The understanding and prediction of information diffusion processes on networks is a major challenge in network theory with many implications in social sciences. Many theoretical advances occurred due to stochastic spreading models. Nevertheless, these stochastic models overlooked the influence of rational decisions on the outcome of the process. For instance, different levels of trust in acqua...

As the amount of information on the web grows, users may find increasing challenges in trusting and sometimes distrusting sources. One possible aid is to maintain a network of trust between sources. In this paper, we propose to model such a network as an intuitionistic fuzzy relation. This allows to elegantly handle together the problem of ignorance, i.e. not knowing whether to trust or not, an...

Semantic Web endeavors have mainly focused on issues pertaining to knowledge representation and ontology design. However, besides understanding information metadata stated by subjects, knowing about their credibility becomes equally crucial. Hence, trust and trust metrics, conceived as computational means to evaluate trust relationships between individuals, come into play. Our major contributio...

Visual analytics combines human and machine abilities to generate new knowledge from data. Within this process, uncertainty often plays an important role in hindering the sensemaking process and analysis tasks. On the machine side, uncertainty builds up from the data source level to the visual output. On the human side, these uncertainties often result in “lack of knowledge or trust” or “overtr...

Dynamic trust federation in grids p. 3 Being trusted in a social network : trust as relational capital p. 19 A requirements-driven trust framework for secure interoperation in open environments p. 33 Normative structures in trust management p. 48 Gathering experience in trust-based interactions p. 62 Multilateral decisions for collaborative defense against unsolicited bulk e-mail p. 77 Generati...

In this work, we explore the benefits of combining clustering and social trust information for Recommender Systems. We demonstrate the performance advantages of traditional clustering algorithms like kMeans and we explore the use of new ones like Affinity Propagation (AP). Contrary to what has been used before, we investigate possible ways that social-oriented information like explicit trust co...

MANET is a self methodized system comprised of mobile nodes without any infrastructure. MANET are at more imperil to attacks since it is dynamic in nature. To define and manage trust in a military MANET, we must cogitate the interface between the communication networks, and severe resource constraints such as computing power, energy, bandwidth, time etc and dynamics. Dynamics include changes in...

Social agents naturally use their social and professional networks to filter information by trustworthiness. In this paper, we present a model of an automated distributed recommendation system on a social network and we investigate how the dynamics of trust among agents affect the performance of the system. Agents search their social network for recommendations on items to be consumed and the p...