skip to main content
10.1145/1526709.1526817acmconferencesArticle/Chapter ViewAbstractPublication PagesthewebconfConference Proceedingsconference-collections
research-article

Computers and iphones and mobile phones, oh my!: a logs-based comparison of search users on different devices

Published: 20 April 2009 Publication History

Abstract

We present a logs-based comparison of search patterns across three platforms: computers, iPhones and conventional mobile phones. Our goal is to understand how mobile search users differ from computer-based search users, and we focus heavily on the distribution and variability of tasks that users perform from each platform. The results suggest that search usage is much more focused for the average mobile user than for the average computer-based user. However, search behavior on high-end phones resembles computer-based search behavior more so than mobile search behavior. A wide variety of implications follow from these findings. First, there is no single search interface which is suitable for all mobile phones. We suggest that for the higher-end phones, a close integration with the standard computer-based interface (in terms of personalization and available feature set) would be beneficial for the user, since these phones seem to be treated as an extension of the users' computer. For all other phones, there is a huge opportunity for personalizing the search experience for the user's "mobile needs", as these users are likely to repeatedly search for a single type of information need on their phone.

References

[1]
Baeza-Yates, R., Dupret, G., & Velasco, J. 2007. A study of mobile search queries in Japan. Query Log Analysis: Social and Technological Challenges. WWW 2007 Workshop.
[2]
Beitzel, S., Jense, E.C., Chowdhury, A., Grossman, D., Frieder, O. 2004. Hourly analysis of a very large topically categorized web query log. SIGIR 2004. 321--328.
[3]
Church, K., Smyth, B., Cotter, P., & Bradley, K. 2007. Mobile information access: A study of emerging search behavior on the mobile Internet. ACM Transactions on the Web, 1(1).
[4]
Church, K., Smyth, B., Bradley, K., & Cotter, P. 2008. A large scale study of European mobile search behaviour. Mobile HCI 2008. 13--22.
[5]
Dearman, D., Kellar, M., & Truong, K. 2008. An Examination of Daily Information Needs and Sharing Opportunities. CSCW 2008. 679--688.
[6]
Fox, S. 2008. Almost half of all internet users now use search on a typical day. http://www.pewinternet.org/pdfs/PIP_Search_ Aug08.pdf. 2008. Pew/Internet.
[7]
Covey, N. 2008. Critical Mass: The Worldwide State of the Mobile Web. Nielsen Mobile. http://www.nielsenmobile.com/documents/CriticalMass.pdf.
[8]
Jansen, B.J., & Spink, A. 2005. How are we searching the World Wide Web? A comparison of nine search engine transaction logs. Information Processing and Management, 52(2006): 249 --- 263.
[9]
Jansen, B. J., Spink, A., Bateman, J., & Saracevic, T. 1998. Real life information retrieval: A study of user queries on the web. SIGIR Forum, 32(1): 5--17.
[10]
Jansen, B. J., Spink, A., & Saracevic, T. 1998. Real life information retrieval: A Study of User Queries on the Web. SIGIR Forum, 32(1): S--17
[11]
Jansen, B., Spink, A., & Saracevic, T. 2000. Real life, real users, and real needs: A study and analysis of user queries on the web. Information Processing and Management, 36(2): 207--227.
[12]
Jones, M., Jain, P., Buchanan, G., & Marsden, G. 2003. Using a mobile device to vary the pace of search. Mobile HCI 2003. 90--394.
[13]
Kamvar, M., Baluja, S. 2006. A Large Scale Study of Wireless Search Behavior: Google Mobile Search. CHI 2006. 701 -- 709.
[14]
Kamvar, M. & Baluja, S. 2007. Deciphering Trends in Mobile Search. Computer, 40(8): 58--62.
[15]
Kamvar, M. & Baluja, S. 2007. The Role of Context in Query Input: Using contextual signals to complete queries on mobile devices. Mobile HCI 2007. 121--128.
[16]
MacKenzie, I.S. 2002. KSPC (keystrokes per character) as a characteristic of text entry techniques. Mobile HCI 2002. 195--210.
[17]
Shannon, C.E. 1948. A Mathematical Theory of Communication. Bell System Technical Journal, 27: 379--423.
[18]
Silverstein, C., Henzinger, M., Marais, H., & Moricz, M. 1999. Analysis of a Very Large Web Search Engine Query Log. SIGIR Forum, 33(1): 6--12.
[19]
Sohn, T., Li, K.A.,Griswold, W. & Hollan, J.D. 2008. A diary study of mobile information needs. CHI 2008. 433--442.
[20]
Spink, A., Jansen, B., Wolfram, D., & Saracevic, T. 2002. From E-Sex to E-Commerce: Web search changes. IEEE Computer, 35(3): 107--109.
[21]
Spink, A., Wolfram, D., Jansen, B. J., & Saracevic, T. 2001. Searching the web: The public and their queries. Journal of the American Society for Information Science and Technology, 52(3), 226--234.
[22]
Wedig, S. & Madani, O. 2006. A large-scale analysis of query logs for assessing personalization opportunities. SIGKDD 2006. 742 -- 747.
[23]
Yi, J., Maghoul, F., & Pendersen, J. 2008. Deciphering Mobile Search Patterns: A Study of Yahoo! Mobile Search Queries. WWW 2008. 257--266.

Cited By

View all
  • (2024)MeMemo: On-device Retrieval Augmentation for Private and Personalized Text GenerationProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657662(2765-2770)Online publication date: 10-Jul-2024
  • (2023)An F-shape Click Model for Information Retrieval on Multi-block Mobile PagesProceedings of the Sixteenth ACM International Conference on Web Search and Data Mining10.1145/3539597.3570365(1057-1065)Online publication date: 27-Feb-2023
  • (2022)An overview of cluster-based image search result organization: background, techniques, and ongoing challengesKnowledge and Information Systems10.1007/s10115-021-01650-9Online publication date: 11-Feb-2022
  • Show More Cited By

Index Terms

  1. Computers and iphones and mobile phones, oh my!: a logs-based comparison of search users on different devices

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    WWW '09: Proceedings of the 18th international conference on World wide web
    April 2009
    1280 pages
    ISBN:9781605584874
    DOI:10.1145/1526709

    Sponsors

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 20 April 2009

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. google
    2. iphone
    3. mobile search
    4. search
    5. user behavior

    Qualifiers

    • Research-article

    Conference

    WWW '09
    Sponsor:

    Acceptance Rates

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

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)36
    • Downloads (Last 6 weeks)3
    Reflects downloads up to 22 Feb 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)MeMemo: On-device Retrieval Augmentation for Private and Personalized Text GenerationProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657662(2765-2770)Online publication date: 10-Jul-2024
    • (2023)An F-shape Click Model for Information Retrieval on Multi-block Mobile PagesProceedings of the Sixteenth ACM International Conference on Web Search and Data Mining10.1145/3539597.3570365(1057-1065)Online publication date: 27-Feb-2023
    • (2022)An overview of cluster-based image search result organization: background, techniques, and ongoing challengesKnowledge and Information Systems10.1007/s10115-021-01650-9Online publication date: 11-Feb-2022
    • (2021)Content-Determined Web Page Segmentation and Navigation for Mobile Web SearchingResult Page Generation for Web Searching10.4018/978-1-7998-0961-6.ch007(88-108)Online publication date: 2021
    • (2021)Mobile vs desktop user search behaviours of the 1300K site, a Korean shopping search engineThe Electronic Library10.1108/EL-09-2020-026139:2(239-257)Online publication date: 15-Jun-2021
    • (2021)On Latency of E-Commerce PlatformsJournal of Organizational Computing and Electronic Commerce10.1080/10919392.2021.1882240(1-17)Online publication date: 24-Feb-2021
    • (2020)When Are Search Completion Suggestions Problematic?Proceedings of the ACM on Human-Computer Interaction10.1145/34152424:CSCW2(1-25)Online publication date: 15-Oct-2020
    • (2020)An Eye Tracking Study of Web Search by People With and Without DyslexiaProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401103(729-738)Online publication date: 25-Jul-2020
    • (2020)The Influence of Device Type on Querying Behavior and Learning Outcomes in a Searching as Learning Task with a Laptop or SmartphoneProceedings of the 2020 Conference on Human Information Interaction and Retrieval10.1145/3343413.3378000(373-377)Online publication date: 14-Mar-2020
    • (2019)Constructing Click Model for Mobile Search with Viewport TimeACM Transactions on Information Systems10.1145/336048637:4(1-34)Online publication date: 26-Sep-2019
    • 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