Abstract
The economic impact of tourism and travel is considerable as it drives the growth of investment in infrastructure and is a source of significant foreign currency not subject to debt obligations, purchase and specific payments. Among the major expenses of tourists during their stay in Morocco are their outlays in markets and souks, since they represent a contributing element in the income of actors in the tourism sector. TripAdvisor is one of the most popular social media for travelers, it is considered as a bank of information about each country’s tourism, which can be trusted and recommended. This information can be exploited for analytical purposes using data mining techniques to help decision-makers in the sphere of tourism to take measures to improve touristic shopping sites in Morocco. In this paper, we present a detailed exploratory data analysis of tourist’s feelings towards Moroccan shopping places, in particular, the characteristics of each shopping place according to ratings, a discussion about types of shopping places with a detailed geographical analysis, and finally an introduction to topic discovery using N-grams and Word-Cloud.
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Bouabdallaoui, I., Guerouate, F., Bouhaddour, S., Saadi, C., Sbihi, M. (2022). Advanced Exploratory Data Analysis for Moroccan Shopping Places in TripAdvisor. In: Guarda, T., Portela, F., Augusto, M.F. (eds) Advanced Research in Technologies, Information, Innovation and Sustainability. ARTIIS 2022. Communications in Computer and Information Science, vol 1675. Springer, Cham. https://doi.org/10.1007/978-3-031-20319-0_20
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