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People in London Love To Twitter

As discussed earlier, tracking the mountainous amounts of social media data is getting much, much easier as more and more companies include geospatial options in their services. Another process involv...
People in London Love To Twitter
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  • As discussed earlier, tracking the mountainous amounts of social media data is getting much, much easier as more and more companies include geospatial options in their services. Another process involves animating some of this data, overlaying on a map to show usage, travel routes, and well, just about anything else geolocation-based there is.

    Consider the earthquake map from Japan. Granted, its geospatial data was based on seismic readings instead of Twitter or Flickr postings. That being said, the concepts are similar. As are the concepts on display in the “24h London Twitter Traffic” video from Anders Johnson.

    In order to visually demonstrate his data, Anderson used the SIMULCARA technology developed by the Centre for Advanced Spatial Analysis, University College London. The center’s ability to animate map-based data was demonstrated in their “Visualizing Public Transport Networks” videos, which tracked the movement of public transportation in the UK.

    Instead of buses and underground trains, Anderson’s video tracked London-based tweets.

    Anderson explains his work by saying the red circles are tweets and the yellow points are retweets moving in the direction the originating tweet came from. The results are quite impressive, at least in a visual sense:


    It’s hard not to wonder about whether or not the content of the video is better than the content being tracked — considering it’s originating from Twitter. Furthermore, the frequency of the tweets in London notably increase during the evening, and that’s around the time people are going out for social calls. Apparently, even Londoners enjoy drunk tweeting as well.

    Considering the date of the post, March 23rd, the data was collected before the England/Ghana friendly, so it’s hard to gauge what the topic(s) of discussion were.

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