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From Skimming to Reading: A Two-stage Examination Model for Web Search

Published: 03 November 2014 Publication History

Abstract

User's examination of search results is a key concept involved in all the click models. However, most studies assumed that eye fixation means examination and no further study has been carried out to better understand user's examination behavior. In this study, we design an experimental search engine to collect both the user's feedback on their examinations and the eye-tracking/click-through data. To our surprise, a large proportion (45.8%) of the results fixated by users are not recognized as being "read". Looking into the tracking data, we found that before the user actually "reads" the result, there is often a "skimming" step in which the user quickly looks at the result without reading it. We thus propose a two-stage examination model which composes of a first "from skimming to reading" stage (Stage 1) and a second "from reading to clicking" stage (Stage 2). We found that the biases (e.g. position bias, domain bias, attractiveness bias) considered in many studies impact in different ways in Stage 1 and Stage 2, which suggests that users make judgments according to different signals in different stages. We also show that the two-stage examination behaviors can be predicted with mouse movement behavior, which can be collected at large scale. Relevance estimation with the two-stage examination model also outperforms that with a single-stage examination model. This study shows that the user's examination of search results is a complex cognitive process that needs to be investigated in greater depth and this may have a significant impact on Web search.

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Cited By

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  • (2024)Relevance Feedback with Brain SignalsACM Transactions on Information Systems10.1145/363787442:4(1-37)Online publication date: 9-Feb-2024
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    cover image ACM Conferences
    CIKM '14: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management
    November 2014
    2152 pages
    ISBN:9781450325981
    DOI:10.1145/2661829
    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: 03 November 2014

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    Author Tags

    1. eye tracking
    2. mouse movement
    3. selective attention
    4. web search

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    CIKM '14 Paper Acceptance Rate 175 of 838 submissions, 21%;
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    Cited By

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    • (2024)Relevance Feedback with Brain SignalsACM Transactions on Information Systems10.1145/363787442:4(1-37)Online publication date: 9-Feb-2024
    • (2023)RankFormer: Listwise Learning-to-Rank Using Listwide LabelsProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599892(3762-3773)Online publication date: 6-Aug-2023
    • (2023)A Passage-Level Reading Behavior Model for Mobile SearchProceedings of the ACM Web Conference 202310.1145/3543507.3583343(3236-3246)Online publication date: 30-Apr-2023
    • (2023)Behavior Modeling for Point of Interest SearchProceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3539618.3591955(1843-1847)Online publication date: 19-Jul-2023
    • (2023)Mouse tracking and consumer experience: exploring the associations between mouse movements, consumer emotions, brand awareness and purchase intentBehaviour & Information Technology10.1080/0144929X.2023.223502443:10(1924-1937)Online publication date: 13-Jul-2023
    • (2022)LBDProceedings of the 36th International Conference on Neural Information Processing Systems10.5555/3600270.3602690(33400-33413)Online publication date: 28-Nov-2022
    • (2022)Scalar is Not EnoughProceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3534678.3539468(136-145)Online publication date: 14-Aug-2022
    • (2022)Brain Topography Adaptive Network for Satisfaction Modeling in Interactive Information Access SystemProceedings of the 30th ACM International Conference on Multimedia10.1145/3503161.3548258(90-100)Online publication date: 10-Oct-2022
    • (2022)The Dark Side of Relevance: The Effect of Non-Relevant Results on Search BehaviorProceedings of the 2022 Conference on Human Information Interaction and Retrieval10.1145/3498366.3505770(1-11)Online publication date: 14-Mar-2022
    • (2022)Axiomatically Regularized Pre-training for Ad hoc SearchProceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3477495.3531943(1524-1534)Online publication date: 6-Jul-2022
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