People fulfill their informational needs through smartphones, however, little is known regarding how the urban fabric and the activities that take place in it affect the usage of mobile applications. In this regard, starting from an anonymized dataset of Deep Packet Inspection (DPI) data from the largest telecommunications operator in Chile, we focus on the following questions: What are the most popular applications used in the city Where are they spatially clustered When does an application is more frequently used And How does the urban context and the mobility patterns relate to application usage As a result, we observed that specific applications present high spatial clustering, while the most popular services are geographically dispersed throughout the entire city. Clusters appear in places of high floating population; however, hotspots vary in space depending on the application. Interestingly, we found that commuting plays an important role, both in terms of rush hours and transportation infrastructure. We present a discussion on these results, focusing on how the physical space and the daily commuting routine affect the pattern of data consumption and represent an important aspect in mobile users behavioral studies.
The WWW (and an H) of Mobile Application Usage in the City
Schifanella, Rossano;
2018-01-01
Abstract
People fulfill their informational needs through smartphones, however, little is known regarding how the urban fabric and the activities that take place in it affect the usage of mobile applications. In this regard, starting from an anonymized dataset of Deep Packet Inspection (DPI) data from the largest telecommunications operator in Chile, we focus on the following questions: What are the most popular applications used in the city Where are they spatially clustered When does an application is more frequently used And How does the urban context and the mobility patterns relate to application usage As a result, we observed that specific applications present high spatial clustering, while the most popular services are geographically dispersed throughout the entire city. Clusters appear in places of high floating population; however, hotspots vary in space depending on the application. Interestingly, we found that commuting plays an important role, both in terms of rush hours and transportation infrastructure. We present a discussion on these results, focusing on how the physical space and the daily commuting routine affect the pattern of data consumption and represent an important aspect in mobile users behavioral studies.File | Dimensione | Formato | |
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