Skip to Main content Skip to Navigation
Theses

Une approche de détection des communautés d'intérêt dans les réseaux sociaux : application à la génération d'IHM personnalisées

Abstract : Nowadays, Social Networks are ubiquitous in all aspects of life. A fundamental feature of these networks is the connection between users. These are gradually engaged to contribute by adding their own content. So Social Networks also integrate user creations ; which encourages researchers to revisit the methods of their analysis. This field has now led to a great deal of research in recent years. One of the main problems is the detection of communities. The research presented in this thesis is positioned in the themes of the semantic analysis of Social Networks and the generation of personalized interactive applications. This thesis proposes an approach for the detection of communities of interest in Social Networks. This approach models social data in the form of a social user profile represented by an ontology. It implements a method for the Sentiment Analysis based on the phenomena of social influence and homophily. The detected communities are exploited in the generation of personalized interactive applications. This generation is based on an approach of type MDA, independent of the application domain. In addition, this manuscript reports an evaluation of our proposals on data from Real Social Networks.
Document type :
Theses
Complete list of metadatas

Cited literature [160 references]  Display  Hide  Download

https://tel.archives-ouvertes.fr/tel-01997693
Contributor : Abes Star :  Contact
Submitted on : Tuesday, January 29, 2019 - 11:04:26 AM
Last modification on : Friday, October 23, 2020 - 4:40:52 PM
Long-term archiving on: : Tuesday, April 30, 2019 - 2:16:54 PM

File

Chouchani_Nadia2.pdf
Version validated by the jury (STAR)

Identifiers

  • HAL Id : tel-01997693, version 1

Collections

Citation

Nadia Chouchani. Une approche de détection des communautés d'intérêt dans les réseaux sociaux : application à la génération d'IHM personnalisées. Web. Université de Valenciennes et du Hainaut-Cambresis, 2018. Français. ⟨NNT : 2018VALE0048⟩. ⟨tel-01997693⟩

Share

Metrics

Record views

287

Files downloads

1667