Identification of Mobility Patterns of Clusters of City Visitors: An Application of Artificial Intelligence Techniques to Social Media Data

In order to enhance tourists’ experiences, Destination Management Organizations need to know who their tourists are, their travel preferences, and their flows around the destination. The study develops a methodology that, through the application of Artificial Intelligence techniques to social media...

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Bibliographic Details
Main Authors: Jonathan Ayebakuro Orama, Assumpció Huertas, Joan Borràs, Antonio Moreno, Salvador Anton Clavé
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/12/12/5834
Description
Summary:In order to enhance tourists’ experiences, Destination Management Organizations need to know who their tourists are, their travel preferences, and their flows around the destination. The study develops a methodology that, through the application of Artificial Intelligence techniques to social media data, creates clusters of tourists according to their mobility and visiting preferences at the destination. The applied method improves the knowledge about the different mobility patterns of tourists (the most visited points and the main flows between them within a destination) depending on who they are and what their preferences are. Clustering tourists by their travel mobility permits uncovering much more information about them and their preferences than previous studies. This knowledge will allow DMOs and tourism service providers to offer personalized services and information, to attract specific types of tourists to certain points of interest, to create new routes, or to enhance public transport services.
ISSN:2076-3417