Skip to Main content Skip to Navigation
Journal articles

Modéliser l'utilisateur pour la diffusion de l'information dans les réseaux sociaux

Abstract : Predicting information diffusion in social networks is a hard task which can lead to interesting applications: recommending relevant information for users, choosing the best entry points in the network for the best diffusion of a given piece of information, etc. We present new models which take into account three main characteristics: the number of neighbors who have disclosed the information, the relevance of the information for each user and the willingness of users to diffuse information. After this presentation, we propose to estimate the parameters of our models and illustrate their behavior through a comparison with standard information diffusion models on a real dataset. We also propose a study of the influence maximization problem associated with these new models.
Complete list of metadatas

Cited literature [31 references]  Display  Hide  Download
Contributor : Eric Gaussier <>
Submitted on : Friday, October 12, 2012 - 3:16:35 PM
Last modification on : Monday, April 20, 2020 - 11:24:01 AM
Document(s) archivé(s) le : Saturday, December 17, 2016 - 12:20:41 AM


Files produced by the author(s)


  • HAL Id : hal-00741416, version 1



Cédric Lagnier, Éric Gaussier, François Kawala. Modéliser l'utilisateur pour la diffusion de l'information dans les réseaux sociaux. Revue des Sciences et Technologies de l'Information - Série ISI : Ingénierie des Systèmes d'Information, Lavoisier, 2012, 17 (3), pp.1-22. ⟨hal-00741416⟩



Record views


Files downloads