exposing non-geographical aspects of mobility using location-based social networks
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Exposing non-geographical aspects of mobility using location-based social networks
Alejandro Llorente Pinto, Instituto de Ingeniería del Conocimiento Manuel Cebrián, NICTA Manuel García-Herranz, Universidad Autónoma de Madrid Esteban Moro, Universidad Carlos III de Madrid
Urban Beers, Barcelona, 2013
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Geolocated Twitter data
• 5 months of data
• Continental part of Spain
• 146 million of tweets
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City Flows Graph
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City Flows Graph
![Page 5: Exposing non-geographical aspects of mobility using location-based social networks](https://reader034.vdocument.in/reader034/viewer/2022042813/54795b3db4795990098b4774/html5/thumbnails/5.jpg)
The Gravity Model
High correlation between observed flows and the model and low MAE
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The Gravity Model
Are model failures just statistical fluctuations or...?
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The Gravity Model Everything seems nice but...
Are model failures just statistical fluctuations or...?
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Thank you very much!
Urban Beers, Barcelona, 2013
Alejandro Llorente Pinto, Instituto de Ingeniería del Conocimiento Manuel Cebrián, NICTA Manuel García-Herranz, Universidad Autónoma de Madrid Esteban Moro, Universidad Carlos III de Madrid