In the act of placing and receiving calls, or sending text messages, a mobile phone reports its presence to the closest cell towers and unveils its geographical position. Mobile phone providers collect in their call data records the information about the clients’ spatial localization. The use of such data sets represents an enormous scientific opportunity to detect the structure of social networks. Quantifying and understanding network features may help to obtain deeper insight into applications of practical importance. For instance, knowing the number of visitors moving from one destination to another is an information that reveals valuable knowledge for regional tourism planning. With this aim, we investigate how visitors of Sardinia (Italy) move across the island, according to the localization tracks revealed by their cell phones. In order to study such mobility patterns, we employ aggregated call data records to construct a spatial network that we analyze with the aid of statistical tools. We also provide a comparison between the movement behaviors of national and international visitors.
Fiori, A., Foroni, I. (2020). Spatial Localization of Visitors Mobile Phones in a Sardinian Destinations’ Network. In P. Mariani, M. Zenga (a cura di), Data Science and Social Research II : Methods, Technologies and Applications (pp. 145-155). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-030-51222-4_12].
Spatial Localization of Visitors Mobile Phones in a Sardinian Destinations’ Network
Fiori, AM;Foroni, I
2020
Abstract
In the act of placing and receiving calls, or sending text messages, a mobile phone reports its presence to the closest cell towers and unveils its geographical position. Mobile phone providers collect in their call data records the information about the clients’ spatial localization. The use of such data sets represents an enormous scientific opportunity to detect the structure of social networks. Quantifying and understanding network features may help to obtain deeper insight into applications of practical importance. For instance, knowing the number of visitors moving from one destination to another is an information that reveals valuable knowledge for regional tourism planning. With this aim, we investigate how visitors of Sardinia (Italy) move across the island, according to the localization tracks revealed by their cell phones. In order to study such mobility patterns, we employ aggregated call data records to construct a spatial network that we analyze with the aid of statistical tools. We also provide a comparison between the movement behaviors of national and international visitors.
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