A MODEL FOR OPTIMISING EARNED ATTENTION IN SOCIAL MEDIA BASED ON A MEMETIC ALGORITHM

Pedro Godinho (), Luiz Moutinho and Manuela Silva

Chapter 17 in Quantitative Modelling in Marketing and Management, 2015, pp 423-456 from World Scientific Publishing Co. Pte. Ltd.

Abstract: With the advent of social media in our lives and the transformation of consumer behaviour through the impact of the internet technology, online brand–human interactions are crucial in the consumer decision-making process, as well as on corporate performance. In this research study, we have developed a model to predict brand engagement as measured in terms of the amount of earned attention by the brand from the consumer. The exogenous variables of the model comprise parameters related to online traffic, flow of consumer-initiated brand commentaries as measured by three different time frames and the quantity of brand mentions. To test and validate the research model, we have applied a Memetic Algorithm (MA) which is well tailored to the phenomenon of propagation and social contagion. In order to assess this evolutionary algorithm, we have used two alternative local search methods—a Specific Local Search Procedure (SLSP) and the Steepest Ascent (SA) heuristic.We have found that the MA outperforms both local search-based methods, and the SLSP outperforms the SA.

Keywords: Quantitative Analysis; Modeling; Marketing Management; Statistical Modelling; Computer Modelling; Memetic Algorithm; Structural Equation Modelling; Artificial Neural Networks (search for similar items in EconPapers)
Date: 2015
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