García Palomares, Juan CarlosOsorio Arjona, Joaquín2024-05-202024-05-202019-06-010264-2751; eISSN: 1873-6084https://doi.org/10.1016/j.cities.2019.03.006https://hdl.handle.net/20.500.14468/12105The proliferation of Big Data is beneficial to the study of mobility patterns in cities. This work investigates the use of social media as an efficient tool for urban mobility studies. In this case, the social network Twitter has been used, due to its wealth of spatial and temporal data and the possibility of accessing data free of charge. Using a database of geotagged tweets in the Madrid Metropolitan Area over a two-year period, this article describes the steps followed in the preparation and cleansing of the initial data and the visualisation of the results in Geographic Information Systems in the form of home-work matrices. The Origin-Destination matrices obtained were then compared with the official data provided by the Madrid Transport Consortium from the 2014 Synthetic Mobility Survey. The results of this comparison demonstrate that the level of precision offered by Twitter as a source of geographic information is adequate and efficient, thereby permitting a more in-depth analysis of flows between different zones of interest in the study area.enAtribución-NoComercial-SinDerivadas 4.0 Internacionalinfo:eu-repo/semantics/openAccessartículoSocial networksMobilityGeographic information systemsTwitterHome-work matrices