More research on the behavior of crowds–benefits and risks …
*Becker, J., Porter, E., & Centola, D. (2019). The wisdom of partisan crowds. PNAS Proceedings of the National Academy of Sciences of the United States of America, 116(22), 10717-10722. [PDF] [Cited by]
“Theories in favor of deliberative democracy are based on the premise that social information processing can improve group beliefs. While research on the “wisdom of crowds” has found that information exchange can increase belief accuracy on noncontroversial factual matters, theories of political polarization imply that groups will become more extreme—and less accurate—when beliefs are motivated by partisan political bias. A primary concern is that partisan biases are associated not only with more extreme beliefs, but also with a diminished response to social information. While bipartisan networks containing both Democrats and Republicans are expected to promote accurate belief formation, politically homogeneous networks are expected to amplify partisan bias and reduce belief accuracy. To test whether the wisdom of crowds is robust to partisan bias, we conducted two web-based experiments in which individuals answered factual questions known to elicit partisan bias before and after observing the estimates of peers in a politically homogeneous social network. In contrast to polarization theories, we found that social information exchange in homogeneous networks not only increased accuracy but also reduced polarization. Our results help generalize collective intelligence research to political domains.”
“As political polarization in the United States continues to rise, the question of whether polarized individuals can fruitfully cooperate becomes pressing. Although diverse perspectives typically lead to superior team performance on complex tasks, strong political perspectives have been associated with conflict, misinformation and a reluctance to engage with people and ideas beyond one’s echo chamber. Here, we explore the effect of ideological composition on team performance by analyzing millions of edits to Wikipedia’s political, social issues and science articles. We measure editors’ online ideological preferences by how much they contribute to conservative versus liberal articles. Editor surveys suggest that online contributions associate with offline political party affiliation and ideological self-identity. Our analysis reveals that polarized teams consisting of a balanced set of ideologically diverse editors produce articles of a higher quality than homogeneous teams. The effect is most clearly seen in Wikipedia’s political articles, but also in social issues and even science articles. Analysis of article ‘talk pages’ reveals that ideologically polarized teams engage in longer, more constructive, competitive and substantively focused but linguistically diverse debates than teams of ideological moderates. More intense use of Wikipedia policies by ideologically diverse teams suggests institutional design principles to help unleash the power of polarization.
These articles have been added to Science Primary Literature (database) and to Crowds: behavior, social change, movement, collective action, social media, context, identity (Science Bibliographies Online).
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