Mining Big Data for Tourist Hot Spots: Geographical Patterns of Online Footprints

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Abstract

Understanding the complex, and often unequal, spatiality of tourist demand in urban contexts requires other methodologies, among which the information base available online and in social networks has gained prominence. Innovation supported by Information and Communication Technologies in terms of data access and data exchange has emerged as a complementary supporting tool for the more traditional data collection techniques currently in use, particularly, in urban destinations where there is the need to more (near)real-time monitoring. The capacity to collect and analise massive amounts of data on individual and group behaviour is leading to new data-rich research approaches. This chapter addresses the potential for discovering geographical insights regarding tourists’ spatial patterns within a destination, based on the analysis of geotagged data available from two social networks.

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Encalada, L., Ferreira, C. C., Boavida-Portugal, I., & Rocha, J. (2019). Mining Big Data for Tourist Hot Spots: Geographical Patterns of Online Footprints. In Key Challenges in Geography (Vol. Part F2238, pp. 99–123). Springer International Publishing. https://doi.org/10.1007/978-3-030-04750-4_6

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