A Memetic Algorithm for Maximizing Earned Attention in Social Media

Pedro Godinho (), Luiz Moutinho and Margherita Pagani ()
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Luiz Moutinho: DCU - Dublin City University [Dublin]
Margherita Pagani: EM - EMLyon Business School

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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.

Keywords: marketing; Decision making; Algorithms; Modelling (search for similar items in EconPapers)
Date: 2017-09-01
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Published in Journal of Modelling in Management, 2017, 12 (3), 364-385 p. ⟨10.1108/JM2-10-2015-0078⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-02313436

DOI: 10.1108/JM2-10-2015-0078

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