Department of Psychology.
J Pers Soc Psychol. 2013 Dec;105(6):909-20. doi: 10.1037/a0033183.
How does the acquisition of information about a person affect the liking of that person? A recent set of studies suggests that liking decreases as people acquire more information (Norton, Frost, & Ariely, 2007). We test this "less-is-more" hypothesis along with an alternative hypothesis based on information integration theory. According to this alternative, people average available person information in an unbiased manner so that the liking of a person described by a random sample of any number of traits from a trait universe approximates the degree of liking that would be obtained if all trait information were known. The correlation between liking and the number of traits should be zero. We present the results of computer simulation and 2 empirical person-judgment studies. Using Bayesian analyses, we find that the evidence is more consistent with the information-integration hypothesis than with the "less-is-more" hypothesis.
人们获取关于某个人的信息会如何影响他们对这个人的喜欢程度？最近的一系列研究表明，随着人们获取更多的信息，他们对某个人的喜欢程度会降低（Norton、Frost 和 Ariely，2007）。我们检验了“少即是多”的假设，以及基于信息整合理论的另一种假设。根据这一替代假设，人们会以无偏差的方式对可获得的个人信息进行平均，因此，一个人所描述的喜欢程度，如果从特质宇宙中随机抽取任何数量的特质，就会接近如果所有特质信息都已知时所获得的喜欢程度。喜欢程度和特质数量之间的相关性应该为零。我们展示了计算机模拟和 2 项实证人格判断研究的结果。使用贝叶斯分析，我们发现，证据更符合信息整合假设，而不是“少即是多”假设。
