THERE are those who edit Wikipedia entries for accuracy 鈥� and those who use the online encyclopaedia daily without ever contributing. A new mathematical model says that鈥檚 probably as it should be: crowdsourcing a problem works best when a certain subset of the population chooses not to participate.
鈥淚n most social undertakings, there is a group that actually joins forces and works,鈥� says at the the Faculty of Information Studies in Novo Mesto, Slovenia. 鈥淎nd there is a group of free-riders that typically benefits from work being done, without contributing much.鈥�
Levnajic and his colleagues simulated this scenario. Digital people in a virtual population each had a randomly assigned tendency to collaborate on a problem or 鈥渇reeload鈥� 鈥� working alone and not sharing their findings. The team ran simulations to see whether there was an optimum crowdsource size for problem-solving.
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It turned out there was 鈥� and surprisingly, the most effective crowd was not the largest possible. In fact, the simulated society was at its problem-solving best when just half the population worked together.
Smaller crowds contained too few willing collaborators with contrasting but complementary perspectives to effectively solve a problem. But if the researchers ran simulations with larger crowds, the freeloaders it contained naturally 鈥渄efected鈥� to working alone 鈥� knowing that they could benefit from any solutions the crowd reached, while also potentially reaping huge benefits if they could solve the problem without sharing the result ().
But does that happen in reality?
鈥淐rowdsourcing is interesting precisely because humans are not simple,鈥� says of the University of Harvard.
Consequently, Levnajic鈥檚 team will soon study the behaviour of real-world crowds.
This article appeared in print under the headline 鈥淐rowdsourcing works best if some don鈥檛 help鈥�
