Optimization Problems in Online Social Networks

  • Jie Wang
  • You Li
  • Benyuan Liu
  • Guanling Chen
  • Jun-Hong Cui
Reference work entry

Abstract

This chapter introduces and elaborates four major issues in online social networks. First, it describes the problem of maximizing the spread of influence in social networks and the problem of computing the spread. It shows that the problem of maximizing influence is NP-hard and the problem of computing the spread is #P-hard. It also presents a number of algorithms for finding approximations to the problem of influence maximization. Second, it describes the problem of detecting network communities and presents a few heuristic algorithms. In particular, it introduces and elaborates a new algorithm that uses random walkers to find communities effectively and efficiently. Third, it discusses how to collect data from online social networks and it presents the recent work on data collection. Forth, it discusses how to measure influence (friendship) in online social networks and elaborates the recent results on the location-based three-layer friendship modeling.

Keywords

Marketing Photography 

Notes

Acknowledgements

The author “Jie Wang” was supported in part by the NSF under grants CNS-0958477 and CNS-1018422. The author “You Li” was supported in part by the NSF under grant CNS-1018422. The author “Jun-Hong Cui” was supported in part by the US Department of Education under Grants P200A100141 and P200A090342. The author “Benyuan Liu” was supported in part by the NSF under grant CNS-0953620. The author “Guanling Chen” was supported in part by the NSF under grant IIS-0917112.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Jie Wang
    • 1
  • You Li
    • 1
  • Benyuan Liu
    • 1
  • Guanling Chen
    • 1
  • Jun-Hong Cui
    • 2
  1. 1.Department of Computer ScienceUniversity of MassachusettsLowellUSA
  2. 2.Department of Computer Science and EngineeringUniversity of ConnecticutStorrsUSA

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