Abstract
This study aims at exploring social media data to evaluate how regional and cultural characteristics influence the mobility behavior of tourists and residents. By considering information taken from the mobility graphs of users from different countries, we observe that users’ origins can influence their choices. Additionally, the analysis performed in the experiments shows that a regression model could enable the prediction of the behavior of a tourist from a specific country when visiting another country, based on their cultural distances (obtained offline). The ability to explore the cultural characteristics of each nationality in different destinations shows a promising way to improve recommendation systems for points of interest and other services to particular groups of tourists.
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Notes
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Arts & Entertainment; College & University; Professional & Other Places; Residences; Outdoors & Recreation; Shops & Services; Nightlife Spots; Food; Travel & Transport; and Event.
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Other distances and linkage criteria were evaluated, but this combination provided the most consistent results.
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Acknowledgment
This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. This work is also partially supported by the project GoodWeb (Grant #2018/23011-1 from São Paulo Research Foundation - FAPESP), and CNPq, grants 309935/2017-2, 439226/2018-0, and by a Connaught Global Challenge Award.
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Senefonte, H., Frizzo, G., Delgado, M., Lüders, R., Silver, D., Silva, T. (2020). Regional Influences on Tourists Mobility Through the Lens of Social Sensing. In: Aref, S., et al. Social Informatics. SocInfo 2020. Lecture Notes in Computer Science(), vol 12467. Springer, Cham. https://doi.org/10.1007/978-3-030-60975-7_23
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