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Positive Influence Dominating Set in Online Social Networks

  • Feng Wang
  • Erika Camacho
  • Kuai Xu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5573)

Abstract

Online social network has developed significantly in recent years as a medium of communicating, sharing and disseminating information and spreading influence. Most of current research has been on understanding the property of online social network and utilizing it to spread information and ideas. In this paper, we explored the problem of how to utilize online social networks to help alleviate social problems in the physical world, for example, the drinking, smoking, and drug related problems. We proposed a Positive Influence Dominating Set (PIDS) selection algorithm and analyzed its effect on a real online social network data set through simulations. By comparing the size and the average positive degree of PIDS with those of a 1-dominating set, we found that by strategically choosing 26% more people into the PIDS to participate in the intervention program, the average positive degree increases by approximately 3.3 times. In terms of the application, this result implies that by moderately increasing the participation related cost, the probability of positive influencing the whole community through the intervention program is significantly higher. We also discovered that a power law graph has empirically larger dominating sets (both the PIDS and 1-dominating set) than a random graph does.

Keywords

Greedy Algorithm Random Graph Binge Drinker Node Degree Online Social Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Feng Wang
    • 1
  • Erika Camacho
    • 1
  • Kuai Xu
    • 1
  1. 1.Mathematical and Natural SciencesArizona State UniversityPhoenixUSA

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