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Sun Sep 21 11:05:08 2014

A Django site.

QGIS Planet

A Visual Exploration of Twitter Streams

Twitter streams are curious things, especially the spatial data part. I’ve been using Tweepy to collect tweets from the public timeline and what did I discover? Tweets can have up to three different spatial references: “coordinates”, “geo” and “place”. I’ll still have to do some more reading on how to interpret these different attributes.

For now, I have been using “coordinates” to explore the contents of a stream which was collected over a period of five hours using

stream.filter(follow=None,locations=(-180,-90,180,90))

for global coverage. In the video, each georeferenced tweet produces a new dot on the map and if the user’s coordinates change, a blue arrow is drawn:

While pretty, these long blue arrows seem rather suspicious. I’ve only been monitoring the stream for around five hours. Any cross-Atlantic would take longer than that. I’m either misinterpreting the tweets or these coordinates are fake. Seems like it is time to dive deeper into the data.


Mapping Movement Using Tweets

After playing around with some twitter data for animation purposes (in Time Manager), I’m now looking into movement patterns. Series of successive georeferenced tweets can be connected to get an idea of how people move within a city as well as between cities and continents.

Currently, I’m still working on the basics of collecting relevant data. A first proof of concept can be seen in this map which contains locations of a handful of users in the greater Viennese area:

Each user is represented by a differently colored line.

Updates and code samples will follow.


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