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An exact method for influence maximization based on deterministic linear threshold model

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Abstract

Influence maximization (IM) is a challenging combinatorial optimization problem on (social) networks given a diffusion model and limited choice for initial seed nodes. In a recent paper by Keskin and Güler (Turkish J of Electrical Eng & Comput Sci 26:3383–3396, 2018) an integer programming formalization of IM using the so-called deterministic linear threshold diffusion model was proposed. In fact, it is a special 0-1 linear program in which the objective is to maximize influence while minimizing the diffusion time. In this paper, by rigorous analysis, we show that the proposed algorithm can get stuck in locally optimal solution or cannot even start on certain input graphs. The identified problems are resolved by introducing further constraints which then leads to a correct algorithmic solution. Benchmarking results are shown to demonstrate the efficiency of the proposed method.

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Acknowledgements

We thank our reviewers for their critical comments and valuable suggestions that highlighted important details and helped us in improving our paper. The research has been supported by the grant TKP2021-NVA-09 of the Ministry for Innovation and Technology, Hungary and by the grant SNN-135643 of the National Research, Development and Innovation Office, Hungary.

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  1. Department of Computational Optimization, University of Szeged, Szeged, Hungary

    Eszter Julianna Csókás & Tamás Vinkó

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  1. Eszter Julianna Csókás
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  2. Tamás Vinkó
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Correspondence to Tamás Vinkó.

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Csókás, E.J., Vinkó, T. An exact method for influence maximization based on deterministic linear threshold model. Cent Eur J Oper Res 31, 269–286 (2023). https://doi.org/10.1007/s10100-022-00807-3

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