Independence of Sources in Social Networks

Abstract : Online social networks are more and more studied. The links between users of a social network are important and have to be well qualified in order to detect communities and find influencers for example. In this paper, we present an approach based on the theory of belief functions to estimate the degrees of cognitive independence between users in a social network. We experiment the proposed method on a large amount of data gathered from the Twitter social network.
Document type :
Conference papers
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01823784
Contributor : Arnaud Martin <>
Submitted on : Tuesday, June 26, 2018 - 2:32:02 PM
Last modification on : Thursday, February 7, 2019 - 4:45:47 PM
Document(s) archivé(s) le : Wednesday, September 26, 2018 - 10:11:57 PM

Files

IPMU18.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01823784, version 1
  • ARXIV : 1806.09959

Citation

Manel Chehibi, Mouna Chebbah, Arnaud Martin. Independence of Sources in Social Networks. Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations - 17th International Conference, IPMU, Jun 2018, Cadiz, Spain. ⟨hal-01823784⟩

Share

Metrics

Record views

113

Files downloads

52