To switch or not to switch: Understanding social influence in online choices

Haiyi Zhu, Bernardo A. Huberman, Yarun Luon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

25 Scopus citations

Abstract

We designed and ran an experiment to measure social influence in online recommender systems, specifically how often people's choices are changed by others' recommendations when facing different levels of confirmation and conformity pressures. In our experiment participants were first asked to provide their preferences between pairs of items. They were then asked to make second choices about the same pairs with knowledge of others' preferences. Our results show that others people's opinions significantly sway people's own choices. The influence is stronger when people are required to make their second decision sometime later (22.4%) than immediately (14.1%). Moreover, people seem to be most likely to reverse their choices when facing a moderate, as opposed to large, number of opposing opinions. Finally, the time people spend making the first decision significantly predicts whether they will reverse their decisions later on, while demographics such as age and gender do not. These results have implications for consumer behavior research as well as online marketing strategies.

Original languageEnglish (US)
Title of host publicationConference Proceedings - The 30th ACM Conference on Human Factors in Computing Systems, CHI 2012
Pages2257-2266
Number of pages10
DOIs
StatePublished - May 24 2012
Event30th ACM Conference on Human Factors in Computing Systems, CHI 2012 - Austin, TX, United States
Duration: May 5 2012May 10 2012

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Other

Other30th ACM Conference on Human Factors in Computing Systems, CHI 2012
CountryUnited States
CityAustin, TX
Period5/5/125/10/12

Keywords

  • Online choices
  • Recommender systems
  • Social influence

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