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.
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Communication dans un congrès
Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations - 17th International Conference, IPMU, Jun 2018, Cadiz, Spain
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https://hal.archives-ouvertes.fr/hal-01823784
Contributeur : Arnaud Martin <>
Soumis le : mardi 26 juin 2018 - 14:32:02
Dernière modification le : jeudi 28 juin 2018 - 01:15:47

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

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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〉

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