This study examines user voting behaviors across three popular websites: IMDb, Amazon, and BookCrossings. Through an expert evaluation of each site's voting mechanisms and a quantitative analysis of users' voting patterns, findings indicate that platforms with higher voting barriers attract a significant number of one-off voters, who are likely experts. These voters often rate popular items, while expert users tend to vote for more obscure, low-rated items. The study concludes by offering design recommendations to mitigate the "wisdom of the crowd" bias, suggesting ways to balance the influence of one-off and expert voters to achieve a more representative assessment of items.
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Kostakos, Vassilis. "Is the crowd's wisdom biased? A quantitative analysis of three online communities." 2009 International Conference on Computational Science and Engineering. Vol. 4. IEEE, 2009.
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