Temporal Semantic Centrality for the Analysis of Communication Networks

Damien Leprovost (1) , Lylia Abrouk (1) , Nadine Cullot (1) , David Gross-Amblard (2)

1 Le2i - Laboratoire Electronique, Informatique et Image [UMR6306]
2 IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires

Understanding communication structures in huge and versatile online communities becomes a major issue. In this paper we propose a new metric, the Semantic Propagation Probability, that characterizes the user's ability to propagate a concept to other users, in a rapid and focused way. The message semantics is analyzed according to a given ontology. We use this metric to obtain the Temporal Semantic Centrality of a user in the community. We propose and evaluate an efficient implementation of this metric, using real-life ontologies and data sets.

Mots clés: semantic analysis; centrality; community; communication network; ontology

Domaines: Web

Damien Leprovost, Lylia Abrouk, Nadine Cullot, David Gross-Amblard. Temporal Semantic Centrality for the Analysis of Communication Networks. International Conference of Web Engineering, Jul 2012, Berlin, Germany. pp.177-184, ⟨10.1007/978-3-642-31753-8_13⟩. ⟨hal-00803128⟩