Socially-informed sorting for guiding personal finance choices

Graham Dove, Ayanna Seals, Oded Nov

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


Planning for personal financial security is complex, and better-informed investors are likely to make better investment choices. However, the number of alternatives presented by most personal finance platforms pose novices a dual challenge of choice overload coupled with a lack of domain knowledge. We present a study investigating socially-informed sorting, in which users are offered subtle guidance in the form of visual and textual cues that aim to encourage information-seeking when choosing between large numbers of options. We evaluate this approach in an online experiment in which participants go through ten rounds of retirement saving budget allocation, making choices among 77 different funds. While we found that this technique increased novice investors' information-seeking, and offered significant benefit in terms of return performance, it may also be detrimental for more experienced investors. We discuss these findings in light of prior research.

Original languageEnglish (US)
Title of host publicationCHI EA 2020 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450368193
StatePublished - Apr 25 2020
Event2020 ACM CHI Conference on Human Factors in Computing Systems, CHI EA 2020 - Honolulu, United States
Duration: Apr 25 2020Apr 30 2020

Publication series

NameConference on Human Factors in Computing Systems - Proceedings


Conference2020 ACM CHI Conference on Human Factors in Computing Systems, CHI EA 2020
Country/TerritoryUnited States


  • Choice overload
  • Personal finance
  • Social search

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software


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