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Item type:Publication, A data fusion approach with mobile phone data for updating travel survey-based mode split estimates(2023) ;Eduardo Graells-Garrido; ;Francisco RoweJacqueline ArriagadaScopus© Citations 35 3 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Linking physical violence to women’s mobility in ChileDespite increased global attention on violence against women, understanding the factors that lead to women becoming victims remains a critical challenge. Notably, the impact of domestic violence on women’s mobility—a critical determinant of their social and economic independence—has remained largely unexplored. This study bridges this gap, employing police records to quantify physical and psychological domestic violence, while leveraging mobile phone data to proxy women’s mobility. Our analyses reveal a negative correlation between physical violence and female mobility, an association that withstands robustness checks, including controls for economic independence variables like education, employment, and occupational segregation, bootstrapping of the data set, and applying a generalized propensity score matching identification strategy. The study emphasizes the potential causal role of physical violence on decreased female mobility, asserting the value of interdisciplinary research in exploring such multifaceted social phenomena to open avenues for preventive measures. The implications of this research extend into the realm of public policy and intervention development, offering new strategies to combat and ultimately eradicate domestic violence against women, thereby contributing to wider efforts toward gender equity.Scopus© Citations 7 2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Evaluation of home detection algorithms on mobile phone data using individual-level ground truth(2021) ;Luca Pappalardo; ;Manuel Sacasa ;Ciro CattutoInferring mobile phone users’ home location, i.e., assigning a location in space to a user based on data generated by the mobile phone network, is a central task in leveraging mobile phone data to study social and urban phenomena. Despite its widespread use, home detection relies on assumptions that are difficult to check without ground truth, i.e., where the individual who owns the device resides. In this paper, we present a dataset that comprises the mobile phone activity of sixty-five participants for whom the geographical coordinates of their residence location are known. The mobile phone activity refers to Call Detail Records (CDRs), eXtended Detail Records (XDRs), and Control Plane Records (CPRs), which vary in their temporal granularity and differ in the data generation mechanism. We provide an unprecedented evaluation of the accuracy of home detection algorithms and quantify the amount of data needed for each stream to carry out successful home detection for each stream. Our work is useful for researchers and practitioners to minimize data requests and maximize the accuracy of the home antenna location.Scopus© Citations 35 3 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Toward An Interdisciplinary Methodology to Solve New (Old) Transportation Problems(2020) ;Eduardo Graells-garridoVanessa Peña-ArayaScopus© Citations 1 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Measuring Spatial Subdivisions in Urban Mobility with Mobile Phone Data(2020) ;Eduardo Graells-garrido ;Irene Meta ;Feliu Serra-Buriel ;Patricio ReyesFernando M. CucchiettiScopus© Citations 6 1