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The effect of intra-urban mobility flows on the spatial heterogeneity of social media activity: investigating the response to rainfall events / Sidgley Camargo de Andrade in International journal of geographical information science IJGIS, vol 36 n° 6 (June 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 6 (June 2022) . - pp 1140 - 1165 Titre : The effect of intra-urban mobility flows on the spatial heterogeneity of social media activity: investigating the response to rainfall events Type de document : Article/Communication Auteurs : Sidgley Camargo de Andrade, Auteur ; João Porto de Albuquerque, Auteur ; Camilo Restrepo-Estrada, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1140 - 1165 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] auto-régression [Termes IGN] distribution spatiale [Termes IGN] données issues des réseaux sociaux [Termes IGN] données socio-économiques [Termes IGN] hétérogénéité spatiale [Termes IGN] mobilité urbaine [Termes IGN] modélisation spatio-temporelle [Termes IGN] pluie [Termes IGN] précipitation [Termes IGN] Sao Paulo [Termes IGN] Twitter Résumé : (auteur) Although it is acknowledged that urban inequalities can lead to biases in the production of social media data, there is a lack of studies which make an assessment of the effects of intra-urban movements in real-world urban analytics applications, based on social media. This study investigates the spatial heterogeneity of social media with regard to the regular intra-urban movements of residents by means of a case study of rainfall-related Twitter activity in São Paulo, Brazil. We apply a spatial autoregressive model that uses population and income as covariates and intra-urban mobility flows as spatial weights to explain the spatial distribution of the social response to rainfall events in Twitter vis-à-vis rainfall radar data. Results show high spatial heterogeneity in the response of social media to rainfall events, which is linked to intra-urban inequalities. Our model performance (R2=0.80) provides evidence that urban mobility flows and socio-economic indicators are significant factors to explain the spatial heterogeneity of thematic spatiotemporal patterns extracted from social media. Therefore, urban analytics research and practice should consider not only the influence of socio-economic profile of neighborhoods but also the spatial interaction introduced by intra-urban mobility flows to account for spatial heterogeneity when using social media data. Numéro de notice : A2022-405 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1957898 Date de publication en ligne : 03/08/2021 En ligne : https://doi.org/10.1080/13658816.2021.1957898 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100717 [article]