skip to main content
10.1145/1242572.1242576acmconferencesArticle/Chapter ViewAbstractPublication PagesthewebconfConference Proceedingsconference-collections
Article

Investigating behavioral variability in web search

Published: 08 May 2007 Publication History

Abstract

Understanding the extent to which people's search behaviors differ in terms of the interaction flow and information targeted is important in designing interfaces to help World Wide Web users search more effectively. In this paper we describe a longitudinal log-based study that investigated variability in people.s interaction behavior when engaged in search-related activities on the Web.allWe analyze the search interactions of more than two thousand volunteer users over a five-month period, with the aim of characterizing differences in their interaction styles.allThe findings of our study suggest that there are dramatic differences in variability in key aspects of the interaction within and between users, and within and between the search queries they submit.allOur findings also suggest two classes of extreme user. navigators and explorers. whose search interaction is highly consistent or highly variable. Lessons learned from these users can inform the design of tools to support effective Web-search interactions for everyone.

References

[1]
Bates, M. (1989). The design of browsing and berrypicking techniques for the online search interface. Online Review, 13: 407--424.
[2]
Bederson, B.B. & Shneiderman, B. (2003). The Craft of Information Visualization: Readings and Reflections. Morgan Kaufmann.
[3]
Bhavnani, S.K. (2001). Domain-specific search strategies for the effective retrieval of healthcare and shopping information. In Proc. CHI 2002, 610--611.
[4]
Buckland, M.K. & Florian, D. (1991). Expertise, task complexity, and artificial intelligence: A conceptual framework. J. Amer. Soc. Info. Sci, 42 (9), 635--643.
[5]
Card, S.K. et al. (2001). Information scent as a driver of web behavior graphs: Results of a protocol analysis method for web usability. In Proc. CHI 2001, 498--505.
[6]
Catledge, L.D. & Pitkow, J.E. (1995). Characterizing browsing strategies in the world wide web. Computer Networks and ISDN Systems, 27(6): 1065--1073.
[7]
Chi, E., Pirolli, P., Chen, J., Pitkow, J. (2001).allUsing information scent to model user information needs and actions on the web. In Proc. CHI 2001, pp. 490--497.
[8]
Cutrell, E. et al. (2006). Fast, flexible filtering with Phlat -- Personal search and organization made easy. In Proc. CHI 2006, 261--270.
[9]
Dillon, A. & Watson, C. (1996). User analysis in HCI: the historical lesson from individual differences research. International Journal of Human-Computer Studies, 45(6): 619--637.
[10]
Egan, D. (1988) Individual differences in human-computer interaction. In: Handbook of Human-computer Interaction. Elsevier, 543--568.
[11]
Eisenstein, J. & Rich, R. (2002). Agents and GUIs from task models. In Proc. IUI 2002, 47--54.
[12]
Ford, N. et al. (2002). Information seeking and mediated searching. Part 4. Cognitive styles in information seeking. JASIST, 53(9), 728--35.
[13]
Hölscher, C. & Strube, G. (2000). Web search behavior of Internet experts and newbies. Computer Networks, 33, 337--46.
[14]
Huberman, B. et al. (1998). Strong regularities in World Wide Web surfing. Science, 280 (5360): 95--97.
[15]
Jansen, B. J., Spink, A. & Saracevic, T. (2000). Real life, real users, and real needs: A study and analysis of user queries on the Web. Info. Proc. & Mgt., 36: 207--227.
[16]
Jones, R. et al. (2006). Generating query substitutions. In Proc. WWW 2006, 387--396.
[17]
Lau, T. & Horvitz, E. (1999). Patterns of search: Analyzing and modeling web query refinement. In Proc. UM 1999, 119--128.
[18]
Levenshtein, V. (1966). Binary codes capable of correcting deletions, insertions and reversals. Soviet Physics Doklady, 10(8):707--710.
[19]
Lieberman, H.L., Fry, C. & Weitzman, L. (2001). Exploring the Web with reconnaissance agents. Communications of the ACM, 44(8): 69--75.
[20]
Malone, T.E. (1983). How do people organize their desks? ACM TOIS, 1(1): 99--112.
[21]
Marchionini, G. (1995). Information seeking in electronic environments. Cambridge University Press.
[22]
Milic-Frayling, N. (2004). SmartBack: Supporting users in back navigation. In Proc. WWW 2004, 63--71.
[23]
Neilsen, J. (1993). Usability Engineering, Cambridge MA: Academic Press.
[24]
Newell, A. & Simon, H. (1972). Human Problem Solving. Prentice-Hall.
[25]
O'Day, V. & Jeffries, R. (1993). Orienteering in an information landscape: how information seekers get from here to there. In Proc. CHI 1993, 438--445.
[26]
Pask, G. (1976). Conventional techniques in the study and practice of education. British Journal of Educational Psychology, 46, 12--25.
[27]
Pirolli, P. & Card, S.K. (1995). Information foraging. Psychological Review, 106, 643--675.
[28]
Pirolli, P. & Fu, W. (2003). Snif-act: A model of information foraging on the World Wide Web. In Proc. UM 2003, 45--54.
[29]
Pitkow, J. & Pirolli, P. (1999). Mining longest repeating subsequences to predict World Wide Web surfing. In Proc. USENIX Symposium, 139--150.
[30]
Pitkow, J. et al. (2002). Personalized search. Communications of the ACM, 45(9): 50--55.
[31]
Rich, E. (1989). Stereotypes and user modeling. In User Models in Dialog Systems. Springer.
[32]
Rose, D. E. & Levinson, D. (2004). Understanding user goals in Web search. In Proc. WWW 2004, 13--19.
[33]
Russell, D.M. et al. (1993). The cost structure of sensemaking. In Proc. CHI 1993, 269--276.
[34]
Tauscher, L. & Greenberg, S. (1997). Revisitation patterns in World Wide Web navigation. In Proc. CHI 1997, 399--406.
[35]
Teevan, J. et al. (2006). History repeats itself: Repeat queries in Yahoo's logs. In Proc. SIGIR 2006, 703--704.
[36]
Teevan, J. et al. (2004). The perfect search engine is not enough: A study of orienteering behavior in directed search. In Proc. CHI 2004, 415--422.
[37]
Teevan, J. et al. (2005). Beyond the commons: Investigating the value of personalizing web search. In Proc. PIA 2005.
[38]
Trigg, R.H. (1988). Guided tours and tabletops: tools for communicating in a hypertext environment. Transactions on Information Systems, 6(4): 398--414.
[39]
Weinreich, H., Obendorf, H., Herder, E. & Mayer, M. (2006). Off the beaten tracks: Exploring three aspects of web navigation. In Proc. WWW 2006, 133--142.
[40]
Wexelblat, A. & Maes, P. (1999). Footprints: History-rich tools for information foraging. In Proc. CHI 1999, 270--277.

Cited By

View all
  • (2024)Predicting Representations of Information Needs from Digital Activity ContextACM Transactions on Information Systems10.1145/363981942:4(1-29)Online publication date: 15-Jan-2024
  • (2023)A Large-Scale Characterization of How Readers Browse WikipediaACM Transactions on the Web10.1145/358031817:2(1-22)Online publication date: 3-Apr-2023
  • (2023)When Browsing Gets Cluttered: Exploring and Modeling Interactions of Browsing Clutter, Browsing Habits, and CopingProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580690(1-29)Online publication date: 19-Apr-2023
  • Show More Cited By

Index Terms

  1. Investigating behavioral variability in web search

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    WWW '07: Proceedings of the 16th international conference on World Wide Web
    May 2007
    1382 pages
    ISBN:9781595936547
    DOI:10.1145/1242572
    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: 08 May 2007

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. behavioral variability
    2. web search

    Qualifiers

    • Article

    Conference

    WWW'07
    Sponsor:
    WWW'07: 16th International World Wide Web Conference
    May 8 - 12, 2007
    Alberta, Banff, Canada

    Acceptance Rates

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

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)64
    • Downloads (Last 6 weeks)3
    Reflects downloads up to 18 Feb 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Predicting Representations of Information Needs from Digital Activity ContextACM Transactions on Information Systems10.1145/363981942:4(1-29)Online publication date: 15-Jan-2024
    • (2023)A Large-Scale Characterization of How Readers Browse WikipediaACM Transactions on the Web10.1145/358031817:2(1-22)Online publication date: 3-Apr-2023
    • (2023)When Browsing Gets Cluttered: Exploring and Modeling Interactions of Browsing Clutter, Browsing Habits, and CopingProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580690(1-29)Online publication date: 19-Apr-2023
    • (2023)Enhancing Potential Re-Finding in Personalized Search With Hierarchical Memory NetworksIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2021.312606635:4(3846-3857)Online publication date: 1-Apr-2023
    • (2023)Individual variations in information behaviour of professional translators: towards a classification of translation-oriented research stylesTranslation Studies10.1080/14781700.2023.223193317:2(394-415)Online publication date: 16-Aug-2023
    • (2023)Web Page Evaluation and Opinion Formation on Controversial Search TopicsLeveraging Generative Intelligence in Digital Libraries: Towards Human-Machine Collaboration10.1007/978-981-99-8085-7_17(188-203)Online publication date: 30-Nov-2023
    • (2023)Fragmented Visual Attention in Web Browsing: Weibull Analysis of Item Visit TimesAdvances in Information Retrieval10.1007/978-3-031-28238-6_5(62-78)Online publication date: 2-Apr-2023
    • (2022)Improving Personalized Search with Dual-Feedback NetworkProceedings of the Fifteenth ACM International Conference on Web Search and Data Mining10.1145/3488560.3498447(210-218)Online publication date: 11-Feb-2022
    • (2022)Deconstructing Categorization in Visualization Recommendation: A Taxonomy and Comparative StudyIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.308575128:12(4225-4239)Online publication date: 1-Dec-2022
    • (2021)Group based Personalized Search by Integrating Search Behaviour and Friend NetworkProceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3404835.3462918(92-101)Online publication date: 11-Jul-2021
    • Show More Cited By

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media