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A Large-Scale Study of User Image Search Behavior on the Web

Published: 18 April 2015 Publication History

Abstract

In this study, we analyze user image search behavior from a large-scale Yahoo! Image Search query log, based on the hypothesis that behavior is dependent on query type. We categorize queries using two orthogonal taxonomies (subject-based and facet-based) and identify important query types at the intersection of these taxonomies. We study user search behavior on a large-scale set of search sessions for each query type, examining characteristics of sessions, query reformulation patterns, click patterns, and page view patterns. We identify important behavioral differences across query types, in particular showing that some query types are more exploratory, while others correspond to focused search. We also supplement our study with a survey to link the behavioral differences to users' intent. Our findings shed light on the importance of considering query categories to better understand user behavior on image search platforms.

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      cover image ACM Conferences
      CHI '15: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems
      April 2015
      4290 pages
      ISBN:9781450331456
      DOI:10.1145/2702123
      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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      Publication History

      Published: 18 April 2015

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      Author Tags

      1. click analysis
      2. image search
      3. query analysis
      4. search intent
      5. search strategy
      6. user search behavior

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      CHI '15
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      CHI '15: CHI Conference on Human Factors in Computing Systems
      April 18 - 23, 2015
      Seoul, Republic of Korea

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      CHI '15 Paper Acceptance Rate 486 of 2,120 submissions, 23%;
      Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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      Cited By

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      • (2024)Semi-supervised based k-means clustering for classifying social bots in online social network7TH INTERNATIONAL CONFERENCE ON NANOSCIENCE AND NANOTECHNOLOGY10.1063/5.0196132(020021)Online publication date: 2024
      • (2022)Representativeness and face-ism: Gender bias in image searchNew Media & Society10.1177/1461444822110069926:6(3541-3567)Online publication date: 19-Jun-2022
      • (2022)On The Understanding of Customer Purchase Behavior: A Case Study on the Computer Systems E-Commerce Website2022 22nd International Conference on Computational Science and Its Applications (ICCSA)10.1109/ICCSA57511.2022.00013(16-21)Online publication date: Jul-2022
      • (2022)Mapping HCI research methods for studying social media interactionComputers in Human Behavior10.1016/j.chb.2021.107131129:COnline publication date: 1-Apr-2022
      • (2022)ISRE-Framework: nonlinear and multimodal exploration of image search result spacesMultimedia Tools and Applications10.1007/s11042-022-12561-481:19(27275-27308)Online publication date: 25-Mar-2022
      • (2021)The impact of cognitive style on the level of satisfaction and image search behavior in the textual and content search system of Google ImagesAslib Journal of Information Management10.1108/AJIM-04-2021-011674:1(19-36)Online publication date: 28-Sep-2021
      • (2020)Predicting Users’ Revisitation Behaviour Based on Web Access Contextual Clusters2020 8th International Conference on Information and Communication Technology (ICoICT)10.1109/ICoICT49345.2020.9166179(1-6)Online publication date: Jun-2020
      • (2019)Co-learning Multiple Browsing Tendencies of a User by Matrix Factorization-based Multitask LearningIEEE/WIC/ACM International Conference on Web Intelligence10.1145/3350546.3352526(253-257)Online publication date: 14-Oct-2019
      • (2019)Does Diversity Affect User Satisfaction in Image SearchACM Transactions on Information Systems10.1145/332011837:3(1-30)Online publication date: 8-May-2019
      • (2019)On Annotation Methodologies for Image Search EvaluationACM Transactions on Information Systems10.1145/330999437:3(1-32)Online publication date: 27-Mar-2019
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