Exploring the filter bubble: The effect of using recommender systems on content diversity

Tien T. Nguyen, Pik Mai Hui, F. Maxwell Harper, Loren Terveen, Joseph A. Konstan

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

179 Scopus citations

Abstract

Eli Pariser coined the term 'filter bubble' to describe the potential for online personalization to effectively isolate people from a diversity of viewpoints or content. Online recommender systems - built on algorithms that attempt to predict which items users will most enjoy consuming - are one family of technologies that potentially suffers from this effect. Because recommender systems have become so prevalent, it is important to investigate their impact on users in these terms. This paper examines the longitudinal impacts of a collaborative filtering-based recommender system on users. To the best of our knowledge, it is the first paper to measure the filter bubble effect in terms of content diversity at the individual level. We contribute a novel metric to measure content diversity based on information encoded in user-generated tags, and we present a new set of methods to examine the temporal effect of recommender systems on the user experience. We do find that recommender systems expose users to a slightly narrowing set of items over time. However, we also see evidence that users who actually consume the items recommended to them experience lessened narrowing effects and rate items more positively. Copyright is held by the International World Wide Web Conference Committee (IW3C2).

Original languageEnglish (US)
Title of host publicationWWW 2014 - Proceedings of the 23rd International Conference on World Wide Web
PublisherAssociation for Computing Machinery
Pages677-686
Number of pages10
ISBN (Electronic)9781450327442
DOIs
StatePublished - Apr 7 2014
Event23rd International Conference on World Wide Web, WWW 2014 - Seoul, Korea, Republic of
Duration: Apr 7 2014Apr 11 2014

Publication series

NameWWW 2014 - Proceedings of the 23rd International Conference on World Wide Web

Other

Other23rd International Conference on World Wide Web, WWW 2014
Country/TerritoryKorea, Republic of
CitySeoul
Period4/7/144/11/14

Keywords

  • Content diversity
  • Filter bubble
  • Longitudinal data
  • Recommender system
  • Tag-genome
  • User experience

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