research-article

Knowledge in the head and on the web: using topic expertise to aid search

Authors:

Geoffrey B. Duggan,

Stephen J. PayneAuthors Info & Claims

CHI '08: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Pages 39 - 48

https://doi.org/10.1145/1357054.1357062

Published: 06 April 2008 Publication History

Abstract

The importance of background knowledge for effective searching on the Web is not well understood. Participants were given trivia questions on two topics and asked to answer them first using background knowledge and second by searching on the Web. Knowledge of a topic predicted search performance on that topic for all questions and, more importantly, for questions for which participants did not already know the answer. In terms of process, greater topic knowledge led to less time being spent on each Webpage, faster decisions to give up a line of inquiry and shorter queries being entered into the search engine. A more complete theory-led understanding of these effects would assist workers in a whole range of Web-related professions.

References

[1]

Bhavnani, S.K. (2001). Important Cognitive Components of Domain-Specific Search Knowledge. Proceedings of TREC'2001, 571--578.

[2]

Cohen, J. (1988). Statistical power for the behavioral sciences (2nd Edition). Hillsdale, NJ: Erlbaum.

[3]

Fu, W.-T., Pirolli, P. (in press), SNIF-ACT: A Model of Information-Seeking Behavior in the World Wide Web. Human-Computer Interaction.

[4]

Greenfield, S. (2003). How tomorrow's technology is changing the way we think and feel. London, Penguin.

[5]

Hembrooke, H.A., Gay, G.K., Granka, L.A. (2005), "The effects of expertise and feedback on search term selection and subsequent learning", Journal of the American Society for Information Science and Technology, 56(8), 861--71.

Digital Library

[6]

Hölscher, C., & G. Strube. (2000). Web search behavior of internet experts and newbies. Computer Networks, 33(1), 337--346.

Digital Library

[7]

Hsieh-Yee, I. (1993). Effects of search experience and subject knowledge on the search tactics of novice and experienced searchers. Journal of the American Society for Information Science and Technology, 44(3), 161--174.

[8]

James, C. Helplessly advanced. On clever machines. http://www.clivejames.com/point-of-view/helplessly-advanced.

[9]

Jansen, B.J., & Pooch, U. (2000). A review of web searching studies and a framework for future research. Journal of the American Society of Information Science and Technology, 52(3), 235--246.

Digital Library

[10]

Jansen, B.J., & Spink, A. (2003). An analysis of Web documents retrieved and viewed. Proceedings of the 4th International Conference on Internet Computing. 65--69, Las Vegas, NV.

[11]

Kintsch, W. (1998). Comprehension A paradigm for cognition. New York: Cambridge University Press.

[12]

Kuhlthau, Carol C. (1991). Inside the Search Process: Information Seeking from the User's Perspective. Journal of the American Society of Information Science, 42, 361--371.

[13]

Lazonder, A., Bieiemans, H., & Wopereis, I. (2002). Differences between novice and experienced users in searching for information on the World Wide Web. Journal of the American Society for Information Science, 51, 576--581.

Digital Library

[14]

MacCallum, R.C., Zhang, S., Preacher, K.J., & Rucker, D.D. (2002). On the practice of dichotomization of quantitative variables. Psychological Methods, 7, 19--40.

[15]

Marchionini, G. (1997). Information seeking in electronic environments. Cambridge, Cambridge University Press.

Digital Library

[16]

Mat-Hassan, M., & Levene, M. (2005). Associating search and navigation behavior through log analysis. Journal of the American Society for Information Science and Technology, 56(9), 913--934.

[17]

Payne, S. J., Duggan, G. B., & Neth, H. (2007). Discretionary task interleaving: Heuristics for time allocation in cognitive foraging. Journal of Experimental Psychology: General, 136(3), 370--388.

[18]

Sellen, A.J., Murphy, R., & Shaw, K.L. (2002). How knowledge workers use the Web. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 227--234, Minneapolis, MN.

Digital Library

[19]

Tabachnick, B. G., & Fidell, L. S. (1989). Using multivariate statistics (2nd Edition). Cambridge, MA: Harper & Row.

Digital Library

[20]

Wildemuth, B. M. (2003). The effects of domain knowledge on search tactic formulation. Journal of the American Society for Information Science, 55, 246--258.

Digital Library

Cited By

Teixeira Lopes CHenriques M(2024)Unveiling Health Literacy through Web Search Behavior: A Classification-Based Analysis of User InteractionsProceedings of the 2024 Conference on Human Information Interaction and Retrieval10.1145/3627508.3638318(1-11)Online publication date: 10-Mar-2024
https://dl.acm.org/doi/10.1145/3627508.3638318
Botturi LHermida MAddimando LBeretta C(2024)Visualizing Online Search Processes for Information Literacy EducationInformation Experience and Information Literacy10.1007/978-3-031-52998-6_24(277-289)Online publication date: 1-Feb-2024
https://doi.org/10.1007/978-3-031-52998-6_24
Rogushina J(2023)A three-dimensional model of semantic search: queries, resources, and resultsPROBLEMS IN PROGRAMMING10.15407/pp2023.04.039(39-55)Online publication date: Dec-2023
https://doi.org/10.15407/pp2023.04.039
Show More Cited By

Index Terms

Knowledge in the head and on the web: using topic expertise to aid search
1. Applied computing
  1. Document management and text processing
    1. Document preparation
      1. Multi / mixed media creation
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Hypertext / hypermedia

Recommendations

Characterizing the influence of domain expertise on web search behavior
WSDM '09: Proceedings of the Second ACM International Conference on Web Search and Data Mining

Domain experts search differently than people with little or no domain knowledge. Previous research suggests that domain experts employ different search strategies and are more successful in finding what they are looking for than non-experts. In this ...
The role of expertise in aiding video search
CIVR '09: Proceedings of the ACM International Conference on Image and Video Retrieval

The importance of expertise for effective video search is not well understood. To address this problem we investigate the role of expertise in video search. In our evaluation participants were given a number of video search topics and asked to find ...
The Boiled Frog Problem

In all complex sociotechnical workplaces, knowledge and skill have become widely recognized as increasingly important assets. They are important because expertise is a "must" for proficient performance in these domains. Furthermore, this importance is ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

CHI '08: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

April 2008

1870 pages

ISBN:9781605580111

DOI:10.1145/1357054

General Chairs:
Mary Czerwinski
Microsoft Research, USA
,
Arnie Lund
Microsoft, USA
,
Program Chair:
Desney Tan
Microsoft Research, USA

Copyright © 2008 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 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]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 April 2008

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

CHI '08

Sponsor:

CHI '08: CHI Conference on Human Factors in Computing Systems

April 5 - 10, 2008

Florence, Italy

Acceptance Rates

CHI '08 Paper Acceptance Rate 157 of 714 submissions, 22%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

Upcoming Conference

CHI 2025

Sponsor:
sigchi

ACM CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

Yokohama , Japan

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

47
Total Citations
View Citations
988
Total Downloads

Downloads (Last 12 months)10
Downloads (Last 6 weeks)3

Reflects downloads up to 02 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Teixeira Lopes CHenriques M(2024)Unveiling Health Literacy through Web Search Behavior: A Classification-Based Analysis of User InteractionsProceedings of the 2024 Conference on Human Information Interaction and Retrieval10.1145/3627508.3638318(1-11)Online publication date: 10-Mar-2024
Botturi LHermida MAddimando LBeretta C(2024)Visualizing Online Search Processes for Information Literacy EducationInformation Experience and Information Literacy10.1007/978-3-031-52998-6_24(277-289)Online publication date: 1-Feb-2024
Rogushina J(2023)A three-dimensional model of semantic search: queries, resources, and resultsPROBLEMS IN PROGRAMMING10.15407/pp2023.04.039(39-55)Online publication date: Dec-2023
Dosso CTamine LPaubel PChevalier A(2023)Navigational and thematic exploration–exploitation trade-offs during web search: effects of prior domain knowledge, search contexts and strategies on search outcomeBehaviour & Information Technology10.1080/0144929X.2023.224251443:10(2232-2258)Online publication date: 10-Aug-2023
Abendroth JRichter T(2023)Informelles Lernen im InternetDigital ist besser?! Psychologie der Online- und Mobilkommunikation10.1007/978-3-662-66608-1_10(139-153)Online publication date: 29-Dec-2023
O'Brien HCole AKampen ABrennan KElsweiler DKruschwitz ULudwig B(2022)The Effects of Domain and Search Expertise on Learning Outcomes in Digital Library UseProceedings of the 2022 Conference on Human Information Interaction and Retrieval10.1145/3498366.3505761(202-210)Online publication date: 14-Mar-2022
Jia HMiller LHicks JMoscot ELandberg AHeflin JDavison B(2022)Truth in a sea of data: adoption and use of data search tools among researchers and journalistsInformation, Communication & Society10.1080/1369118X.2022.214739826:16(3237-3256)Online publication date: 27-Nov-2022
Payne SHowes A(2022)Adaptive InteractionundefinedOnline publication date: 4-Mar-2022
Sanchiz MAmadieu FChevalier A(2020)An Evolving Perspective to Capture Individual Differences Related to Fluid and Crystallized Abilities in Information Searching with a Search EngineUnderstanding and Improving Information Search10.1007/978-3-030-38825-6_5(71-96)Online publication date: 30-May-2020
Liu JLiu CBelkin N(2020)Personalization in text information retrievalJournal of the Association for Information Science and Technology10.1002/asi.2423471:3(349-369)Online publication date: 28-Jan-2020
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten