The effect of intra-urban mobility flows on the spatial heterogeneity of social media activity: investigating the response to rainfall events. Issue 6 (3rd June 2022)

• Record Type: Journal Article
• Authors: de Andrade, Sidgley Camargo; Porto de Albuquerque, João; Restrepo-Estrada, Camilo; Westerholt, René; Rodriguez, Carlos Augusto Morales; Mendiondo, Eduardo Mario; Delbem, Alexandre Cláudio Botazzo
• Is Part Of: International journal of geographical information science. Volume 36:Issue 6(2022)
• Page Start: 1140
• Page End: 1165
• Publication Date: 2022-06-03
• Subjects: Spatial heterogeneity -- spatial autoregressive model -- social media -- mobility flows -- rainfall data; Geography -- Data processing -- Periodicals; Information storage and retrieval systems -- Periodicals; Géomatique -- Périodiques; Systèmes d'information -- Périodiques; 910.285
• DOI: 10.1080/13658816.2021.1957898
• Languages: English
• ISSNs: 1365-8816

Abstract

ABSTRACT: 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 ( R 2 = 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.