Advertisement

Evaluating the Social Acceptability of Voice Based Smartwatch Search

  • Christos Efthymiou
  • Martin Halvey
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9994)

Abstract

There has been a recent increase in the number of wearable (e.g. smartwatch, interactive glasses, etc.) devices available. Coupled with this there has been a surge in the number of searches that occur on mobile devices. Given these trends it is inevitable that search will become a part of wearable interaction. Given the form factor and display capabilities of wearables this will probably require a different type of search interaction to what is currently used in mobile search. This paper presents the results of a user study focusing on users’ perceptions of the use of smartwatches for search. We pay particular attention to social acceptability of different search scenarios, focussing on input method, device form and information need. Our findings indicate that audience and location heavily influence whether people will perform a voice based search. The results will help search system developers to support search on smartwatches.

Keywords

Smartwatch Acceptability Voice Search Information need 

References

  1. 1.
    Shokouhi, M., Guo, Q.: From queries to cards: re-ranking proactive card recommendations based on reactive search history. In: 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 695–704 (2015)Google Scholar
  2. 2.
    Rico, J., Brewster, S.: Usable gestures for mobile interfaces: evaluating social acceptability. In: 28th ACM Conference Conference on Human Factors in Computing Systems, pp. 887–896 (2010)Google Scholar
  3. 3.
    Jones, M., Buchanan, G., Thimbleby, H.: Improving web search on small screen devices. Interact. Comput. 15, 479–495 (2003)CrossRefGoogle Scholar
  4. 4.
    Church, K., Smyth, B., Bradley, K., Cotter, P.: A large scale study of European mobile search behaviour. In: 10th International Conference on Human Computer Interaction with Mobile Devices and Services, pp. 13–22 (2008)Google Scholar
  5. 5.
    Broder, A.: A taxonomy of web search. ACM SIGIR Forum 36, 3–10 (2002). ACMCrossRefMATHGoogle Scholar
  6. 6.
    Church, K., Cousin, A., Oliver, N.: I wanted to settle a bet!: understanding why and how people use mobile search in social settings. In: 14th International Conference on Human-Computer Interaction with Mobile Devices and Services, pp. 393–402 (2012)Google Scholar
  7. 7.
    Church, K., Neumann, J., Cherubini, M., Oliver, N.: SocialSearchBrowser: a novel mobile search and information discovery tool. In: Proceedings of the 15th International Conference on Intelligent User Interfaces, pp. 101–110 (2012)Google Scholar
  8. 8.
    Ren, Y., Tomko, M., Ong, K., Sanderson, M.: How people use the web in large indoor spaces. In: 23rd ACM International Conference on Conference on Information and Knowledge Management, pp. 1879–1882 (2014)Google Scholar
  9. 9.
    Church, K., Cramer, H.: Understanding requirements of place in local search. In: 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, pp. 1857–1862 (2015)Google Scholar
  10. 10.
    Montañez, G.D., White, R.W., Huang, X.: Cross-device search. In: 23rd ACM Conference on Conference on Information and Knowledge Management, pp. 1669–1678 (2015)Google Scholar
  11. 11.
    Schaar, A.K., Ziefle, M.: Smart clothing: perceived benefits vs. perceived fears. In: 5th IEEE Pervasive Computing Technologies for Healthcare, pp. 601–608 (2011)Google Scholar
  12. 12.
    Shinohara, K., Wobbrock, J.O.: In the shadow of misperception: assistive technology use and social interactions. In: 29th ACM Conference Conference on Human Factors in Computing Systems, pp. 705–714 (2011)Google Scholar
  13. 13.
    Hoyle, R., Templeman, R., Armes, S., Anthony, D., Crandall, D., Kapadia, A.: Privacy behaviors of lifeloggers using wearable cameras. In: ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 571–582 (2014)Google Scholar
  14. 14.
    Pearson, J., Robinson, S., Jones, M.: It’s about time: smartwatches as public displays. In: 33rd ACM Conference Conference on Human Factors in Computing Systems, pp. 1257–1266 (2015)Google Scholar
  15. 15.
    Easwara Moorthy, A., Vu, K.-P.L.: Privacy concerns for use of voice activated personal assistant in the public space. Int. J. Hum.-Comput. Interact. 31, 307–335 (2015)CrossRefGoogle Scholar
  16. 16.
    Wakeling, S., Halvey, M., Villa, R., Hasler, L.: A comparison of primary and secondary relevance judgements for real-life topics. In: ACM SIGIR Conference on Human Information Interaction and Retrieval, pp. 173–182 (2016)Google Scholar
  17. 17.
    Leiva, L.A., Sahami, A., Catalá, A., Henze, N., Schmidt, A.: Text entry on tiny QWERTY soft keyboards. In: 33rd Annual ACM Conference on Human Factors in Computing Systems, pp. 669–678 (2015)Google Scholar
  18. 18.
    Montero, C.S., Alexander, J., Marshall, M.T., Subramanian, S.: Would you do that?: understanding social acceptance of gestural interfaces. In: 12th International Conference on Human Computer Interaction with Mobile Devices and Services, pp. 275–278 (2010)Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Department of Computer and Information SciencesUniversity of StrathclydeGlasgowUK

Personalised recommendations