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Does clustered presentation lead readers to diverse selections?

Authors:

Sidharth Chhabra,

Paul ResnickAuthors Info & Claims

CHI EA '13: CHI '13 Extended Abstracts on Human Factors in Computing Systems

Pages 1689 - 1694

https://doi.org/10.1145/2468356.2468659

Published: 27 April 2013 Publication History

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Abstract

A recent study found that presenting news suggestions as clusters in a sidebar can lead to more exploration of articles and clusters related to particular stories [1]. We conducted a lab study to test the robustness of the result.Our results only partially replicate the original findings: people read more articles, but not from significantly more clusters;we also foundthat they prefer the clustered presentation. Further research is needed to better understand the conditions under which clustered presentation leads people to sample from more clusters.

References

[1]

Park, S., et al., NewsCube: delivering multiple aspects of news to mitigate media bias, in Proceedings of the 27th international conference on Human factors in computing systems2009, ACM: Boston, MA, USA. p. 443--452.

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Garrett, R.K. and P. Resnick, Resisting Political Fragmentation on the Internet. Daedalus, 2011. 140(4): p. 108--120.

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Cited By

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Epstein RRobertson RLazer DWilson C(2017)Suppressing the Search Engine Manipulation Effect (SEME)Proceedings of the ACM on Human-Computer Interaction10.1145/31346771:CSCW(1-22)Online publication date: 6-Dec-2017
https://dl.acm.org/doi/10.1145/3134677
Graells-Garrido ELalmas MBaeza-Yates RNichols JMahmud JO'Donovan JConati CZancanaro M(2016)Data Portraits and Intermediary TopicsProceedings of the 21st International Conference on Intelligent User Interfaces10.1145/2856767.2856776(228-240)Online publication date: 7-Mar-2016
https://dl.acm.org/doi/10.1145/2856767.2856776
Desarkar MShinde N(2014)Diversification in news recommendation for privacy concerned users2014 International Conference on Data Science and Advanced Analytics (DSAA)10.1109/DSAA.2014.7058064(135-141)Online publication date: Oct-2014
https://doi.org/10.1109/DSAA.2014.7058064

Index Terms

Does clustered presentation lead readers to diverse selections?
1. Human-centered computing

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CHI EA '13: CHI '13 Extended Abstracts on Human Factors in Computing Systems

April 2013

3360 pages

ISBN:9781450319522

DOI:10.1145/2468356

General Chair:
Wendy E. Mackay
INRIA
,
Program Chairs:
Stephen Brewster
Glasgow University
,
Susanne Bødker
University of Aarhus

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

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Published: 27 April 2013

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April 27 - May 2, 2013

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CHI EA '13 Paper Acceptance Rate 630 of 1,963 submissions, 32%;

Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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Epstein RRobertson RLazer DWilson C(2017)Suppressing the Search Engine Manipulation Effect (SEME)Proceedings of the ACM on Human-Computer Interaction10.1145/31346771:CSCW(1-22)Online publication date: 6-Dec-2017
https://dl.acm.org/doi/10.1145/3134677
Graells-Garrido ELalmas MBaeza-Yates RNichols JMahmud JO'Donovan JConati CZancanaro M(2016)Data Portraits and Intermediary TopicsProceedings of the 21st International Conference on Intelligent User Interfaces10.1145/2856767.2856776(228-240)Online publication date: 7-Mar-2016
https://dl.acm.org/doi/10.1145/2856767.2856776
Desarkar MShinde N(2014)Diversification in news recommendation for privacy concerned users2014 International Conference on Data Science and Advanced Analytics (DSAA)10.1109/DSAA.2014.7058064(135-141)Online publication date: Oct-2014
https://doi.org/10.1109/DSAA.2014.7058064

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Recommendations

CubeThat: news article recommender

A clustering-ranking method for many-objective optimization

Removing Bias from Diverse Data Clusters for Ensemble Classification

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