Modeling user and topic interactions in social networks using Hawkes processes
Journal Title: EAI Endorsed Transactions on Cloud Systems - Year 2015, Vol 1, Issue 3
Abstract
We present in this paper a framework to model information diffusion in social networks based on linear multivariate Hawkes processes. Our model exploits the effective broadcasting times of information by users, which guarantees a more realistic view of the information diffusion process. The proposed model takes into consideration not only interactions between users but also interactions between topics, which provides a deeper analysis of influences in social networks. We provide an estimation algorithm based on nonnegative matrix factorization techniques, which together with a dimensionality reduction argument is able to discover, in addition, the latent community structure of the social network. We also provide several numerical results of our method.
Authors and Affiliations
Julio Cesar Louzada Pinto, Tijani Chahed
Keywords
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- EP ID EP45562
- DOI http://dx.doi.org/10.4108/icst.valuetools.2014.258186
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