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The Rise of the Algorithmic Medium
Algorithms are the new medium between people and people, people and data, data and data.
Curated by Pierre Levy
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Is This What Twitter Commerce Will Look Like?

Is This What Twitter Commerce Will Look Like? | The Rise of the Algorithmic Medium | Scoop.it
In pictures!
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Algorithm Writes People's Life Histories Using Twitter | MIT Technology Review

Algorithm Writes People's Life Histories Using Twitter | MIT Technology Review | The Rise of the Algorithmic Medium | Scoop.it
If you tweet about your life, a new algorithm can identify your most significant events and assemble them into an accurate life history, say the computer scientists who built it
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New Algorithm Can Spot the Bots in Your Twitter Feed | Wired Enterprise | Wired.com

New Algorithm Can Spot the Bots in Your Twitter Feed | Wired Enterprise | Wired.com | The Rise of the Algorithmic Medium | Scoop.it
Researchers have created an algorithm that can tell—with 85 percent accuracy—whether a Twitter account is home to a bot or (worse) a corporate shill.
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luiy's curator insight, October 19, 2013 2:04 PM

You know Twitter spam when you see it—but wouldn’t it be nice if you didn’t have to see it?

 

Unfortunately, email-style filters, which analyze message contents, are of little help. Due to the rigors of 140-character communication, even legitimate tweets tend to read like Nigerian phishing scams, while the hucksters often hide their pitches in links. So Twitter simply puts the onus on users to report offending accounts.

 

But a fascinating recent study from Imperial College London suggests a new approach. Borrowing some tricks from computational neuroscience, coauthors Gabriela Tavares and Aldo Faisal have come up with an algorithm that can tell—with 85 percent accuracy—whether a Twitter account is home to a bot or (worse) a corporate shill instead of a regular person.

 

It’s all in the timing. By analyzing the timestamps on 165,000 tweets, the researchers found that these three user types—individuals, companies, and robots—have very distinct activity patterns. Think of it as temporal fingerprinting. The approach could eventually be used to create more effective filters for all kinds of social networks.

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Why Twitter Has More Freedom to Innovate Than Google | Wired Enterprise | Wired.com

Why Twitter Has More Freedom to Innovate Than Google | Wired Enterprise | Wired.com | The Rise of the Algorithmic Medium | Scoop.it
When the University of Michigan abandoned good old fashioned telephone lines in favor of new-age phones that sent calls over the public internet, Marius Eriksen's class project was to build software that could eavesdrop on student conversations.
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