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Network Structures of Collective Intelligence: The Contingent Benefits of Group Discussion
arXiv - CS - Social and Information Networks Pub Date : 2020-09-15 , DOI: arxiv-2009.07202
Joshua Becker, Abdullah Almaatouq, Agnes Horvat

Research on belief formation has produced contradictory findings on whether and when communication between group members will improve the accuracy of numeric estimates such as economic forecasts, medical diagnoses, and job candidate assessments. While some evidence suggests that carefully mediated processes such as the "Delphi method" produce more accurate beliefs than unstructured discussion, others argue that unstructured discussion outperforms mediated processes. Still others argue that independent individuals produce the most accurate beliefs. This paper shows how network theories of belief formation can resolve these inconsistencies, even when groups lack apparent structure as in informal conversation. Emergent network structures of influence interact with the pre-discussion belief distribution to moderate the effect of communication on belief formation. As a result, communication sometimes increases and sometimes decreases the accuracy of the average belief in a group. The effects differ for mediated processes and unstructured communication, such that the relative benefit of each communication format depends on both group dynamics as well as the statistical properties of pre-interaction beliefs. These results resolve contradictions in previous research and offer practical recommendations for teams and organizations.

中文翻译:

集体智慧的网络结构:小组讨论的或有好处

关于信念形成的研究产生了矛盾的发现,即小组成员之间的交流是否以及何时会提高经济预测、医疗诊断和求职者评估等数字估计的准确性。虽然一些证据表明像“德尔菲法”这样的精心中介的过程比非结构化讨论产生更准确的信念,但其他人认为非结构化讨论优于中介过程。还有一些人认为,独立的个体产生最准确的信念。本文展示了信念形成的网络理论如何解决这些不一致的问题,即使群体缺乏非正式对话中的明显结构。影响的新兴网络结构与讨论前的信念分布相互作用,以调节交流对信念形成的影响。因此,交流有时会增加,有时会降低群体中平均信念的准确性。中介过程和非结构化沟通的效果不同,因此每种沟通形式的相对收益取决于群体动态以及交互前信念的统计特性。这些结果解决了先前研究中的矛盾,并为团队和组织提供了实用的建议。这样,每种通信格式的相对收益取决于群体动态以及交互前信念的统计特性。这些结果解决了先前研究中的矛盾,并为团队和组织提供了实用的建议。这样,每种通信格式的相对收益取决于群体动态以及交互前信念的统计特性。这些结果解决了先前研究中的矛盾,并为团队和组织提供了实用的建议。
更新日期:2020-09-16
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