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Princeton University

Crowd wisdom such as what might arise from online voting is popularly assumed to provide better answers than any one person by aggregating multiple perspectives. Democratic methods, however, tend to favor the most popular information, not necessarily the most correct. The ignorance of the masses can cancel out a knowledgeable minority with specialized information of a topic, resulting in the wrong answer becoming the most accepted.

To give more weight to correct information that may not be widely known, researchers from Princeton University and the Massachusetts Institute of Technology have developed what they call the “surprisingly popular” algorithm. Reported in the journal Nature on Jan. 26, the technique hinges on asking people two things about a given question: What do they think the right answer is, and how popular do they think each answer will be?

The correct answer is that which is more popular than people predict, the researchers report. The technique could refine wisdom-of-crowds surveys, which are used in political and economic forecasting, as well as many other collective activities, from pricing artwork to grading scientific research proposals.

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