Collective Intelligence and Neutral Point of View in the Case of Wikipedia

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* Article: Collective Intelligence and Neutral Point of View: The Case of Wikipedia*. By Shane Greenstein and Feng Zhu.



An increasing number of organizations or communities today are harnessing the power of collective intelligence to tackle problems that are too big to be solved by themselves. While several prior studies have shown that collective intelligence can lead to high-quality output in the context of uncontroversial and verifiable information, it is unclear whether a production model based on collective intelligence will produce any desirable outcome when information is controversial, subjective, and unverifiable. We examine whether collective intelligence helps achieve a neutral point of view (NPOV) using data from 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. Our study provides the first empirical evidence on the limit of collective intelligence. While many managers believe that they could improve their products by taking advantage of the wisdom of crowds, we show that in the case of Wikipedia, there are aspects such as NPOV that collective intelligence does not help achieve successfully.