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A memetic algorithm for maximizing earned attention in social media

A memetic algorithm for maximizing earned attention in social media PurposeThe 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/approachUtility functions are used as the base of the earned attention measure. An evolutionary algorithm – a memetic algorithm – is applied to identify 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.FindingsThe 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/valueA 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Modelling in Management Emerald Publishing

A memetic algorithm for maximizing earned attention in social media

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References (56)

Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1746-5664
DOI
10.1108/JM2-10-2015-0078
Publisher site
See Article on Publisher Site

Abstract

PurposeThe 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/approachUtility functions are used as the base of the earned attention measure. An evolutionary algorithm – a memetic algorithm – is applied to identify 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.FindingsThe 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/valueA 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.

Journal

Journal of Modelling in ManagementEmerald Publishing

Published: Aug 14, 2017

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