Exploring Cross-Device Web Use on PCs and Mobile Devices

  • Shaun K. Kane
  • Amy K. Karlson
  • Brian R. Meyers
  • Paul Johns
  • Andy Jacobs
  • Greg Smith
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5726)


In this paper, we explore whether sharing a user’s web browsing activity across their computing devices can make it easier to find and access web sites on a mobile device. We first surveyed 175 smartphone users about their web use across multiple devices. We found that users shared web information between devices, but generally used cumbersome manual methods to do so. In a second study, we tracked the web sites visited by 14 participants on their PC and mobile phone, and used experience-sampling surveys to determine whether sharing sites across devices would be useful. We found that participants visited many of the same sites on both their mobile device and PC, and that participants were interested in viewing additional sites from their PC on their mobile device. Our results suggest that automatically sharing web activity information between devices has potential to improve the usability of the mobile web.


Mobile web cross-device user experience activity logging experience sampling method 


  1. 1.
    Church, K., Smyth, B.: Understanding Mobile Information Needs. In: MobileHCI 2008, pp. 493–494. ACM Press, New York (2008)Google Scholar
  2. 2.
    Kamvar, M., Baluja, S.: The Role Of Context in Query Input: Using Contextual Signals to Complete Queries on Mobile Devices. In: MobileHCI 2007, pp. 405–412. ACM Press, New York (2007)Google Scholar
  3. 3.
    Sohn, T., Li, K.A., Griswold, W.G., Hollan, J.D.: A Diary Study of Mobile Information Needs. In: CHI 2008, pp. 433–442. ACM Press, New York (2008)Google Scholar
  4. 4.
    Demumieux, R., Losquin, P.: Gather Customer’s Real Usage on Mobile Phones. In: MobileHCI 2005, pp. 267–270. ACM Press, New York (2005)Google Scholar
  5. 5.
    Cui, Y., Roto, V.: How People Use the Web on Mobile Devices. In: WWW 2008, pp. 905–914. ACM Press, New York (2008)Google Scholar
  6. 6.
    Lee, I., Kim, J., Kim, J.: Use Contexts for the Mobile Internet: A Longitudinal Study Monitoring Actual Use of Mobile Internet Services. International Journal of Human-Computer Interaction 18(3), 269–292 (2005)CrossRefGoogle Scholar
  7. 7.
    Church, K., Smyth, B., Bradley, K., Cotter, P.: A Large Scale Study of European Mobile Search Behaviour. In: MobileHCI 2008, pp. 13–22. ACM Press, New York (2008)Google Scholar
  8. 8.
    Kamvar, M., Baluja, S.: A Large Scale Study Of Wireless Search Behavior: Google Mobile Search. In: CHI 2006, pp. 701–709. ACM Press, New York (2006)Google Scholar
  9. 9.
    Cohen, D., Herscovici, M., Petruschka, Y., Maarek, Y.S., Soffer, A.: Personalized Pocket Directories for Mobile Devices. In: WWW 2002, pp. 627–638. ACM Press, New York (2002)Google Scholar
  10. 10.
    Panayiotou, C., Samaras, G.: mPERSONA: Personalized Portals for the Wireless User: An Agent Approach. Mobile Networks and Applications 9(6), 663–677 (2004)CrossRefGoogle Scholar
  11. 11.
    Oulasvirta, A., Sumari, L.: Mobile Kits and Laptop Trays: Managing Multiple Devices in Mobile Information Work. In: CHI 2007, pp. 1127–1136. ACM Press, New York (2007)Google Scholar
  12. 12.
    Dearman, D., Pierce, J.S.: “It’s on My Other Computer!”: Computing with Multiple Devices. In: CHI 2008, pp. 767–776. ACM Press, New York (2008)Google Scholar
  13. 13.
    Potter, S., Nieh, J.: WebPod: Persistent Web Browsing Sessions with Pocketable Storage Devices. In: WWW 2005, pp. 603–612. ACM Press, New York (2005)Google Scholar
  14. 14.
    Morrison, J.B., Pirolli, P., Card, S.K.: A Taxonomic Analysis of What World Wide Web Activities Significantly Impact People’s Decisions and Actions. In: Extended Abstracts of CHI 2001, pp. 163–164. ACM Press, New York (2001)Google Scholar
  15. 15.
    Consolvo, S., Walker, M.: Using the Experience Sampling Method to Evaluate Ubicomp Applications. Pervasive Computing 2(2), 24–31 (2003)CrossRefGoogle Scholar
  16. 16.
    Brush, A.J.B., Meyers, B.R., Tan, D.S., Czerwinski, M.: Understanding Memory Triggers for Task Tracking. In: CHI 2007, pp. 947–950. ACM Press, New York (2007)Google Scholar
  17. 17.
    Adar, E., Teevan, J., Dumais, S.T.: Large Scale Analysis of Web Revisitation Patterns. In: CHI 2008, pp. 1197–1206. ACM Press, New York (2008)Google Scholar
  18. 18.
    Holm, S.: A Simple Sequentially Rejective Multiple Test Procedure. Scandinavian Journal of Statistics 6(2), 65–70 (1979)MathSciNetzbMATHGoogle Scholar
  19. 19.
    Karlson, A.K., Meyers, B.R., Jacobs, A., Johns, P., Kane, S.K.: Working Overtime: Patterns of Smartphone and PC Usage in the Day of an Information Worker. To appear in: Pervasive 2009. Springer, Heidelberg (2009)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2009

Authors and Affiliations

  • Shaun K. Kane
    • 1
  • Amy K. Karlson
    • 2
  • Brian R. Meyers
    • 2
  • Paul Johns
    • 2
  • Andy Jacobs
    • 2
  • Greg Smith
    • 2
  1. 1.The Information School, DUB GroupUniversity of WashingtonSeattleUSA
  2. 2.Microsoft Research, One Microsoft WayRedmondUSA

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