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Title: A global analysis of cities’ geosocial temporal signatures for points of interest hours of operation

Abstract

The temporal nature of humans interaction with Points of Interest (POIs) in cities can differ depending on place type and regional location. Times when many people are likely to visit restaurants (place type) in Italy, may differ from times when many people are likely to visit restaurants in Lebanon (i.e. regional differences). Geosocial data are a powerful resource to model these temporal differences in cities, as traditional methods used to study cross-cultural differences do not scale to a global level. As cities continue to grow in population and economic development, research identifying the social and geophysical (e.g., climate) factors that influence city function remains important and incomplete. Here, we take a quantitative approach, applying dynamic time warping and hierarchical clustering on temporal signatures to model geosocial temporal patterns for Retail and Restaurant Facebook POIs hours of operation for more than 100 cities in 90 countries around the world. Results show cities’ temporal patterns cluster to reflect the cultural region they represent. Furthermore, temporal patterns are influenced by a mix of social and geophysical factors. Trends in the data imply social factors influence unique drops in temporal signatures, and geophysical factors influence when daily temporal patterns start and finish.

Authors:
 [1]; ORCiD logo [1];  [2]; ORCiD logo [1]
  1. Oak Ridge National Laboratory, Oak Ridge, TN, USA
  2. Department of Computer Science, Columbia University, New York, NY, USA
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1546559
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
International Journal of Geographical Information Science
Additional Journal Information:
Journal Volume: TBD; Journal Issue: TBD; Journal ID: ISSN 1365-8816
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS; Geosocial; points of interest; temporal signatures; social media; cities

Citation Formats

Sparks, Kevin, Thakur, Gautam, Pasarkar, Amol, and Urban, Marie. A global analysis of cities’ geosocial temporal signatures for points of interest hours of operation. United States: N. p., 2019. Web. doi:10.1080/13658816.2019.1615069.
Sparks, Kevin, Thakur, Gautam, Pasarkar, Amol, & Urban, Marie. A global analysis of cities’ geosocial temporal signatures for points of interest hours of operation. United States. doi:10.1080/13658816.2019.1615069.
Sparks, Kevin, Thakur, Gautam, Pasarkar, Amol, and Urban, Marie. Tue . "A global analysis of cities’ geosocial temporal signatures for points of interest hours of operation". United States. doi:10.1080/13658816.2019.1615069. https://www.osti.gov/servlets/purl/1546559.
@article{osti_1546559,
title = {A global analysis of cities’ geosocial temporal signatures for points of interest hours of operation},
author = {Sparks, Kevin and Thakur, Gautam and Pasarkar, Amol and Urban, Marie},
abstractNote = {The temporal nature of humans interaction with Points of Interest (POIs) in cities can differ depending on place type and regional location. Times when many people are likely to visit restaurants (place type) in Italy, may differ from times when many people are likely to visit restaurants in Lebanon (i.e. regional differences). Geosocial data are a powerful resource to model these temporal differences in cities, as traditional methods used to study cross-cultural differences do not scale to a global level. As cities continue to grow in population and economic development, research identifying the social and geophysical (e.g., climate) factors that influence city function remains important and incomplete. Here, we take a quantitative approach, applying dynamic time warping and hierarchical clustering on temporal signatures to model geosocial temporal patterns for Retail and Restaurant Facebook POIs hours of operation for more than 100 cities in 90 countries around the world. Results show cities’ temporal patterns cluster to reflect the cultural region they represent. Furthermore, temporal patterns are influenced by a mix of social and geophysical factors. Trends in the data imply social factors influence unique drops in temporal signatures, and geophysical factors influence when daily temporal patterns start and finish.},
doi = {10.1080/13658816.2019.1615069},
journal = {International Journal of Geographical Information Science},
number = TBD,
volume = TBD,
place = {United States},
year = {2019},
month = {6}
}

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