Scaling of City Attractiveness for Foreign Visitors through Big Data of Human Economical and Social Media Activity

Scientific studies investigating laws and regularities of human behavior are nowadays increasingly relying on the wealth of widely available digital information produced by human activity. In this paper we use big data created by three different aspects of this activity (i.e., Bank card transactions...

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Bibliographic Details
Main Authors: Sobolevsky, Stanislav, Bojic, Iva, Belyi, Alexander, Sitko, Izabela, Hawelka, Bartosz, Murillo Arias, Juan, Ratti, Carlo
Format: Conference Proceeding
Language:English
Subjects:
bank cards
Cities and towns
discrete-choice model
Flickr
human mobility
Robustness
Sociology
Statistics
superlinear scaling
Twitter
urban attraction
Videos
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Summary:Scientific studies investigating laws and regularities of human behavior are nowadays increasingly relying on the wealth of widely available digital information produced by human activity. In this paper we use big data created by three different aspects of this activity (i.e., Bank card transactions, geotagged photographs and tweets) in Spain for quantifying city attractiveness for foreign visitors. An important finding of this paper is a strong super linear scaling law of city attractiveness with its population size. The observed scaling exponent stays nearly the same for different ways of defining cities and for different data sources, emphasizing the robustness of our finding. We also consider temporal variation of the scaling exponent in order to reveal seasonal patterns in the attractiveness. Finally, we propose a possible explanatory mechanism for the observed super linear effect based on a simple discrete choice model.
ISSN:2379-7703
DOI:10.1109/BigDataCongress.2015.92