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Least cost influence propagation in (social) networks

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Abstract

Influence maximization problems aim to identify key players in (social) networks and are typically motivated from viral marketing. In this work, we introduce and study the Generalized Least Cost Influence Problem (GLCIP) that generalizes many previously considered problem variants and allows to overcome some of their limitations. A formulation that is based on the concept of activation functions is proposed together with strengthening inequalities. Exact and heuristic solution methods are developed and compared for the new problem. Our computational results also show that our approaches outperform the state-of-the-art on relevant, special cases of the GLCIP.

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Authors and Affiliations

  1. DEI, University of Padua, Padua, Italy

    Matteo Fischetti

  2. Department of Statistics and Operations Research, University of Vienna, Vienna, Austria

    Michael Kahr, Markus Leitner & Mario Ruthmair

  3. DEI, University of Bologna, Bologna, Italy

    Michele Monaci

Authors
  1. Matteo Fischetti
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  2. Michael Kahr
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  3. Markus Leitner
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  4. Michele Monaci
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  5. Mario Ruthmair
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Corresponding author

Correspondence to Matteo Fischetti.

Additional information

Supported by WWTF (Project ICT15-014) and MiUR, Italy (Project PRIN 2015).

A Detailed results

A Detailed results

See Tables 3, 4 and 5.

Table 3 Results on SW instances for \(\varGamma = 0.9\)
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Table 4 Results on SW instances for \(\varGamma = 1\)
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Table 5 Results on SW instances for \(\varGamma = 1.1\)
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Fischetti, M., Kahr, M., Leitner, M. et al. Least cost influence propagation in (social) networks. Math. Program. 170, 293–325 (2018). https://doi.org/10.1007/s10107-018-1288-y

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  • DOI: https://doi.org/10.1007/s10107-018-1288-y

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