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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Romão, M. T., Moro, S., Rita, P. & Ramos, P. (2019). Leveraging a luxury fashion brand through social media. European Research on Management and Business Economics. 25 (1), 15-22
Exportar Referência (IEEE)
M. T. Romão et al.,  "Leveraging a luxury fashion brand through social media", in European Research on Management and Business Economics, vol. 25, no. 1, pp. 15-22, 2019
Exportar BibTeX
@article{romão2019_1732205061243,
	author = "Romão, M. T. and Moro, S. and Rita, P. and Ramos, P.",
	title = "Leveraging a luxury fashion brand through social media",
	journal = "European Research on Management and Business Economics",
	year = "2019",
	volume = "25",
	number = "1",
	doi = "10.1016/j.iedeen.2018.10.002",
	pages = "15-22",
	url = "https://www.sciencedirect.com/science/article/pii/S2444883418301104"
}
Exportar RIS
TY  - JOUR
TI  - Leveraging a luxury fashion brand through social media
T2  - European Research on Management and Business Economics
VL  - 25
IS  - 1
AU  - Romão, M. T.
AU  - Moro, S.
AU  - Rita, P.
AU  - Ramos, P.
PY  - 2019
SP  - 15-22
SN  - 2444-8834
DO  - 10.1016/j.iedeen.2018.10.002
UR  - https://www.sciencedirect.com/science/article/pii/S2444883418301104
AB  - 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.
ER  -