Virtual interaction with strangers often makes use of underlying trust networks. Usually, existing proposals address the evaluation of global (unique) trust for a given node within the network. In this paper we discuss about how to assess the local (direct) trust a node receives from each of his neighbors. Our proposal is social-based and takes into account both positive and negative experiences as well as the history of past feedbacks, ensuring good stability also when a node receives hundreds of positive feedbacks briefly followed by few negative feedbacks. In order to highlight the stability of this approach we performed several simulations with different networks.
Social-based arcs weight assignment in trust networks
CARCHIOLO, Vincenza;MALGERI, Michele Giuseppe;
2016-01-01
Abstract
Virtual interaction with strangers often makes use of underlying trust networks. Usually, existing proposals address the evaluation of global (unique) trust for a given node within the network. In this paper we discuss about how to assess the local (direct) trust a node receives from each of his neighbors. Our proposal is social-based and takes into account both positive and negative experiences as well as the history of past feedbacks, ensuring good stability also when a node receives hundreds of positive feedbacks briefly followed by few negative feedbacks. In order to highlight the stability of this approach we performed several simulations with different networks.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
