Maximizing the Coverage of Information Propagation in Social Networks

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Author(s)

  • Zhefeng Wang
  • Enhong Chen
  • Qi Liu
  • Yong Ge
  • Biao Chang

Detail(s)

Original languageEnglish
Title of host publicationProceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI 2015)
EditorsQiang Yang, Michael Wooldridge
Place of PublicationPalo Alto, California USA
PublisherAAAI Press/International Joint Conferences on Artificial Intelligence
Pages2104-2110
ISBN (Print)9781577357384
Publication statusPublished - Jul 2015
Externally publishedYes

Publication series

NameInternational Joint Conference on Artificial Intelligence (IJCAI)
ISSN (Print)1045-0823

Conference

Title24th International Joint Conference on Artificial Intelligence, IJCAI 2015
PlaceArgentina
CityBuenos Aires
Period25 - 31 July 2015

Abstract

Social networks, due to their popularity, have been studied extensively these years. A rich body of these studies is related to influence maximization, which aims to select a set of seed nodes for maximizing the expected number of active nodes at the end of the process. However, the set of active nodes can not fully represent the true coverage of information propagation. A node may be informed of the information when any of its neighbours become active and try to activate it, though this node (namely informed node) is still inactive. Therefore, we need to consider both active nodes and informed nodes that are aware of the information when we study the coverage of information propagation in a network. Along this line, in this paper we propose a new problem called Information Coverage Maximization that aims to maximize the expected number of both active nodes and informed ones. After we prove that this problem is NP-hard and submodular in the independent cascade model, we design two algorithms to solve it. Extensive experiments on three real-world data sets demonstrate the performance of the proposed algorithms.

Citation Format(s)

Maximizing the Coverage of Information Propagation in Social Networks. / Wang, Zhefeng; Chen, Enhong; Liu, Qi et al.

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI 2015). ed. / Qiang Yang; Michael Wooldridge. Palo Alto, California USA : AAAI Press/International Joint Conferences on Artificial Intelligence, 2015. p. 2104-2110 (International Joint Conference on Artificial Intelligence (IJCAI)).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review