Abstract
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. © 2012 Springer-Verlag.
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CITATION STYLE
Leprovost, D., Abrouk, L., Cullot, N., & Gross-Amblard, D. (2012). Temporal semantic centrality for the analysis of communication networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7387 LNCS, pp. 177–184). https://doi.org/10.1007/978-3-642-31753-8_13
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