Latest revision as of 04:18, 23 March 2021

Abstract

The goal of the present thematic series is to showcase some of the most relevant contributions submitted to the ‘Telecom Italia Big Data Challenge 2014’ and to provide a discussion venue about recent advances in the appplication of mobile phone and social media data to the study of individual and collective behaviors. Particular attention is devoted to data-driven studies aimed at understanding city dynamics. These studies include: modeling individual and collective traffic patterns and automatically identifying areas with traffic congestion, creating high-resolution population estimates for Milan inhabitants, clustering urban dynamics of migrants and visitors traveling to a city for business or tourism, and investigating the relationship between urban communication and urban happiness.

Document type: Article

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The different versions of the original document can be found in:

• http://dx.doi.org/10.1140/epjds/s13688-015-0050-4 under the license http://creativecommons.org/licenses/by/4.0

• https://epjdatascience.springeropen.com/track/pdf/10.1140/epjds/s13688-015-0050-4

• http://hdl.handle.net/1721.1/103285,

https://orcid.org/0000-0002-8053-9983 under the license cc-by

• http://link.springer.com/content/pdf/10.1140/epjds/s13688-015-0050-4.pdf,

http://link.springer.com/article/10.1140/epjds/s13688-015-0050-4/fulltext.html,

http://link.springer.com/content/pdf/10.1140/epjds/s13688-015-0050-4,

http://dx.doi.org/10.1140/epjds/s13688-015-0050-4 under the license http://creativecommons.org/licenses/by/4.0/

• https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-015-0050-4,

https://epjdatascience.springeropen.com/track/pdf/10.1140/epjds/s13688-015-0050-4,

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https://link.springer.com/content/pdf/10.1140%2Fepjds%2Fs13688-015-0050-4.pdf,

https://academic.microsoft.com/#/detail/2107414416 under the license http://creativecommons.org/licenses/by/4.0