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Understanding User Attention and Engagement in Online News Reading

Authors:

Mounia LalmasAuthors Info & Claims

WSDM '16: Proceedings of the Ninth ACM International Conference on Web Search and Data Mining

Pages 113 - 122

https://doi.org/10.1145/2835776.2835833

Published: 08 February 2016 Publication History

Abstract

Prior work on user engagement with online media identified web page dwell time as a key metric reflecting level of user engagement with online news articles. While on average, dwell time gives a reasonable estimate of user experience with a news article, it is not able to capture important aspects of user interaction with the page, such as how much time a user spends reading the article vs. viewing the comment posted by other users, or the actual proportion of article read by the user. In this paper, we propose a set of user engagement classes along with new user engagement metrics that, unlike dwell time, more accurately reflect user experience with the content. Our user engagement classes provide clear and interpretable taxonomy of user engagement with online news, and are defined based on amount of time user spends on the page, proportion of the article user actually reads and the amount of interaction users performs with the comments. Moreover, we demonstrate that our metrics are relatively easier to predict from the news article content, compared to the dwell time, making optimization of user engagement more attainable goal.

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Cited By

Jangir KSharma VGupta MGrover PTaneja S(2024)Efficiency Boost and AdoptionRobo-Advisors in Management10.4018/979-8-3693-2849-1.ch006(90-103)Online publication date: 28-Jun-2024
https://doi.org/10.4018/979-8-3693-2849-1.ch006
Watson SBenning TMarcon AZhu XCaulfield TSharp RMaster Z(2024)Descriptions of Scientific Evidence and Uncertainty of Unproven COVID-19 Therapies in US News: Content Analysis StudyJMIR Infodemiology10.2196/513284(e51328)Online publication date: 29-Aug-2024
https://doi.org/10.2196/51328
Simonov AValletti TVeiga A(2024)Attention Spillovers from News to Ads: Evidence from an Eye-Tracking ExperimentJournal of Marketing Research10.1177/00222437241256900Online publication date: 2-Aug-2024
https://doi.org/10.1177/00222437241256900
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Index Terms

Understanding User Attention and Engagement in Online News Reading
1. Information systems
  1. World Wide Web
    1. Web applications
    2. Web services

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cover image ACM Conferences

WSDM '16: Proceedings of the Ninth ACM International Conference on Web Search and Data Mining

February 2016

746 pages

ISBN:9781450337168

DOI:10.1145/2835776

General Chairs:
Paul N. Bennett
Microsoft Research
,
Vanja Josifovski
Pinterest
,
Program Chairs:
Jennifer Neville
Purdue University
,
Filip Radlinski
Microsoft

Copyright © 2016 ACM.

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Published: 08 February 2016

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February 22 - 25, 2016

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WSDM '16 Paper Acceptance Rate 67 of 368 submissions, 18%;

Overall Acceptance Rate 498 of 2,863 submissions, 17%

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https://doi.org/10.4018/979-8-3693-2849-1.ch006
Watson SBenning TMarcon AZhu XCaulfield TSharp RMaster Z(2024)Descriptions of Scientific Evidence and Uncertainty of Unproven COVID-19 Therapies in US News: Content Analysis StudyJMIR Infodemiology10.2196/513284(e51328)Online publication date: 29-Aug-2024
https://doi.org/10.2196/51328
Simonov AValletti TVeiga A(2024)Attention Spillovers from News to Ads: Evidence from an Eye-Tracking ExperimentJournal of Marketing Research10.1177/00222437241256900Online publication date: 2-Aug-2024
https://doi.org/10.1177/00222437241256900
Alby T(2024)Bridging the Analytics Gap: Optimizing Content Performance using Actionable Knowledge DiscoveryProceedings of the 35th ACM Conference on Hypertext and Social Media10.1145/3648188.3675121(185-192)Online publication date: 10-Sep-2024
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Omar BNg SIsmail N(2023)Effects of message, medium, and motivational factors on news engagement and mobile news consumption: Evidence from MalaysiaOnline Journal of Communication and Media Technologies10.30935/ojcmt/1311613:3(e202325)Online publication date: 2023
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