Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/205783 
Year of Publication: 
2019
Citation: 
[Journal:] European Research on Management and Business Economics (ERMBE) [ISSN:] 2444-8834 [Volume:] 25 [Issue:] 1 [Publisher:] Elsevier [Place:] Amsterdam [Year:] 2019 [Pages:] 15-22
Publisher: 
Elsevier, Amsterdam
Abstract: 
This research aims to understand how the interactions across several social networks influence the visibility of a luxury brand's most relevant social network which acts as a showcase (Instagram). A data mining approach is proposed for modeling the number of likes on Instagram using 365 posts published in the luxury brand's different social networks between 2015 and 2016. Fifteen features related with the brand's social networks, product characteristics and visibility in external media were prepared and used to feed a support vector machine model which achieved an adequate performance (mean absolute percentage error of 27%). A sensitivity analysis was applied to reveal how each of the fifteen features influenced the Instagram likes. The findings unveiled interactions on the remaining networks hold an influence on Instagram likes, particularly Facebook, with the number of video views, the positive emoticons, and the number of comments and shares explaining around 40% of the model.
Subjects: 
Social media
Social networks
Luxury marketing
Brand image
Data mining
JEL: 
M31
M37
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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