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Prédictions d'activité dans les réseaux sociaux en ligne

Abstract : Online Platforms dedicated to social networking host new social phenomenons. Thus several keywords may suddenly take an unprecedented importance, reflecting the number of dis- cussions they have raised within a short time period. Such bursts in topic discussions are usually referred to as buzz events. We address in this paper the problem of predicting the activity volume associated to a given keyword without a priori knowledge on the underlying social network. To do so, we propose to define social netowrk on a content-centric way. Our approach is evaluated at "industrial scale" on two different social networks: Twitter, a platform with extremely fast dynamics (Kwak et al., 2010), and Tom's Hardware, a worldwide forum network focusing on new technology. The experiments conducted reveal that it is possible to predict activity volume associated to a keyword in social media with high accuracy.
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Contributor : François Kawala <>
Submitted on : Tuesday, November 12, 2013 - 3:35:42 PM
Last modification on : Friday, November 20, 2020 - 2:54:16 PM
Long-term archiving on: : Thursday, February 13, 2014 - 4:21:37 AM


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  • HAL Id : hal-00881395, version 1




François Kawala, Ahlame Douzal-Chouakria, Eric Gaussier, Eustache Dimert. Prédictions d'activité dans les réseaux sociaux en ligne. 4ième conférence sur les modèles et l'analyse des réseaux : Approches mathématiques et informatiques, Oct 2013, France. pp.16. ⟨hal-00881395⟩



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