Signed-PageRank: An Efficient Influence Maximization Framework for Signed Social Networks

  title={Signed-PageRank: An Efficient Influence Maximization Framework for Signed Social Networks},
  author={Xiaoyan Yin and Xiao Hu and Yanjiao Chen and Xu Yuan and Baochun Li},
  journal={IEEE Transactions on Knowledge and Data Engineering},
Influence maximization in social networks is of great importance for marketing new products. Signed social networks with both positive (friends) and negative (foes) relationships pose new challenges and opportunities, since the influence of negative relationships can be leveraged to promote information propagation. In this paper, we study the problem of influence maximization for advertisement recommendation in signed social networks. We propose a new framework to characterize the information… 
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Influence Maximization on Signed Social Networks with Integrated PageRank
  • Shubo Chen, Kejing He
  • Computer Science
    2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity)
  • 2015
This paper integrates the PageRank on signed social networks and uses the integrated PageRank to study influence maximization in OSNs with both friend and hostile relations which are respected as positive edges and negative edges on signed networks.
Polarity Related Influence Maximization in Signed Social Networks
The polarity-related influence maximization (PRIM) problem which aims to find the seed node set with maximum positive influence or maximum negative influence in signed social networks is proposed and a greedy algorithm can be used to achieve an approximation ratio of 1-1/e for solving the PRIM problem insigned social networks.
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