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Extracting insights from big social data for smarter tourism destination management

Gianluca Solazzo (Department of Engineering for Innovation, University of Salento, Lecce, Italy)
Ylenia Maruccia (Department of Engineering for Innovation, University of Salento, Lecce, Italy)
Gianluca Lorenzo (Department of Engineering for Innovation, University of Salento, Lecce, Italy)
Valentina Ndou (Department of Engineering for Innovation, University of Salento, Lecce, Italy)
Pasquale Del Vecchio (Department of Engineering for Innovation, University of Salento, Lecce, Italy)
Gianluca Elia (Department of Engineering for Innovation, University of Salento, Lecce, Italy)

Measuring Business Excellence

ISSN: 1368-3047

Article publication date: 20 May 2021

Issue publication date: 21 February 2022

668

Abstract

Purpose

This paper aims to highlight how big social data (BSD) and analytics exploitation may help destination management organisations (DMOs) to understand tourist behaviours and destination experiences and images. Gathering data from two different sources, Flickr and Twitter, textual and visual contents are used to perform different analytics tasks to generate insights on tourist behaviour and the affective aspects of the destination image.

Design/methodology/approach

This work adopts a method based on a multimodal approach on BSD and analytics, considering multiple BSD sources, different analytics techniques on heterogeneous data types, to obtain complementary results on the Salento region (Italy) case study.

Findings

Results show that the generated insights allow DMOs to acquire new knowledge about discovery of unknown clusters of points of interest, identify trends and seasonal patterns of tourist demand, monitor topic and sentiment and identify attractive places. DMOs can exploit insights to address its needs in terms of decision support for the management and development of the destination, the enhancement of destination attractiveness, the shaping of new marketing and communication strategies and the planning of tourist demand within the destination.

Originality/value

The originality of this work is in the use of BSD and analytics techniques for giving DMOs specific insights on a destination in a deep and wide fashion. Collected data are used with a multimodal analytic approach to build tourist characteristics, images, attitudes and preferred destination attributes, which represent for DMOs a unique mean for problem-solving, decision-making, innovation and prediction.

Keywords

Acknowledgements

The approach described in this paper is adopted in the NEST (Networking for smart tourism development, INTERREG-IPA CBC Italia-Albania-Montenegro – Project n. 96-1· call for standard project – co-financed by the European Union under the Instrument for Pre-Accession Assistance (IPA II)) project, which aims at enabling a cross-border cooperation between Albania, Italy and Montenegro, in order to create a common branding of the Adriatic-Ionian area as a smart tourism destination at a macro regional level and to develop common tourist routes and products.

Citation

Solazzo, G., Maruccia, Y., Lorenzo, G., Ndou, V., Del Vecchio, P. and Elia, G. (2022), "Extracting insights from big social data for smarter tourism destination management", Measuring Business Excellence, Vol. 26 No. 1, pp. 122-140. https://doi.org/10.1108/MBE-11-2020-0156

Publisher

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Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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