Fragmented Visual Attention in Web Browsing: Weibull Analysis of Item Visit Times

Aini Putkonen; Aurélien Nioche; Markku Laine; Crista Kuuramo; Antti Oulasvirta

doi:10.1007/978-3-031-28238-6_5

Fragmented Visual Attention in Web Browsing: Weibull Analysis of Item Visit Times

Aini Putkonen^*, Aurélien Nioche, Markku Laine, Crista Kuuramo, Antti Oulasvirta

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

3 Citations (Scopus)

64 Downloads (Pure)

Abstract

Users often browse the web in an exploratory way, inspecting what they find interesting without a specific goal. However, the temporal dynamics of visual attention during such sessions, emerging when users gaze from one item to another, are not well understood. In this paper, we examine how people distribute visual attention among content items when browsing news. Distribution of visual attention is studied in a controlled experiment, wherein eye-tracking data and web logs are collected for 18 participants exploring newsfeeds in a single- and multi-column layout. Behavior is modeled using Weibull analysis of item (article) visit times, which describes these visits via quantities like durations and frequencies of switching focused item. Bayesian inference is used to quantify uncertainty. The results suggest that visual attention in browsing is fragmented, and affected by the number, properties and composition of the items visible on the viewport. We connect these findings to previous work explaining information-seeking behavior through cost-benefit judgments.

Original language	English
Title of host publication	Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Proceedings
Editors	Jaap Kamps, Lorraine Goeuriot, Fabio Crestani, Maria Maistro, Hideo Joho, Brian Davis, Cathal Gurrin, Annalina Caputo, Udo Kruschwitz
Publisher	Springer
Pages	62-78
Number of pages	17
ISBN (Electronic)	978-3-031-28238-6
ISBN (Print)	978-3-031-28237-9
DOIs	https://doi.org/10.1007/978-3-031-28238-6_5
Publication status	Published - 2023
MoE publication type	A4 Conference publication
Event	European Conference on Information Retrieval - Dublin, Ireland Duration: 2 Apr 2023 → 6 Apr 2023

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13981 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	European Conference on Information Retrieval
Abbreviated title	ECIR
Country/Territory	Ireland
City	Dublin
Period	02/04/2023 → 06/04/2023

Keywords

Eye-tracking
Newsfeeds
Visual attention
Web browsing

Access to Document

10.1007/978-3-031-28238-6_5Licence: CC BY

978-3-031-28238-6_5Final published version, 12.6 MBLicence: CC BY

Cite this

Putkonen, A., Nioche, A., Laine, M., Kuuramo, C., & Oulasvirta, A. (2023). Fragmented Visual Attention in Web Browsing: Weibull Analysis of Item Visit Times. In J. Kamps, L. Goeuriot, F. Crestani, M. Maistro, H. Joho, B. Davis, C. Gurrin, A. Caputo, & U. Kruschwitz (Eds.), Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Proceedings (pp. 62-78). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13981 LNCS). Springer. https://doi.org/10.1007/978-3-031-28238-6_5

Putkonen, Aini ; Nioche, Aurélien ; Laine, Markku et al. / Fragmented Visual Attention in Web Browsing : Weibull Analysis of Item Visit Times. Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Proceedings. editor / Jaap Kamps ; Lorraine Goeuriot ; Fabio Crestani ; Maria Maistro ; Hideo Joho ; Brian Davis ; Cathal Gurrin ; Annalina Caputo ; Udo Kruschwitz. Springer, 2023. pp. 62-78 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{2a6cb0acc7b94d138fd44147360efb0a,

title = "Fragmented Visual Attention in Web Browsing: Weibull Analysis of Item Visit Times",

abstract = "Users often browse the web in an exploratory way, inspecting what they find interesting without a specific goal. However, the temporal dynamics of visual attention during such sessions, emerging when users gaze from one item to another, are not well understood. In this paper, we examine how people distribute visual attention among content items when browsing news. Distribution of visual attention is studied in a controlled experiment, wherein eye-tracking data and web logs are collected for 18 participants exploring newsfeeds in a single- and multi-column layout. Behavior is modeled using Weibull analysis of item (article) visit times, which describes these visits via quantities like durations and frequencies of switching focused item. Bayesian inference is used to quantify uncertainty. The results suggest that visual attention in browsing is fragmented, and affected by the number, properties and composition of the items visible on the viewport. We connect these findings to previous work explaining information-seeking behavior through cost-benefit judgments.",

keywords = "Eye-tracking, Newsfeeds, Visual attention, Web browsing",

author = "Aini Putkonen and Aur{\'e}lien Nioche and Markku Laine and Crista Kuuramo and Antti Oulasvirta",

note = "Funding Information: Acknowledgements. This work was supported by the Finnish Center for Artificial Intelligence (FCAI), Business Finland (MINERAL project), the Academy of Finland (projects Human Automata – ID: 328813, and BAD – ID: 318559), as well as the Technology Industries of Finland (project SOWP). We would also like to thank the reviewers for their feedback. Publisher Copyright: {\textcopyright} 2023, The Author(s).; European Conference on Information Retrieval, ECIR ; Conference date: 02-04-2023 Through 06-04-2023",

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doi = "10.1007/978-3-031-28238-6_5",

language = "English",

isbn = "978-3-031-28237-9",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

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editor = "Jaap Kamps and Lorraine Goeuriot and Fabio Crestani and Maria Maistro and Hideo Joho and Brian Davis and Cathal Gurrin and Annalina Caputo and Udo Kruschwitz",

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address = "Germany",

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Putkonen, A, Nioche, A, Laine, M, Kuuramo, C & Oulasvirta, A 2023, Fragmented Visual Attention in Web Browsing: Weibull Analysis of Item Visit Times. in J Kamps, L Goeuriot, F Crestani, M Maistro, H Joho, B Davis, C Gurrin, A Caputo & U Kruschwitz (eds), Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13981 LNCS, Springer, pp. 62-78, European Conference on Information Retrieval, Dublin, Ireland, 02/04/2023. https://doi.org/10.1007/978-3-031-28238-6_5

Fragmented Visual Attention in Web Browsing: Weibull Analysis of Item Visit Times. / Putkonen, Aini; Nioche, Aurélien; Laine, Markku et al.
Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Proceedings. ed. / Jaap Kamps; Lorraine Goeuriot; Fabio Crestani; Maria Maistro; Hideo Joho; Brian Davis; Cathal Gurrin; Annalina Caputo; Udo Kruschwitz. Springer, 2023. p. 62-78 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13981 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Fragmented Visual Attention in Web Browsing

T2 - European Conference on Information Retrieval

AU - Putkonen, Aini

AU - Nioche, Aurélien

AU - Laine, Markku

AU - Kuuramo, Crista

AU - Oulasvirta, Antti

N1 - Funding Information: Acknowledgements. This work was supported by the Finnish Center for Artificial Intelligence (FCAI), Business Finland (MINERAL project), the Academy of Finland (projects Human Automata – ID: 328813, and BAD – ID: 318559), as well as the Technology Industries of Finland (project SOWP). We would also like to thank the reviewers for their feedback. Publisher Copyright: © 2023, The Author(s).

PY - 2023

Y1 - 2023

N2 - Users often browse the web in an exploratory way, inspecting what they find interesting without a specific goal. However, the temporal dynamics of visual attention during such sessions, emerging when users gaze from one item to another, are not well understood. In this paper, we examine how people distribute visual attention among content items when browsing news. Distribution of visual attention is studied in a controlled experiment, wherein eye-tracking data and web logs are collected for 18 participants exploring newsfeeds in a single- and multi-column layout. Behavior is modeled using Weibull analysis of item (article) visit times, which describes these visits via quantities like durations and frequencies of switching focused item. Bayesian inference is used to quantify uncertainty. The results suggest that visual attention in browsing is fragmented, and affected by the number, properties and composition of the items visible on the viewport. We connect these findings to previous work explaining information-seeking behavior through cost-benefit judgments.

AB - Users often browse the web in an exploratory way, inspecting what they find interesting without a specific goal. However, the temporal dynamics of visual attention during such sessions, emerging when users gaze from one item to another, are not well understood. In this paper, we examine how people distribute visual attention among content items when browsing news. Distribution of visual attention is studied in a controlled experiment, wherein eye-tracking data and web logs are collected for 18 participants exploring newsfeeds in a single- and multi-column layout. Behavior is modeled using Weibull analysis of item (article) visit times, which describes these visits via quantities like durations and frequencies of switching focused item. Bayesian inference is used to quantify uncertainty. The results suggest that visual attention in browsing is fragmented, and affected by the number, properties and composition of the items visible on the viewport. We connect these findings to previous work explaining information-seeking behavior through cost-benefit judgments.

KW - Eye-tracking

KW - Newsfeeds

KW - Visual attention

KW - Web browsing

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U2 - 10.1007/978-3-031-28238-6_5

DO - 10.1007/978-3-031-28238-6_5

M3 - Conference article in proceedings

AN - SCOPUS:85150975430

SN - 978-3-031-28237-9

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 62

EP - 78

BT - Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Proceedings

A2 - Kamps, Jaap

A2 - Goeuriot, Lorraine

A2 - Crestani, Fabio

A2 - Maistro, Maria

A2 - Joho, Hideo

A2 - Davis, Brian

A2 - Gurrin, Cathal

A2 - Caputo, Annalina

A2 - Kruschwitz, Udo

PB - Springer

Y2 - 2 April 2023 through 6 April 2023

ER -

Putkonen A, Nioche A, Laine M, Kuuramo C, Oulasvirta A. Fragmented Visual Attention in Web Browsing: Weibull Analysis of Item Visit Times. In Kamps J, Goeuriot L, Crestani F, Maistro M, Joho H, Davis B, Gurrin C, Caputo A, Kruschwitz U, editors, Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Proceedings. Springer. 2023. p. 62-78. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-28238-6_5

Fragmented Visual Attention in Web Browsing: Weibull Analysis of Item Visit Times

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Human Automata: Simulator-based Methods for Collaborative AI

MINERAL: Machine Insight for Behavioral Analytics

-: Bayesian Artefact Design

Cite this

Fragmented Visual Attention in Web Browsing: Weibull Analysis of Item Visit Times

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Projects

Human Automata: Simulator-based Methods for Collaborative AI

MINERAL: Machine Insight for Behavioral Analytics

-: Bayesian Artefact Design

Cite this