Modelling Multimedia Social Network for Topic Ranking

Abstract

In the last decade, the use of Online Social Networks (OSNs) has been rapidly growing allowing people, that lives in different places, to make friends and to share, comment and observe different types of multimedia content, producing a large amount of data showing Big Data features, mainly due to their high change rate, their large volume and intrinsic heterogeneity. In this paper we present a preliminary work concerning the definition of a novel data model for Multimedia Social Networks (MSNs), i.e. networks that combine information on users belonging to one or more social communities together with the multimedia content that is generated and used within a related environment. The proposed model is based on the hypergraph structure and allows us to represent in a simple way all the different kinds of relationships that are typical of a social network, in particular between multimedia content, between users and multimedia content and between users themselves, at the same time supporting several kinds of applications by means of the introduction of several ranking functions. We provide a strategy for mapping the proposed model into an object relational data model, for efficiently storing the related data. In addition, we report an application of the proposed model in a case of study, declined in the biomedical domain, in which the model is exploited for analyzing the spread of a given topic on a social network.