Week 3: Python for geo-scripting

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Today: Thursday 25/01/2016

As background knowledge it is assumed that you know what JSON is. If not have a look at (http://http://www.w3schools.com/js/js_json_intro.asp). Also aquaint yourself yourself with the datastructure of tweets. You can find it on (https://dev.twitter.com/overview/api/tweets). Try to find out for example where spatial references are made in a tweet . During the self-study also ask yourself question like

  • 8:30-12.15: Self-study by working on the two notebooks below. If you want to go beyond, have a look at: Mining-the-Social-Web and/or the Twitter Cookbook
  • 13:30-14:15: Feedback and presentation about social media as a source of spatial data
  • 14:15-17:00 Assignment

Python notebooks for the self-study

Connecting and harvesting Real-time tweets

Harvesting real time tweets


Create a twitter harvesting application that harvest tweets (either real-time or stored), and create a spatial dataset en map from it. The application should be able to: collect tweets based on a thematic and/or spatial query.


  • Feed a spatial database with information tweeted real time from a certain location and plot it on a map.
  • Create a map indicating where traffic jams, disruptions in the public transport or ... took place last week.
  • Create a map indication the home countries of international tourist visiting Amsterdam (or Wageningen if you like)
  • Go out with your smartphone (what else should you do during lunch), collect spatial information (for examples POIs on the campus) by tweeting from various locations using a specific hashtag (make sure location is enabled in your twitter account), harvest these tweets with an application, and create a map from it.
  • .... think of something else.

Send in your application as a python script as well as a screenshot of the map you produced (through the script review centre: lesson 14)