sequential decision making problem of agents operating in computational economies, where there is uncertainty regarding the trustworthiness of service providers populating the environment. Specifically, we propose a generic Bayesian trust model, and formulate the optimal Bayesian solution to the exploration-exploitation problem facing the agents when repeatedly interacting with others in such environments. We then present a computationally tractable Bayesian reinforcement learning algorithm to approximate that solution by taking into account the expected value of perfect information of an agent's actions. Our algorithm is shown to dramatically outperform all previous finalists of the international Agent Reputation and Trust (ART) competition, including the winner from both years the competition has been run

Legal security and credibility in agent based virtual enterprises

Recent trends in the field of Artificial Intelligence, brought along new ways of formalizing and expressing wills and declarations. Its application to Virtual Enterprises requires an analysis of the interactions among agents, frameworks and users, as well as technical and legal analysis, in order to discover the rules to be applied, to solve a particular problem under a prospective scenario. Credibility, trust and security issues must be taken under consideration, especially concerning authenticity, confidentiality, integrity and non-repudiation. In order to increase the use of agents in Virtual Enterprises, besides the analysis and research of legal solutions in the commercial arena, it is essential to assure that agents will meet requirements of credibility and trust, insuring a transparent and secure way for their commercial acting, now capable of generating legal relations. This paper shows how to construct a dynamic virtual world of complex and interacting entities or agents, in which fitness is judged by a quality of information criterion

AN AUTHENTICATING STRATEGY BY USERS PATTERN

The part-based access control divides the operation of authorization into role-permission furthermore to user-role assignment. The daily rising assets of understanding that's available online makes effective means of data access a crucial part of understanding systems. We introduce computational type of dynamic trust for user approval, that's rooted in findings from social science. Completely different from established types of computational trust, our suggested system differentiates getting belief in belief within integrity from that in competence in many contexts for subjectivity in assessment of particular trustee by way of several trusters. The suggested representation isn't limited towards getting belief in belief since the majority of the computational methods. The suggested representation 's the reason various trust particularly, it differentiate getting belief in belief within integrity from that in proficiency which model views subjectivity of trust ratings by way of various entities, and initiates a method to eliminate the outcomes of subjectivity within status aggregation. This trust model differentiates integrity trust from competence trust

Trust reality-mining: evidencing the role of friendship for trust diffusion

Value sensitive design is driven by the motivation of making social and moral values central to the development of ICT systems. Among the most challenging concerns when imparting shared values like accountability, transparency, liberty, fairness and trust into information technology are reliable and comprehensive formal and computational models of those values. This paper, educated by trust theories and models from cognitive science, social sciences and artificial intelligence, proposes a novel stochastic computational model of trust, encapsulating abstractions of human cognitive capabilities and empirically evidenced social interaction patterns. Qualitative and quantitative features of trust are identified, upon which our formal model is phrased. Reality mining methods are used to validate the model based on a real life community dataset. We analyze the time-varying dynamics of the interaction and communication patterns of the community, consider varying types of relationships as well as their symmetry. Social network data analysis shows that our model better fits the evolved friendships compared to a well designed synthetic trust model, which is used as the baseline.</p

A review on trust propagation and opinion dynamics in social networks and group decision making frameworks

On-line platforms foster the communication capabilities of the Internet to develop large- scale influence networks in which the quality of the interactions can be evaluated based on trust and reputation. So far, this technology is well known for building trust and harness- ing cooperation in on-line marketplaces, such as Amazon (www.amazon.com) and eBay (www.ebay.es). However, these mechanisms are poised to have a broader impact on a wide range of scenarios, from large scale decision making procedures, such as the ones implied in e-democracy, to trust based recommendations on e-health context or influence and per- formance assessment in e-marketing and e-learning systems. This contribution surveys the progress in understanding the new possibilities and challenges that trust and reputation systems pose. To do so, it discusses trust, reputation and influence which are important measures in networked based communication mechanisms to support the worthiness of information, products, services opinions and recommendations. The existent mechanisms to estimate and propagate trust and reputation, in distributed networked scenarios, and how these measures can be integrated in decision making to reach consensus among the agents are analysed. Furthermore, it also provides an overview of the relevant work in opinion dynamics and influence assessment, as part of social networks. Finally, it identi- fies challenges and research opportunities on how the so called trust based network can be leveraged as an influence measure to foster decision making processes and recommen- dation mechanisms in complex social networks scenarios with uncertain knowledge, like the mentioned in e-health and e-marketing frameworks.The authors acknowledge the financial support from the EU project H2020-MSCA-IF-2016-DeciTrustNET-746398, FEDER funds provided in the National Spanish project TIN2016-75850-P , and the support of the RUDN University Program 5-100 (Russian Federation)

A metrology-based approach for measuring the social dimension of cognitive trust in collaborative networks

This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s10111-018-0483-1[Abstract]: This paper addresses the measurement of the social dimension of cognitive trust in collaborative networks. Trust indicators are typically measured and combined in literature in order to calculate partners’ trustworthiness. When expressing the result of a measurement, some quantitative indication of the quality of the result—the uncertainty of measurement—should be given. However, currently this is not taken into account for the measurement of the social dimension of cognitive trust in collaborative networks. In view of this, an innovative metrology-based approach for the measurement of social cognitive trust indicators in collaborative networks is presented. Thus, a measurement result is always accompanied by its uncertainty of measurement, as well as by information traditionally used to properly interpret the results: the sample size, and the standard deviation of the sample

Gossip for social control in natural and artificial societies

In this work we propose a theory of gossip as a means for social control. Exercising social control roughly means to isolate and to punish cheaters. However, punishment is costly and it inevitably implies the problem of second-order cooperation. Moving from a cognitive model of gossip, we report data from ethnographic studies and agent-based simulations to support our claim that gossip reduces the costs of social control without lowering its efficacy