Towards Contextualizing Community Detection in Dynamic Social Networks - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2017

Towards Contextualizing Community Detection in Dynamic Social Networks

Résumé

With the growing number of users and the huge amount of information in dynamic social networks, contextualizing community detection has been a challenging task. Thus, modeling these social networks is a key issue for the process of contextualized community detection. In this work, we propose a temporal multiplex information graph-based model to represent dynamic social networks: we consider simultaneously the social network dynamicity, its structure (different social connections) and various members’ profiles so as to calculate similarities between “nodes” in each specific context. Finally a comparative study on a real social network shows the efficiency of our approach and illustrates practical uses.
Fichier principal
Vignette du fichier
rebhi_19072.pdf (508.2 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01887896 , version 1 (04-10-2018)

Identifiants

  • HAL Id : hal-01887896 , version 1
  • OATAO : 19072

Citer

Wala Rebhi, Nesrine Ben Yahia, Narjès Bellamine Ben Saoud, Chihab Hanachi. Towards Contextualizing Community Detection in Dynamic Social Networks. 10th International and Interdisciplinary Conference on Modeling and Using Context (CONTEXT 2017), Jun 2017, Paris, France. pp. 324-336. ⟨hal-01887896⟩
58 Consultations
70 Téléchargements

Partager

Gmail Facebook X LinkedIn More