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Temporal Semantic Centrality for the Analysis of Communication Networks

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.
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https://hal-univ-bourgogne.archives-ouvertes.fr/hal-00803128
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Submitted on : Thursday, March 21, 2013 - 10:48:46 AM
Last modification on : Friday, July 17, 2020 - 2:53:54 PM
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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⟩

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