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Learning Information Spread in Content Networks
Cédric Lagnier, Ludovic Denoyer, Sylvain Lamprier, Simon Bourigault, patrick gallinari
Dec 24, 2013 (modified: Dec 24, 2013)ICLR 2014 workshop submissionreaders: everyone
Decision:submitted, no decision
Abstract:We introduce a model for predicting the diffusion of content information on social media. When propagation is usually modeled on discrete graph structures, we introduce here a continuous diffusion model, where nodes in a diffusion cascade are projected onto a latent space with the property that their proximity in this space reflects the temporal diffusion process. We focus on the task of predicting contaminated users for an initial initial information source and provide preliminary results on differents datasets.
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