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Evaluating user behavior and strategy during visual exploration

Authors:

Andrew E. Johnson,

Michael E. PapkaAuthors Info & Claims

BELIV '14: Proceedings of the Fifth Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization

Pages 41 - 45

https://doi.org/10.1145/2669557.2669575

Published: 10 November 2014 Publication History

Abstract

Visualization practitioners have traditionally focused on evaluating the outcome of the visual analytic process, as opposed to studying how that process unfolds. Since user strategy would likely influence the outcome of visual analysis and the nature of insights acquired, it is important to understand how the analytic behavior of users is shaped by variations in the design of the visualization interface. This paper presents a technique for evaluating user behavior in exploratory visual analysis scenarios. We characterize visual exploration as a fluid activity involving transitions between mental and interaction states. We show how micro-patterns in these transitions can be captured and analyzed quantitatively to reveal differences in the exploratory behavior of users, given variations in the visualization interface.

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Cited By

Rae IZhou FBilsing MBunge P(2022)Understanding Visual Investigation Patterns Through Digital “Field” ObservationsProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3517445(1-16)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3517445
Koonchanok RBaser PSikharam ARaveendranath NReda KKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)Data Prophecy: Exploring the Effects of Belief Elicitation in Visual AnalyticsProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445798(1-12)Online publication date: 6-May-2021
https://dl.acm.org/doi/10.1145/3411764.3445798
Doppler Haider JGastecker BPohl MSeidler PKodagoda NWong B(2018)Sense-making strategies in explorative intelligence analysis of network evolutionsBehaviour & Information Technology10.1080/0144929X.2018.1519036(1-18)Online publication date: 11-Sep-2018
https://doi.org/10.1080/0144929X.2018.1519036
Show More Cited By

Index Terms

Evaluating user behavior and strategy during visual exploration
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods

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Information & Contributors

Information

Published In

cover image ACM Other conferences

BELIV '14: Proceedings of the Fifth Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization

November 2014

184 pages

ISBN:9781450332095

DOI:10.1145/2669557

Editors:
Heidi Lam
Google Inc.
,
Petra Isenberg
INRIA, France
,
Tobias Isenberg
INRIA, France
,
Michael Sedlmair
University of Vienna, Austria

Copyright © 2014 ACM.

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 the author(s) 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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 November 2014

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U.S. Department of Energy

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BELIV '14

BELIV '14: Novel Evaluation Methods For Visualization 2014

November 10, 2014

Paris, France

Acceptance Rates

BELIV '14 Paper Acceptance Rate 23 of 30 submissions, 77%;

Overall Acceptance Rate 45 of 64 submissions, 70%

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Cited By

Rae IZhou FBilsing MBunge P(2022)Understanding Visual Investigation Patterns Through Digital “Field” ObservationsProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3517445(1-16)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3517445
Koonchanok RBaser PSikharam ARaveendranath NReda KKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)Data Prophecy: Exploring the Effects of Belief Elicitation in Visual AnalyticsProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445798(1-12)Online publication date: 6-May-2021
https://dl.acm.org/doi/10.1145/3411764.3445798
Doppler Haider JGastecker BPohl MSeidler PKodagoda NWong B(2018)Sense-making strategies in explorative intelligence analysis of network evolutionsBehaviour & Information Technology10.1080/0144929X.2018.1519036(1-18)Online publication date: 11-Sep-2018
https://doi.org/10.1080/0144929X.2018.1519036
Islam JWilliam Wong BXu K(2018)Analytic Provenance as Constructs of Behavioural Markers for Externalizing Thinking Processes in Criminal Intelligence AnalysisCommunity-Oriented Policing and Technological Innovations10.1007/978-3-319-89294-8_10(95-105)Online publication date: 27-Apr-2018
https://doi.org/10.1007/978-3-319-89294-8_10
Pohl MDoppler Haider J(2017)Sense-making Strategies for the Interpretation of Visualizations—Bridging the Gap between Theory and Empirical ResearchMultimodal Technologies and Interaction10.3390/mti10300161:3(16)Online publication date: 26-Jul-2017
https://doi.org/10.3390/mti1030016
Islam JWong B(2017)Behavioural Markers: Bridging the Gap between Art of Analysis and Science of Analytics in Criminal Intelligence2017 European Intelligence and Security Informatics Conference (EISIC)10.1109/EISIC.2017.30(147-150)Online publication date: Sep-2017
https://doi.org/10.1109/EISIC.2017.30
Beck FBlascheck TErtl TWeiskopf D(2017)Word-Sized Eye-Tracking VisualizationsEye Tracking and Visualization10.1007/978-3-319-47024-5_7(113-128)Online publication date: 4-Feb-2017
https://doi.org/10.1007/978-3-319-47024-5_7
ElTayeby ODou W(2016)A Survey on Interaction Log Analysis for Evaluating Exploratory VisualizationsProceedings of the Sixth Workshop on Beyond Time and Errors on Novel Evaluation Methods for Visualization10.1145/2993901.2993912(62-69)Online publication date: 24-Oct-2016
https://dl.acm.org/doi/10.1145/2993901.2993912
Blascheck TJohn MKoch SBruder LErtl TQvarfordt PHansen D(2016)Triangulating user behavior using eye movement, interaction, and think aloud dataProceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications10.1145/2857491.2857523(175-182)Online publication date: 14-Mar-2016
https://dl.acm.org/doi/10.1145/2857491.2857523
Blascheck TBeck FBaltes SErtl TWeiskopf D(2016)Visual analysis and coding of data-rich user behavior2016 IEEE Conference on Visual Analytics Science and Technology (VAST)10.1109/VAST.2016.7883520(141-150)Online publication date: Oct-2016
https://doi.org/10.1109/VAST.2016.7883520
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