The Immunity of Users’ Item Selection from Serial Position Effects in Multi-Attribute Item Recommendation Scenarios

Trang Tran, Carmen Isabella Baumann, Alexander Felfernig, Viet-Man Le

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Abstract

Serial position effects are triggered in recommendation scenarios where users focus on evaluating items shown at the beginning and at the end of a list. In this paper, we analyze these effects in the context of multi-attribute item recommendation scenarios where the recommended items are presented to users in the form of a list of relevant attributes. We conducted a user study in different item domains to examine if the item selection of users is affected by the order of the attributes of the recommended items presented to them. The experimental results show that the order of the attributes does not affect users’ item selection. When selecting a recommended item, users tend to focus on evaluating the value of the attributes that reflect their preferences for the desired item but do not care about the order of the attributes. This finding brings us to a conclusion that in the context of multi-attribute item recommendation scenarios, the selection of a recommended item from a list of candidate items is immune to serial position effects.
Original languageEnglish
Title of host publicationProceedings of the 8th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2021), Online Event, September 25 and September 29, 2021.
Subtitle of host publicationco-located with 15th ACM Conference on Recommender Systems (RecSys 2021)
EditorsPeter Brusilovsky, Marco de Gemmis, Alexander Felfernig, Elisabeth Lex, Pasquale Lops, Giovanni Semeraro, Martijn C. Willemsen
Pages101-111
Number of pages11
Volume2948
Publication statusPublished - 20 Sep 2021
Event8th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems: co-located with 15th ACM Conference on Recommender Systems (RecSys 2021) - Amsterdam, Netherlands, Amsterdam, Netherlands
Duration: 25 Sep 202129 Sep 2021
https://recsys.acm.org/recsys21/intrs/

Publication series

NameCEUR Workshop Proceedings
Volume2948
ISSN (Electronic)1613-0073

Workshop

Workshop8th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems
Abbreviated titleIntRS 2021
Country/TerritoryNetherlands
CityAmsterdam
Period25/09/2129/09/21
Internet address

Keywords

  • Decision biases
  • Human decision making
  • Item selection
  • Multi-attribute items
  • Recommender systems
  • Serial position effects

ASJC Scopus subject areas

  • Computer Science(all)

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