Scalable influence maximization for independent cascade model in large-scale social networks

@article{Wang2012ScalableIM,
  title={Scalable influence maximization for independent cascade model in large-scale social networks},
  author={Chi Wang and Wei Chen and Yajun Wang},
  journal={Data Mining and Knowledge Discovery},
  year={2012},
  volume={25},
  pages={545-576}
}
Influence maximization, defined by Kempe et al. (SIGKDD 2003), is the problem of finding a small set of seed nodes in a social network that maximizes the spread of influence under certain influence cascade models. The scalability of influence maximization is a key factor for enabling prevalent viral marketing in large-scale online social networks. Prior solutions, such as the greedy algorithm of Kempe et al. (SIGKDD 2003) and its improvements are slow and not scalable, while other heuristic… CONTINUE READING
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