Critical Approach of Digital Footprints to Study Spatial Practices of Urban Tourist Areas: A Case Study of Instagram Data in Biarritz, France

Abstract

The rise of digital footprints has created a number of promises and expectations for the study of territorial dynamics, particularly those of tourist cities. These footprints would make the observation of visitors' spatial practices possible and make up for the lack of information on these practices at an urban scale. Thus, many studies use data from social networks to study the touristic space at different geographical scales. These studies provide several types of visualisations based on this data, thus making it possible to represent and show a supposedly new touristic space-time-from the heat map to the dashboard, the digital footprints are displayed as processed, aggregated, calculated and smoothed. All these transformations-resulting from algorithmic black boxes that do not allow a precise understanding of the methodologies (often complex and approximate)-are often not very transparent. Consequently, the technicality and opacity of this data make necessary the development of critical approaches that allow the deconstruction of these new mapping registers. Based on data collected on a widely used social network, Instagram, we wish to question digital footprints as a potential tool to observe tourist practices, by going back through the data genealogy, from the map to the footprint. Our approach consists of going back to the initial data and their associated metadata, in order to explore two fundamental dimensions, conditions prerequisite for more complex explorations: time and space. Therefore, we collected a corpus of metadata from photographs published on Instagram between 2016 and 2018 in Biarritz, France, which we analyse following these two axes. Through this exploratory study, we will demonstrate that this data, though very rich, presents a certain number of limits, whether in terms of access to the data itself or its spatiotemporal precision.

رصد البصمة الرقمية السياحية ومراكز الأنشطة السياحية من خلال بيانات التوسيم الجغرافي والبيانات المحددة للموقع: مدينة الإسكندرية كدراسة حالة

“…In fact, point of interest and social media check-in information are some of the most effective instruments for assessing urban landscape (Wu, 2022). McKenzie et al (2015) for instance , proved the viability of utilizing a Foursquare database to convey temporal, thematic, and spatial distribution patterns (Padrón-Ávila& Hernández-Martín, 2017;Mondo et al, 2020). In line with this approach, innovative research has improved the identification of Tourist Activity Centers using Foursquare, Twitter, Google Places, and Airbnb.…”

“…According to Salas-Olmedo et al (2018), innovation has also been achieved in the usage of LBSNs, especially Twitter, Foursquare, and Panoramio, to determine tourism activities from usergenerated content in the context of Barcelona, Spain. In spite of the developed benefits of LBSNs for locating points of interest (POIs) in urban areas, this study conveys a methodology for identifying and pinpointing tourist activity centers (TACs) by incorporating data from five distinct LBSNs: Twitter (Salas-Olmedo et al, 2018;Cebrián & Domenech, 2023), Instagram (Mondo et al, 2020), Instasights heatmaps (Avuxi Ldt 2024), Foursquare (Foursquare Inc. 2019), and TripAdvisor (TripAdvisor LLC 2022.…”

“…Fourthly, the LBSN that is check-in based foursquare encompasses a registry of socioeconomic activities and relevant locations in the city, known as venues (Foursquare Inc., 2019). By "checking-in" at a particular area, foursquare users may share not only their location but also their thoughts and experiences regarding that particular spot (Mondo et al, 2020). In tourism researches, Foursquare has also been used to rank preferences (Tammet et al, 2013) and identify popular tourist destinations or activities (Gao et al, 2024).…”

“…Recent scholarly attention has been directed towards TripAdvisor as a valuable resource for investigating consumer behavior and preferences, encompassing a range of subjects, including the effects of market positioning (Mou, 2022), decision-making processes of travelers (Litvin & Dowling, 2018), and the impact of factors like accessibility and walkability on the spatial behavior of tourists (Hall & Ram, 2019). Noteworthy, all these platforms have been employed in previous researches and proven to be appropriate contributors of baseline information to address a range of tourism-related issues (Mondo et al, 2020;Martí et al, 2021;Nolasco-Cirugeda et al, 2022;Cebrián & Domenech, 2023;Encalada-Abarca et al, 2024).…”

Analyse bibliométrique pour saisir la place de la fréquentation des espaces naturels dans le champ de recherche des Informations Géographiques Volontaires

“…Ces traces disposent de contenu informationnel, expérientiel et/ou spatial, devenant alors des traces géonumériques (Mericskay & Roche, 2011 ;Mericskay et al, 2018), ou Informations Géographiques Volontaires (IGV). L'exploitation de ces données dessine de nouvelles perspectives pour la recherche, par exemple en matière de mobilité urbaine (Le Breton et al, 2022), y compris sportive (Musakwa & Selala, 2016 ;Dadashova et al, 2020 ;Hong et al, 2020 ;Kyuhyun & Ipek Nese, 2021 ;Nelson et al, 2021 ;Venter et al, 2021), ou de comportements spatiaux des touristes en milieu urbain (Mondo et al, 2020). Ce web collaboratif donne accès à de grandes quantités de données documentant des phénomènes par ailleurs difficilement observables (Houllier & Merilhou-Goudard, 2016), notamment en montagne du fait de la dispersion et de la faible densité des usages.…”