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On the optimal solution of budgeted influence maximization problem in social networks

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  • Evren Güney

    (Istanbul Arel University)

Abstract

The budgeted influence maximization problem is a challenging stochastic optimization problem defined on social networks. In this problem, the objective is identifying influential individuals who can influence the maximum number of members within a limited budget. In this work an integer program that approximates the original problem is developed and solved by a sample average approximation (SAA) scheme. Experimental analyses indicate that SAA method provides better results than the greedy method without worsening the solution time performance.

Suggested Citation

  • Evren Güney, 2019. "On the optimal solution of budgeted influence maximization problem in social networks," Operational Research, Springer, vol. 19(3), pages 817-831, September.
    • Handle: RePEc:spr:operea:v:19:y:2019:i:3:d:10.1007_s12351-017-0305-x
    DOI: 10.1007/s12351-017-0305-x
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    References listed on IDEAS

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    1. Erjia Yan & Ying Ding, 2009. "Applying centrality measures to impact analysis: A coauthorship network analysis," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(10), pages 2107-2118, October.
    2. Jeff Linderoth & Alexander Shapiro & Stephen Wright, 2006. "The empirical behavior of sampling methods for stochastic programming," Annals of Operations Research, Springer, vol. 142(1), pages 215-241, February.
    3. Fisher, M.L. & Nemhauser, G.L. & Wolsey, L.A., 1978. "An analysis of approximations for maximizing submodular set functions," LIDAM Reprints CORE 341, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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