On influence maximization to target users in the presence of multiple acceptances

Chien Wei Chang, Mi Yen Yeh, Kun Ta Chuang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

In this paper, we study a novel problem of influence maximization in social networks: Given a period of promotion time and a set of target users, each of which can be activated by its neighbors multiple times, we aim at maximizing the total acceptance frequency of these target users by initially selecting k most influential seeds. The promising viral marketing paradigm on social network is different from the current research in two main aspects. First, instead of maximizing the message spread over the entire social network, we focus on the target market since the business vendors almost specify the target users before designing its marketing strategy. Second, the status of a user is no longer a binary indicator representing either active or inactive. In the new model the user status turns to be an integer value reflecting the amount of influences delivered to that user. In this paper, we prove the NP-hard nature of this challenging problem.

Original languageEnglish
Title of host publicationProceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
EditorsJian Pei, Jie Tang, Fabrizio Silvestri
PublisherAssociation for Computing Machinery, Inc
Pages1592-1593
Number of pages2
ISBN (Electronic)9781450338547
DOIs
Publication statusPublished - 2015 Aug 25
EventIEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015 - Paris, France
Duration: 2015 Aug 252015 Aug 28

Publication series

NameProceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015

Other

OtherIEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
CountryFrance
CityParis
Period15-08-2515-08-28

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Networks and Communications

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  • Cite this

    Chang, C. W., Yeh, M. Y., & Chuang, K. T. (2015). On influence maximization to target users in the presence of multiple acceptances. In J. Pei, J. Tang, & F. Silvestri (Eds.), Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015 (pp. 1592-1593). (Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015). Association for Computing Machinery, Inc. https://doi.org/10.1145/2808797.2809349