research-article

NewsViz: Depicting and Controlling Preference Profiles Using Interactive Treemaps in News Recommender Systems

Authors:

Johannes Kunkel,

Claudia Schwenger,

Jürgen ZieglerAuthors Info & Claims

UMAP '20: Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization

Pages 126 - 135

https://doi.org/10.1145/3340631.3394869

Published: 13 July 2020 Publication History

Abstract

News articles are increasingly consumed digitally and recommender systems (RS) are widely used to personalize news feeds for their users. Thereby, particular concerns about possible biases arise. When RS filter news articles opaquely, they might "trap" their users in filter bubbles. Additionally, user preferences change frequently in the domain of news, which is challenging for automated RS. We argue that both issues can be mitigated by depicting an interactive version of the user's preference profile inside an overview of the entire domain of news articles. To this end, we introduce NewsViz, a RS that visualizes the domain space of online news as treemap, which can interactively be manipulated to personalize a feed of suggested news articles. In a user study (N=63), we compared NewsViz to an interface based on sliders. While both prototypes yielded high results in terms of transparency, recommendation quality and user satisfaction, NewsViz outperformed its counterpart in the perceived degree of control. Structural equation modeling allows us to further uncover hitherto underestimated influences between quality aspects of RS. For instance, we found that the degree of overview of the item domain influenced the perceived quality of recommendations.

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Qian ZFu JZhou Y(2024)Overcoming Barriers, Achieving Goals: A Case Study of an Older User's Technology AutonomyExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3637150(1-7)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3637150
Ziegler JLoepp B(2024)Interactive Recommendation SystemsHandbook of Human Computer Interaction10.1007/978-3-319-27648-9_54-1(1-29)Online publication date: 11-Feb-2024
https://doi.org/10.1007/978-3-319-27648-9_54-1
Liang YPonnada ALamere PDaskalova N(2023)Enabling Goal-Focused Exploration of Podcasts in Interactive Recommender SystemsProceedings of the 28th International Conference on Intelligent User Interfaces10.1145/3581641.3584032(142-155)Online publication date: 27-Mar-2023
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Index Terms

NewsViz: Depicting and Controlling Preference Profiles Using Interactive Treemaps in News Recommender Systems
1. Human-centered computing
  1. Human computer interaction (HCI)
  2. Visualization
    1. Visualization techniques
      1. Treemaps
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Recommender systems

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cover image ACM Conferences

UMAP '20: Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization

July 2020

426 pages

ISBN:9781450368612

DOI:10.1145/3340631

Editors:
Tsvi Kuflik
University of Haifa, Israel
,
Ilaria Torre
University of Genoa, Italy
,
Robin Burke
University of Colorado, Boulder, USA
,
Cristina Gena
University of Turin, Italy

Copyright © 2020 ACM.

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July 14 - 17, 2020

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https://dl.acm.org/doi/10.1145/3613905.3637150
Ziegler JLoepp B(2024)Interactive Recommendation SystemsHandbook of Human Computer Interaction10.1007/978-3-319-27648-9_54-1(1-29)Online publication date: 11-Feb-2024
https://doi.org/10.1007/978-3-319-27648-9_54-1
Liang YPonnada ALamere PDaskalova N(2023)Enabling Goal-Focused Exploration of Podcasts in Interactive Recommender SystemsProceedings of the 28th International Conference on Intelligent User Interfaces10.1145/3581641.3584032(142-155)Online publication date: 27-Mar-2023
https://dl.acm.org/doi/10.1145/3581641.3584032
Madan ANobre C(2023)Visualizing Query Traversals Over Bounding Volume Hierarchies Using Treemaps2023 IEEE Visualization and Visual Analytics (VIS)10.1109/VIS54172.2023.00019(51-55)Online publication date: 21-Oct-2023
https://doi.org/10.1109/VIS54172.2023.00019
Kunkel JZiegler J(2023)A comparative study of item space visualizations for recommender systemsInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2022.102987172:COnline publication date: 9-Mar-2023
https://dl.acm.org/doi/10.1016/j.ijhcs.2022.102987
Guesmi MChatti MTayyar AAin QJoarder S(2022)Interactive Visualizations of Transparent User Models for Self-Actualization: A Human-Centered Design ApproachMultimodal Technologies and Interaction10.3390/mti60600426:6(42)Online publication date: 30-May-2022
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Mattis NMasur PMöller Jvan Atteveldt W(2022)Nudging towards news diversity: A theoretical framework for facilitating diverse news consumption through recommender designNew Media & Society10.1177/1461444822110441326:7(3681-3706)Online publication date: 29-Jun-2022
https://doi.org/10.1177/14614448221104413
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Han CJo JLi ALee BDeussen OWang Y(2022)SizePairs: Achieving Stable and Balanced Temporal Treemaps using Hierarchical Size-based PairingIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.3209450(1-10)Online publication date: 2022
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Liang YWillemsen MHammond TVerbert KParra DKnijnenburg BO'Donovan JTeale P(2021)Interactive Music Genre Exploration with Visualization and Mood ControlProceedings of the 26th International Conference on Intelligent User Interfaces10.1145/3397481.3450700(175-185)Online publication date: 14-Apr-2021
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