Learning the information diffusion probabilities by using variance regularized EM algorithm

@article{Li2014LearningTI,
  title={Learning the information diffusion probabilities by using variance regularized EM algorithm},
  author={Hai-Guang Li and Tianyu Cao and Zhao Li},
  journal={2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)},
  year={2014},
  pages={273-280}
}
In this paper we address the problem of learning the information diffusion probabilities when there is no sufficient data of information diffusion. By observing the information diffusion behavior on the popular social network web-site Twitter, we find that the evidence of information diffusion is extremely sparse. Less than one percent of tweets are retweeted, which is considered as the most important form of information diffusion evidence on Twitter. Previous research on predicting information… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-10 of 16 references

Similar Papers

Loading similar papers…