Hybrid modeling approach for contextualized community detection in multilayer social network: emergency management case study

Within multilayer social networks, finding relevant communities for each specific situation has been a challenging task. Thus, modeling these social networks is the key issue for the process of contextualized community detection. However, traditional formalisms for representing multilayer social networks suffer from the lack of semantics. In the scope of this paper, we propose a hybrid modeling approach to represent participants and community detection context in multilayer social network. This approach combines a semantically rich description of social data (Ontology-based model) with a powerful mathematical abstraction (Graph-based model). Furthermore, we present a modeling scenario in the field of emergency management to illustrate how the proposed model can be used to contextualize community detection within a real social network. Finally, a comparison with another modeling approach is given in order to evaluate the proposed model performance.