John Timmer at Ars Technica discusses some Yahoo! researchers who say they can create an automated system that identifies newsworthy events and judges their reliability with an accuracy of nearly 90 percent.
They used Twitter Monitor to see what was trending and gathered all the tweets on thousands of topics - then they used humans to help calibrate 'credibility' (caveat emptor on that) and used support vector machines, Bayesian networks, and decision trees to help them determine how to find the most credible sources.
Which method worked best? Read Accurate and credible news tweets? Automated system finds them by John Timmer
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