Collective Intelligence and Neutral Point of View: The Case of Wikipedia
National Bureau of Economic Research
We examine whether collective intelligence helps achieve a neutral point of view using data from a decade of Wikipedia’s articles on US politics. Our null hypothesis builds on Linus’ Law, often expressed as “Given enough eyeballs, all bugs are shallow.” Our findings are consistent with a narrow interpretation of Linus’ Law, namely, a greater number of contributors to an article makes an article more neutral. No evidence supports a broad interpretation of Linus’ Law. Moreover, several empirical facts suggest the law does not shape many articles. The majority of articles receive little attention, and most articles change only mildly from their initial slant.
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Wikipedia was founded on the notion the Internet is a self-correcting machine: by harnessing collective intelligence through an open-source platform, the facts will ultimately come to light. But a new study shows that collective intelligence generally produces biased information, except in a narrow range of circumstances. Northwestern’s Shane Greenstein and the University of Southern California’s Feng Zhu analyzed a decade’s worth of Wikipedia articles on U.S. politics and found that only a handful of them were politically neutral.