Abstract Graph Neural Networks (GNNs) have been widely used to learn representations on
graphs and tackle many real-world problems from a wide range of domains. In this paper we …

IoT applications has some characteristics that set it apart from other fields mainly due to the
multitude of different types of sensors producing data. In monitoring applications, data …

The exploitation of trust in virtual environments, on-line services, intelligent pervasive
environments and many other scenarios still deserve researchers' interest. In this work we …

In network science, there is often the need to sort the graph nodes. While the sorting strategy
may be different, in general sorting is performed by exploiting the network structure. In …

Online social networks are overwhelmed with information spreading, phenomena whose
underlying mechanisms require deeper analysis. In this paper, we introduce the direct …

Misinformation spreading over online social networks is becoming more and more critical
due to the huge amount of information sources whose reliability is hard to establish; …

There is a dearth of research on why public trust in government rises and falls over time
following online collective behaviours. For the problem of dynamic process and micro-macro …

Ranking is a widely used technique to classify nodes in networks according to their
relevance. Increasing one's rank is a desiderable feature in almost any context; several …

As social networks continue to expand, an increasing number of people prefer to use social
networks to post their comments and express their feelings, and as a result, the information …

Ordering nodes by rank is a benchmark used in several contexts, from recommendation-
based trust networks to e-commerce, search engines and websites ranking. In these …