The Love of Large Numbers: A Popularity Bias in Consumer Choice

Derek Powell, Jingqi Yu, Melissa DeWolf, Keith J. Holyoak

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Social learning—the ability to learn from observing the decisions of other people and the outcomes of those decisions—is fundamental to human evolutionary and cultural success. The Internet now provides social evidence on an unprecedented scale. However, properly utilizing this evidence requires a capacity for statistical inference. We examined how people’s interpretation of online review scores is influenced by the numbers of reviews—a potential indicator both of an item’s popularity and of the precision of the average review score. Our task was designed to pit statistical information against social information. We modeled the behavior of an “intuitive statistician” using empirical prior information from millions of reviews posted on Amazon.com and then compared the model’s predictions with the behavior of experimental participants. Under certain conditions, people preferred a product with more reviews to one with fewer reviews even though the statistical model indicated that the latter was likely to be of higher quality than the former. Overall, participants’ judgments suggested that they failed to make meaningful statistical inferences.

Original languageEnglish (US)
Pages (from-to)1432-1442
Number of pages11
JournalPsychological Science
Volume28
Issue number10
DOIs
StatePublished - Oct 1 2017
Externally publishedYes

Keywords

  • decision making
  • heuristics
  • open data
  • open materials
  • popularity
  • sample size

ASJC Scopus subject areas

  • Psychology(all)

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