Advertisement

Recommender Interfaces: The More Human-Like, the More Humans Like

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9979)

Abstract

Social robots, when used for information providing, are able to affect humans’ trustworthiness and willingness to interact with them. In this work, we conducted an experimental study aimed at observing if the users’ acceptance of recommendations, as well as their engagement in the interaction, is elicited when using a humanoid robot with respect to a common application on a mobile phone. We conducted an experimental study on movie recommendation where the two interfaces provide the same contents, but through different communication channels. In detail, the robot will attend to the participants in a socially contingent fashion, signaled via head and gaze orientation, speech, eye color and gestures related to the genre of the recommended movie, and the app will provide textual and graphical movie presentation. Results show that while the users perceive the interaction with the mobile application more natural, the social robot is able to enhance the users’ satisfaction and provides a good and stable acceptance rate also when facing participants with various degrees of English proficiency.

Keywords

Acceptance Rate Mobile Application Humanoid Robot English Proficiency Social Robot 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgment

This work has been partially funded by the European Commission’s as part of the RoDyMan project under grant 320992 and supported by the Italian National Project “Security for Smart Cities” PON-FSE Campania 2014-20. Authors thank Francesco Cervone, Anna Tamburro and Valentina Sica for their contribution in code development and testing.

References

  1. 1.
    Alemi, M., Meghdari, A., Ghazisaedy, M.: The impact of social robotics on L2 learners’ anxiety and attitude in english vocabulary acquisition. Int. J. Social Robot. 7(4), 523–535 (2015)CrossRefGoogle Scholar
  2. 2.
    Bainbridge, W., Hart, J., Kim, E., Scassellati, B.: The effect of presence on human-robot interaction. In: The 17th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 701–706, August 2008Google Scholar
  3. 3.
    Boone, R.T., Buck, R.: Emotional expressivity and trustworthiness: the role of nonverbal behavior in the evolution of cooperation. In: Lib., A.R. (ed.) J. of Nonverbal Behavior (2003)Google Scholar
  4. 4.
    Bruce, A., Nourbakhsh, I.R., Simmons, R.G.: The role of expressiveness and attention in human-robot interaction. In: ICRA, pp. 4138–4142. IEEE (2002)Google Scholar
  5. 5.
    Caccavale, R., Leone, E., Lucignano, L., Rossi, S., Staffa, M., Finzi, A.: Attentional regulations in a situated human-robot dialogue. In: The 23rd IEEE International Symposium on Robot and Human Interactive Communication, pp. 844–849, August 2014Google Scholar
  6. 6.
    Cervone, F., Sica, V., Staffa, M., Tamburro, A., Rossi, S.: Comparing a social robot and a mobile application for movie recommendation: a pilot study. In: Proceedings of the 16th Workshop from Objects to Agents, pp. 32–38. CEUR Workshop Proceedings (2015)Google Scholar
  7. 7.
    Crumpton, J., Bethel, C.L.: Validation of vocal prosody modifications to communicate emotion in robot speech. In: 2015 International Conference on Collaboration Technologies and Systems (CTS), pp. 39–46, June 2015Google Scholar
  8. 8.
    Kidd, C., Breazeal, C.: Effect of a robot on user perceptions. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), vol. 4, pp. 3559–3564 (2004)Google Scholar
  9. 9.
    Konstan, J.A., Riedl, J.: Recommender systems: from algorithms to user experience. User Model. User-Adap. Inter. 22(1), 101–123 (2014)Google Scholar
  10. 10.
    de Melo, C.M., Zheng, L., Gratch, J.: Expression of moral emotions in cooperating agents. In: Proceedings of the 9th International Conference on Intelligent Virtual Agents (IVA) (2009)Google Scholar
  11. 11.
    Merritt, S.M., Ilgen, D.R.: Not all trust is created equal: dispositional and history-based trust in human-automation interactions. Hum. Factors 50(2), 194–210 (2008)CrossRefGoogle Scholar
  12. 12.
    Movellan, J., Eckhardt, M., Virnes, M., Rodriguez, A.: Sociable Robot Improves Toddler Vocabulary Skills. IEEE, La Jolla, CA (2009)Google Scholar
  13. 13.
    Murphy-Hill, E., Murphy, G.: Recommendation delivery. In: Robillard, M.P., Maalej, W., Walker, R.J., Zimmermann, T. (eds.) Recommendation Systems in Software Engineering, pp. 223–242. Springer, Heidelberg (2014)Google Scholar
  14. 14.
    Rossi, S., Staffa, M., Giordano, M., De Gregorio, M., Rossi, A., Tamburro, A., Vellucci, C.: Robot head movements and human effort in the evaluation of tracking performance. In: 24th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 791–796 (2015)Google Scholar
  15. 15.
    Rossi, S., Cervone, F.: Social utilities and personality traits for group recommendation: a pilot user study. In: Proceedings of the 8th International Conference on Agents and Artificial Intelligence, pp. 38–46 (2016)Google Scholar
  16. 16.
    Shiomi, M., Shinozawa, K., Nakagawa, Y., Miyashita, T., Sakamoto, T., Terakubo, T., Ishiguro, H., Hagita, N.: Recommendation effects of a social robot for advertisement-use context in a shopping mall. Int. J. Soc. Robot. 5(2), 251–262 (2013)CrossRefGoogle Scholar
  17. 17.
    Wang, Y.D., Emurian, H.H.: An overview of online trust: Concepts, elements, and implications. Comput. Hum. Behav. 21(1), 105–125 (2005)CrossRefGoogle Scholar
  18. 18.
    Yoo, K.H., Gretzel, U.: Creating more credible and persuasive recommender systems: the influence of source characteristics on recommender system evaluations. In: Recommender Systems Handbook, pp. 455–477. Springer, US (2011)Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Department of EngineeringUniversity of Naples ParthenopeNaplesItaly
  2. 2.Department of Electrical Engineering and Information TechnologyUniversity of Naples Federico IINaplesItaly

Personalised recommendations