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A Memetic Algorithm for Maximizing Earned Attention in Social Media

Author

Listed:
  • Pedro Godinho

    (EM - EMLyon Business School)

  • Luiz Moutinho
  • Margherita Pagani

Abstract

Purpose The purpose of this study is to propose a measure for earned attention and a model and procedure for the maximization of earned attention by a company over a period of time. Design/methodology/approach Utility functions are used as the base of the earned attention measure. An evolutionary algorithm - a memetic algorithm - is applied to identifying strategies that aim to maximize earned attention. Computational analysis is performed resorting to simulated data, and the memetic algorithm is assessed through the comparison with a standard steepest ascent heuristic. Findings The shape of the utility functions considered in the model has a huge impact on the characteristics of the best strategies, with actions focused on increasing a single variable being preferred in case of constant marginal utility, and more balanced strategies having a better performance in the case of decreasing marginal utility. The memetic algorithm is shown to have a much better performance that the steepest ascent procedure. Originality/value A new mathematical model for earned attention is proposed, and an approach that has few applications in business problems - a memetic algorithm - is tailored to the model and applied to identify solutions.

Suggested Citation

  • Pedro Godinho & Luiz Moutinho & Margherita Pagani, 2017. "A Memetic Algorithm for Maximizing Earned Attention in Social Media," Post-Print hal-02313436, HAL.
    • Handle: RePEc:hal:journl:hal-02313436
    as

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