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New Tab Page Recommendations Strongly Concentrate Web Browsing to Familiar Sources

Published: 26 June 2019 Publication History

Abstract

To what extent do contemporary web technologies that seek to personalize users' browsing experience trap them in filter bubbles? Existing research has yielded mixed results on the possibility of such influence, but empirical research in this area has been entirely cross-sectional. In this paper, we report results from a longitudinal controlled web experiment conducted to determine whether passive recommendations embedded in common computer user-interfaces (UIs) reinforce users' habitual browsing behaviors, to the detriment of the diversity of the set of pages they tend to visit online. Inspired by classical demonstrations of a part-set cueing effect in memory, our experimental design manipulates the behaviour of the 'New Tab' page for consenting volunteers over a two month-long period in randomized time blocks of equal length. Analysis of their browsing behavior shows that users visit on average 15% fewer unique web pages while their browser's 'New Tab' page displays recommendations based on conventional frequency and recency-based algorithms, than if the display is left blank. This effect is seen systematically for all participants in our study. Further analysis of browsing behavior in this experiment clearly identifies the source of the difference between these modes of browsing: users consistently visit a greater diversity of web pages while typing in URLs in the URL/search bar when there are no recommendations on the 'New Tab' page. Finally, using a simulation study, modelling user behavior as a random walk on a graph, we extracted quantitative predictions about the extent to which discovery of new sources of information may be hindered by the concentration of browsing driven by such personalized 'New Tab' recommendations in classical browser UIs.

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cover image ACM Conferences
WebSci '19: Proceedings of the 10th ACM Conference on Web Science
June 2019
395 pages
ISBN:9781450362023
DOI:10.1145/3292522
Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 26 June 2019

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Author Tags

  1. cognitive science
  2. filter bubble
  3. habitual web browsing
  4. information diet
  5. personalization

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  • Research-article

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  • DST Government of India

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WebSci '19
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WebSci '19: 11th ACM Conference on Web Science
June 30 - July 3, 2019
Massachusetts, Boston, USA

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WebSci '19 Paper Acceptance Rate 41 of 130 submissions, 32%;
Overall Acceptance Rate 245 of 933 submissions, 26%

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