Scaling of City Attractiveness for Foreign Visitors through Big Data of Human Economical and Social Media Activity
Name
Ratti_Scaling of city.pdf
Size
1.43 MB
Format
Adobe PDF
Checksum (MD5)
21b7f9c43c492f4bb4e713d7fc0173b8
Author(s)
Sobolevsky, Stanislav
Bojic, Iva
Belyi, Alexander
Sitko, Izabela
Hawelka, Bartosz
Arias, Juan Murillo
Ratti, Carlo
Date Issued
June 2015
Journal
Proceedings of the 2015 IEEE International Congress on Big Data
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Sobolevsky, Stanislav, Iva Bojic, Alexander Belyi, Izabela Sitko, Bartosz Hawelka, Juan Murillo Arias, and Carlo Ratti. “Scaling of City Attractiveness for Foreign Visitors through Big Data of Human Economical and Social Media Activity.” 2015 IEEE International Congress on Big Data (June 2015).
Version
Author's final manuscript
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Department of Urban Studies and Planning
Massachusetts Institute of Technology. SENSEable City Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/BigDataCongress.2015.92
