research-article

On cognition, emotion, and interaction aspects of search tasks with different search intentions

Authors:

Yashar Moshfeghi,

Joemon M. JoseAuthors Info & Claims

WWW '13: Proceedings of the 22nd international conference on World Wide Web

Pages 931 - 942

https://doi.org/10.1145/2488388.2488469

Published: 13 May 2013 Publication History

Abstract

The complex and dynamic nature of search processes surrounding information seeking have been exhaustively studied. Recent studies have highlighted search processes with different intentions, such as those for entertainment purposes or re-finding a visited information object, are fundamentally different in nature to typical information seeking intentions. Despite the popularity of such search processes on the Web, they have not yet been thoroughly explored. Using a video retrieval system as a use case, we study the characteristics of four different search task types: seeking information, re-finding a particular information object, and two different entertainment intentions (i.e. entertainment by adjusting arousal level, and entertainment by adjusting mood). In particular, we looked at the cognition, emotion and action aspects of these search tasks at different phases of a search process. This follows the common assumption in the information seeking and retrieval community that a complex search process can be broken down into a relatively small number of activity phases. Our experimental results show significant differences in the characteristics of studied search tasks. Furthermore, we investigate whether we can predict these search tasks given user's interaction with the system. Results show that we can learn a model that predicts the search task types with reasonable accuracy. Overall, these findings may help to steer search engines to better satisfy searchers' needs beyond typically assumed information seeking processes.

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Cited By

Ji KHettiachchi DSalim FScholer FSpina DHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Characterizing Information Seeking Processes with Multiple Physiological SignalsProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657793(1006-1017)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657793
Ye ZXie XAi QLiu YWang ZSu WZhang M(2023)Relevance Feedback with Brain SignalsACM Transactions on Information Systems10.1145/363787442:4(1-37)Online publication date: 18-Dec-2023
https://dl.acm.org/doi/10.1145/3637874
Milton APera M(2023)Into the Unknown: Exploration of Search Engines’ Responses to Users with Depression and AnxietyACM Transactions on the Web10.1145/358028317:4(1-29)Online publication date: 11-Jul-2023
https://dl.acm.org/doi/10.1145/3580283
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Index Terms

On cognition, emotion, and interaction aspects of search tasks with different search intentions
1. Information systems
  1. Information retrieval
    1. Information retrieval query processing

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cover image ACM Other conferences

WWW '13: Proceedings of the 22nd international conference on World Wide Web

May 2013

1628 pages

ISBN:9781450320351

DOI:10.1145/2488388

General Chairs:
Daniel Schwabe
PUC-Rio - Brazil
,
Virgílio Almeida
UFMG - Brazil
,
Hartmut Glaser
CGI.br - Brazil
,
Program Chairs:
Ricardo Baeza-Yates
Yahoo! Labs - Spain & Chile
,
Sue Moon
KAIST - South Korea

Copyright © 2013 Copyright is held by the International World Wide Web Conference Committee (IW3C2).

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NICBR: Nucleo de Informatcao e Coordenacao do Ponto BR
CGIBR: Comite Gestor da Internet no Brazil

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

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Published: 13 May 2013

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WWW '13: 22nd International World Wide Web Conference

May 13 - 17, 2013

Rio de Janeiro, Brazil

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WWW '13 Paper Acceptance Rate 125 of 831 submissions, 15%;

Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Ji KHettiachchi DSalim FScholer FSpina DHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Characterizing Information Seeking Processes with Multiple Physiological SignalsProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657793(1006-1017)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657793
Ye ZXie XAi QLiu YWang ZSu WZhang M(2023)Relevance Feedback with Brain SignalsACM Transactions on Information Systems10.1145/363787442:4(1-37)Online publication date: 18-Dec-2023
https://dl.acm.org/doi/10.1145/3637874
Milton APera M(2023)Into the Unknown: Exploration of Search Engines’ Responses to Users with Depression and AnxietyACM Transactions on the Web10.1145/358028317:4(1-29)Online publication date: 11-Jul-2023
https://dl.acm.org/doi/10.1145/3580283
Ruthven I(2022)ReferencesDealing With Change Through Information Sculpting10.1108/978-1-80382-047-720221013(193-259)Online publication date: 21-Jul-2022
https://doi.org/10.1108/978-1-80382-047-720221013
Jaiswal ALiu HFrommholz IHasibi FFang YAizawa A(2021)Semantic Hilbert Space for Interactive Image RetrievalProceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3471158.3472253(307-315)Online publication date: 11-Jul-2021
https://dl.acm.org/doi/10.1145/3471158.3472253
Déneckère RKornyshova EHug C(2021)A Framework for Comparative Analysis of Intention Mining ApproachesResearch Challenges in Information Science10.1007/978-3-030-75018-3_2(20-37)Online publication date: 8-May-2021
https://doi.org/10.1007/978-3-030-75018-3_2
Landoni MPera MMurgia EHuibers T(2020)Inside Out: Exploring the Emotional Side of Search Engines in the ClassroomProceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3340631.3394847(136-144)Online publication date: 7-Jul-2020
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Salutari FHora DDubuc GRossi D(2020)Analyzing Wikipedia Users’ Perceived Quality of Experience: A Large-Scale StudyIEEE Transactions on Network and Service Management10.1109/TNSM.2020.297868517:2(1082-1095)Online publication date: Jun-2020
https://doi.org/10.1109/TNSM.2020.2978685
Kazai GThomas PCraswell NPiwowarski BChevalier MGaussier EMaarek YNie JScholer F(2019)The Emotion Profile of Web SearchProceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3331184.3331314(1097-1100)Online publication date: 18-Jul-2019
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Moshfeghi YTriantafillou PPollick F(2019)Towards Predicting a Realisation of an Information Need based on Brain SignalsThe World Wide Web Conference10.1145/3308558.3313671(1300-1309)Online publication date: 13-May-2019
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