TY  - JOUR
AB  - 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 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.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.
VL  - 12
IS  - 3
SN  - 1746-5664
DO  - 10.1108/JM2-10-2015-0078
UR  - https://doi.org/10.1108/JM2-10-2015-0078
AU  - Godinho Pedro
AU  - Moutinho Luiz
AU  - Pagani Margherita
PY  - 2017
Y1  - 2017/01/01
TI  - A memetic algorithm for maximizing earned attention in social media
T2  - Journal of Modelling in Management
PB  - Emerald Publishing Limited
SP  - 364
EP  - 385
Y2  - 2024/04/23
ER  -