Finding Leaders with Maximum Spread of Influence through Social Networks

Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 20)

Abstract

Social influence is an important phenomenon in social networks. A user is said to be influenced by his/her friends if this user performs the same actions after his/her friends. The problem of influence maximization is to find a small set of users that maximize the spread of influence throughout the social network. Many approaches are proposed to solve this problem under different influence cascade models. In this paper, we propose another solution based on a pruning strategy in which influence boundaries for users are computed to effectively reduce the number of users who have chances to be seeds, thus making the proposed solution efficient. A series of experiments are performed to evaluate the proposed approach and the experiment results reveal that our approach outperforms the previous works.

Keywords

influence maximization social networks independent cascade model 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Tsung An Yeh
    • 1
  • En Tzu Wang
    • 2
  • Arbee L. P. Chen
    • 3
  1. 1.Department of Computer ScienceNational Tsing Hua UniversityHsinchuTaiwan
  2. 2.Cloud Computing Center for Mobile ApplicationsIndustrial Technology Research InstituteHsinchuTaiwan
  3. 3.Department of Computer ScienceNational Chengchi UniversityTaipeiTaiwan

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