Square cities: time dimension

Problem Description

This project is a continuation of two previous research projects:

  • Senseable Moscow “Moya Moskva” project (Kats 2012)
  • NYU CUSP Applied Data science research project (Kats 2015)

All three projects are based on the same idea of explaining significant differences between cities stats, using foursquare venues data. This particular project, however, bounds to the the temporal dimension of data, analyzing venue creation through last 5 years for 8 cities, including New York, San Francisco, Shanghai, Mumbai, Moscow, Singapur, Kiev and Minsk.

This research aims to explore three questions stated below:

  • Do all cities have similar “temporal behavior” on venue registration?
  • Do they perform similar behaviour in terms of vanue-category granulated timelines?

While we are driven by scientific curiosity, This is not the research for the sake of research, as the answers to those questions, potentially, may lead us to the between understanding of the spatial-economical behaviour of cities.


Research is based on foursquare service data on venues (locations), collected through official API with the custom data collector. Scraper was collecting all venues created at any time and still existing1 for the given location. Location at this moment is defined by the coordinate rectangular.


Research will be based on different time-series analysis techniques, time-series correlation, KS2 tests and K-mean clustering.

TimeLines Overview

Venue creation normalised timeline

On the general time line we can see that the general trend is similar, as most of the growth for each city happened on the range from 2010 till now. However, even without clustering we can see 4 groups of cities with similar behaviour:

  • American cities, San Francisco and New York started much earlier, in 2004 (which is interesting, as sevice was officially opened to public in 2009 - most likely, they used databases from the previous project. Both cities grew fast from 2009 till 2013, where they were slowing down. We may assume that in 2013 forsquare covered most of existing places in thse cities.
  • Tokyo and Singapur started in 2010, and both skyrocketed to the level of american cities in 2011, bahaving similarly after that.
  • Minsk and Kiev are the most "late" cities in the set, as they started growing rapidly in 2012, and both have similar dynamics till now - we can assume that both of them did not finish the "extensive" phase, in other words, not all existing significant places were described in the service.
  • All other cities (Shanghai,Moscow, and Singapur) have average behavior, grewing relatively slowly from 2010, and slowing down to "american" behaviour from 2014.