Reading News with a Purpose: Explaining User Profiles for Self-Actualization

Emily Sullivan, Dimitrios Bountouridis, Jaron Harambam, Shabnam Najafian, Felicia Loecherbach, Mykola Makhortykh, Domokos Kelen, Daricia Wilkinson, David Graus, Nava Tintarev

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

Abstract

Personalized content provided by recommender systems is an integral part of the current online news reading experience. However, news recommender systems are criticized for their 'black-box' approach to data collection and processing, and for their lack of explainability and transparency. This paper focuses on explaining user profiles constructed from aggregated reading behavior data, used to provide content-based recommendations. The paper makes a first step toward consolidating epistemic values of news providers and news readers. We present an evaluation of an explanation interface reflecting these values, and find that providing users with different goals for self-actualization (i.e., Broaden Horizons vs. Discover the Unexplored) influences their reading intentions for news recommendations.
Original languageEnglish
Title of host publicationACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization
Place of PublicationNew York, NY, USA
PublisherAssociation for Computing Machinery, Inc
Pages241–245
Number of pages5
ISBN (Electronic)9781450367110
ISBN (Print)9781450367110
DOIs
Publication statusPublished - 6 Jun 2019
Externally publishedYes

Keywords

  • Explainability
  • News recommender systems
  • Self-actualization
  • User control
  • User profile

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