Exploring the filter bubble | Proceedings of the 23rd international conference on World wide web (original) (raw)

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

Published: 07 April 2014 Publication History

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.

References

[1]

X. Amatriain and J. Basilico. The net ix tech blog: Net ix recommendations: Beyond the 5 stars (part 1). http://techblog.net ix.com/2012/04/net ix- recommendations-beyond-5-stars.html, visited on 2013-09-06.

[2]

D. Fleder and K. Hosanagar. Blockbuster culture's next rise or fall: The impact of recommender systems on sales diversity. Management Science, 55(5):697--712, May 2009.

[3]

K. Hosanagar, D. M. Fleder, D. Lee, and A. Buja. Will the global village fracture into tribes: Recommender systems and their effects on consumers. SSRN Scholarly Paper ID 1321962, Social Science Research Network, Rochester, NY, Oct. 2012.

[4]

T. Kamba, K. A. Bharat, and M. C. Albers. The krakatoa chronicle-an interactive, personalized newspaper on the web. 1995.

[5]

G. Linden. Eli pariser is wrong. http://glinden.blogspot.com/2011/05/eli-pariser-is-wrong.html, visited on 2013-09--13.

[6]

G. Linden, B. Smith, and J. York. Amazon.com recommendations: item-to-item collaborative filtering.IEEE Internet Computing, 7(1):76--80, 2003.

[7]

M. Marshall. Aggregate knowledge raises $5m from kleiner, on a roll | VentureBeat. http://venturebeat.com/2006/12/10/aggregate-knowledge-raises-5m-from-kleiner-on-a-roll/, visited on 2013-09-06.

[8]

N. Negroponte. 000 000 111 - double agents. http://www.wired.com/wired/archive/3.03/negroponte\_pr.html, visited on 2013-09--13.

[9]

N. Negroponte. Being Digital. Random House LLC, Jan. 1996.

[10]

T. T. Nguyen, D. Kluver, T.-Y. Wang, P.-M. Hui, M. D. Ekstrand, M. C. Willemsen, and J. Riedl. Rating support interfaces to improve user experience and recommender accuracy. To appear in the seventh ACM Recommender System Conference, RecSys 2013, Oct. 2013.

[11]

E. Pariser. The Filter Bubble: What the Internet is Hiding from You. Penguin, Mar. 2012.

[12]

P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, and J. Riedl. GroupLens: an open architecture for collaborative filtering of netnews. In Proceedings of the 1994 ACM conference on Computer supported cooperative work, CSCW '94, pages 175--186, New York, NY, USA, 1994. ACM.

[13]

B. Sarwar, G. Karypis, J. Konstan, and J. Riedl. Item-based collaborative filtering recommendation algorithms. In Proceedings of the 10th international conference on World Wide Web, WWW '01, pages 285--295, New York, NY, USA, 2001. ACM.

[14]

S. Senecal and J. Nantel. The in uence of online product recommendations on consumers" online choices. Journal of Retailing, 80(2):159--169, 2004.

[15]

C. R. Sunstein. Republic.com: XA-GB. ... Princeton University Press, 2002.

[16]

P. E. Tetlock. Expert political judgment: How good is it? How can we know? Princeton University Press, 2005.

[17]

M. Van Alstyne and E. Brynjolfsson. Global village or cyber-balkans? modeling and measuring the integration of electronic communities. Management Science, 51(6):851--868, 2005.

[18]

J. Vig, S. Sen, and J. Riedl. Navigating the tag genome. In Proceedings of the 16th international conference on Intelligent user interfaces, pages 93--102. ACM, 2011.

[19]

J. Vig, S. Sen, and J. Riedl. The tag genome: Encoding community knowledge to support novel interaction. ACM Trans. Interact. Intell. Syst., 2(3):13:1--13:44, Sept. 2012.

[20]

B. Xiao and I. Benbasat. E-commerce product recommendation agents: use, characteristics, and impact. MIS Q., 31(1):137--209, Mar. 2007.

[21]

C.-N. Ziegler, S. M. McNee, J. A. Konstan, and G. Lausen. Improving recommendation lists through topic diversification. In Proceedings of the 14th international conference on World Wide Web, pages n22--32. ACM, 2005.

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Tien T. Nguyen

GroupLens Research, Computer Science and Engineering, University of Minnesota, TwinCities, Minneapolis, MN, USA

Pik-Mai Hui

GroupLens Research, Computer Science and Engineering, University of Minnesota, TwinCities, Minneapolis, MN, USA

F. Maxwell Harper

GroupLens Research, Computer Science and Engineering, University of Minnesota, TwinCities, Minneapolis, MN, USA

Loren Terveen

GroupLens Research, Computer Science and Engineering, University of Minnesota, TwinCities, Minneapolis, MN, USA

Joseph A. Konstan

GroupLens Research, Computer Science and Engineering, University of Minnesota, TwinCities, Minneapolis, MN, USA