Geotagged urban activity

As described in our paper, we have collected 11.5M checkins around the world that were publicly made available on twitter. Each of them is represented by a line of a CSV file `all_checkins.csv` containing the following values:<br><br>userId: a random number uniquely identifying a foursquare user<br>venueId: id of the venue where the checkin took place<br>timestamp: UTC timestamp of the checkins<br>timeZoneOffset: local offset from UTC in minutes<br><br>In total there are 2M venues in those checkins and while we can't provide too much information as per Foursquare policy (https://developer.foursquare.com/overview/venues#rules), the file `all_venues.csv` contains their location and category. Namely:<br>venueId: id of the venue<br>latitude,longitude: coordinates<br>categoryId: foursquare main category id for that venue (https://developer.foursquare.com/categorytree)<br><br>In addition, the script get_venues_info.py can be used to get the remaining up to date information.<br><br>