Towards Semantic Digital Twins for Social Networks

Abstract

This position paper proposes a platform for the creation of digital twins for social networks as semantic digital twins for people. These are mainly aimed at simulating human behavior from a cognitive point of view. The proposal relies on a semantic data infrastructure aimed at analytical purposes, which is directly fed with real data from social networks. Summarized data and data generation methods are then combined to produce new data streams according to the analyst requirements. All these data are stored in a dynamic knowledge graph, which plays a central role in the design of the digital twins. First experiments will be conducted on two scenarios where semantic data is already available, namely: Tourism and Fashion.