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Monday, 25 October 2010

The Tweet Has Landed


Just Landed - Test Render (4 hrs) from blprnt on Vimeo.


What is this visualisation showing us?

Jer Thorp is an artist and educator currently living in New York. A former geneticist, his digital art practice explores the many-folded boundaries between science and art.

He aims to track data that is hidden in various social network information streams in particular Facebook & Twitter updates.

In the above video he demonstrates how he has extracted travel information from people’s public Twitter streams by searching for the term ‘Just landed in…’.

As he puts it "Find tweets that contain this phrase, parse out the location they’d just landed in, along with the home location they list on their Twitter profile, and use this to map out travel in the Twittersphere."

While this is very much a project in the making, the future application of being able to track tweet terminology in this manner could greatly assist social media analytics.

For a more graphic visualisation try Twit3D

Twit3D

Of more interest though is the ability to predict what might happen in a social media campaign, rather than just measuring or graphically charting results, post-campaign.

MIT's Technoogy review showcases the success of Jason Harper who works for a digital ad agency and has devised a way to use Twitter and Facebook to forecast sales of everything from cars to tampons.

Harper's model borrows from  the concepts of velocity and acceleration from the world of physics. He collects data during three phases of a campaign: the baseline, or the number of Tweets or Facebook fans before an ad campaign starts; The Hot Zone, or the main surge of activity during the campaign, and the Fallout, the inevitable decline when the campaign is finished.

The MIT article states:

"Under Harper's model, which he calls Velocity & Acceleration, the idea is to constantly measure the number of related tweets, blog mentions, and Facebook fan sign-ups during the campaign.

By using calculus to compute the velocity, or rate of change, of the tweets and sign-ups, Harper can easily compute any acceleration, the rate of change of velocity over time. Using these two metrics, Harper says he can predict whether a mass marketing campaign will reach its overall goals within the first few days it begins running.

The resulting curve typically takes a steep upward slope before leveling off, a pattern known in the industry as "the kick-ass curve." Says Harper: "The idea is to predict the height of the plateau."
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