Social-Based Arcs Weight Assignment in Trust Networks

Marco Buzzanca, Vincenza Carchiolo, Alessandro Longheu, Michele Malgeri, Giuseppe Mangioni

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.