Learning content–social influential features for influence analysis

@article{Zhao2016LearningCI,
  title={Learning content–social influential features for influence analysis},
  author={Na Zhao and Hanwang Zhang and Meng Wang and Richang Hong and Tat-Seng Chua},
  journal={International Journal of Multimedia Information Retrieval},
  year={2016},
  volume={5},
  pages={137-149}
}
We address how to measure the information propagation probability between users given certain contents. In sharp contrast to existing works that oversimplify the propagation model as predefined distributions, our approach fundamentally attempts to answer why users are influenced (e.g., by content or relations) and whether the corresponding influential features (e.g., hidden factors) can be inferred from the propagation in the entire network. In particular, we propose a novel method to deeply… CONTINUE READING

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