陷入群体智慧:信息、知识和启发式

Yunwen He, J. Lien, Jie Zheng
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引用次数: 1

摘要

集体知识受到他人观点信息的显著影响。然而,在什么条件下,“群体智慧”对事实信息的了解是有益的还是有害的?在这个实验中,我们给受试者提供了回答50个真实的真假小问题的任务,在从一个独立的会话中获得关于其他受试者答案的不同程度的信息和自我评估的信心水平后,他们有可能有机会修改他们的答案。我们发现,在简单的问题上,关于他人答案的信息会提高表现,但在困难的问题上,往往会损害表现。此外,其他科目提供的答案信息主要是为那些初始知识水平较低的学生提高成绩。中等信息条件下的受试者表现优于低信息条件下或高信息条件下的受试者,这意味着多数原则和最大信心原则相辅相成的社会信息提供的最佳水平。尽管最大置信度规则可以提高性能,在考虑的启发式中产生最低的总体错误率,但受试者通常没有充分利用其他受试者的置信度水平,而倾向于多数规则启发式。这些发现揭示了在网络舆论平台上培养事实知识的政策可能的方向。
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Stuck in the Wisdom of Crowds: Information, Knowledge, and Heuristics
Collective knowledge is significantly affected by information about others’ viewpoints. However, under what conditions does the “wisdom of crowds” help versus harm knowledge of factual information? In this experiment, we present subjects with the task of answering 50 factual true or false trivia questions, with the potential opportunity to revise their answers after receiving different levels of information about other subjects’ answers and self-assessed confidence levels from an independent session. We find that information about others’ answers improves performance on easy questions, but tends to harm performance on difficult questions. In addition, information about answers provided by other subjects mainly improves performance for those with lower initial knowledge levels. Subjects in our Moderate-Information condition outperform those in either the Low or High-Information conditions, implying an optimal level of social information provision, in which the Majority Rule and Maximum Confidence rule complement one another. Although the Maximum Confidence rule can improve performance, yielding the lowest overall error rate out of the heuristics considered, subjects generally underutilize the information on other subjects’ confidence levels in favor of the Majority Rule heuristic. These findings shed light on possible directions for policies that can cultivate factual knowledge on online opinion platforms.
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