Skip to main content
SpringerLink
Log in

Exploring Gaze Behaviour and Perceived Personality Traits

  • Conference paper
  • First Online:
Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis (HCII 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12194))

Included in the following conference series:

Abstract

The paper discusses correlation between interlocutors’ eye-gaze behavior and their perceived personality traits in human-human and human-robot interactions. Given that personality is related to the person’s typical manners and styles of behaving, it can be assumed that such underlying characteristics are reflected in the person’s gaze patterns as well. Starting from the comparison of human-human and human-robot interaction, the participant’s gaze frequency and length in regard to the human vs. robot partner’s face and body are related to the participant’s perceived personality traits. A positive correlation is found concerning the differences in gaze patterns and the extrovert personality trait. This seems highly reasonable, considering the basic function of gaze as a means to collect situational information and the extrovert communication style as actively looking for new information.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Kendon, A.: Some functions of gaze–direction in social interaction. Acta Physiol. 26(1), 22–63 (1967)

    Google Scholar 

  2. Argyle, M., Cook, M.: Gaze and Mutual Gaze. Cambridge University Press, Cambridge (1976)

    Google Scholar 

  3. Clark, H., Wilkes-Gibbs, D.: Referring as a collaborative process. Cognition 22, 1–39 (1986)

    Article  Google Scholar 

  4. Jokinen, K., Furukawa, H., Nishida, M., Yamamoto, S.: Gaze and turn-taking behavior in casual conversational interactions. ACM Trans. Interact. Intell. Syst. (TiiS) 3(2), 12:1–12:30 (2013). Special Section on Eye-gaze and Conversational Engagement

    Google Scholar 

  5. Ijuin, K., Umata, I., Kato, T., Yamamoto, S.: Difference in eye gaze for floor apportionment in native-and second-language conversations. J. Nonverbal Behav. 42(1), 113–128 (2018)

    Article  Google Scholar 

  6. Broz, F., Lehmann, H., Mutlu, B., Nakano, Y.: Gaze in Human-Robot Communication. John Benjamins Publishing Company, Amsterdam (2015)

    Book  Google Scholar 

  7. Jokinen, K.: Conversational gaze modelling in first encounter robot dialogues. In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC-2018). European Languages Resources Association (ELRA) (2018)

    Google Scholar 

  8. Ijuin, K., Jokinen, K., Kato, T., Yamamoto, S.: Eye-gaze in social robot interactions – grounding of information and eye-gaze patterns. In: JSAI (2019)

    Google Scholar 

  9. McCrae, R.R.: Cross-cultural research on the five-factor model of personality. Online Readings Psychol. Cult. 4(4), 1–12 (2002). https://doi.org/10.9707/2307-0919.1038

    Article  MathSciNet  Google Scholar 

  10. Aran, O., Gatica-Perez, D.: One of a kind: inferring personality impressions in meetings. In: Proceedings of the ACM International Conference of Multimodal Interaction, ICMI 2013, pp. 11–18 (2013)

    Google Scholar 

  11. Jayagopi, D.B., et al.: The vernissage corpus: a conversational human-robot-interaction dataset. In: Proceedings of the 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 149–150. IEEE (2013)

    Google Scholar 

  12. Okada, S., Aran, O., Gatica-Perez, D.: Personality trait classification via co-occurrent multiparty multimodal event discovery. In: Proceedings of the ACM International Conference on Multimodal Interaction (ICMI 2015), Seattle, WA, USA, pp 15–22 (2015)

    Google Scholar 

  13. Aly, A., Tapus, A.: A model for synthesizing a combined verbal and nonverbal behavior based on personality traits in human-robot interaction. In: Proceedings of the 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 325–332, March 2013

    Google Scholar 

  14. Jokinen, K., Wilcock, G.: Multimodal open-domain conversations with the Nao Robot. In: Natural Interaction with Robots, Knowbots and Smartphones - Putting Spoken Dialog Systems into Practice, pp. 213–224. Springer, New York (2014)

    Google Scholar 

  15. Koppensteiner, M.: Motion cues that make an impression: predicting perceived personality by minimal motion information. J. Exp. Soc. Psychol. 49(6), 1137–1143 (2013). http://www.sciencedirect.com/science/article/pii/S0022103113001467

    Article  Google Scholar 

  16. Subramanian, R., Yan, Y., Staiano, J., Lanz, O., Sebe, N.: On the relationship between head pose, social attention and personality prediction for unstructured and dynamic group interactions. In: Proceedings of the 15th ACM on International Conference on Multimodal Interaction Association for Computing Machinery, pp. 3–10 (2013). https://doi.org/10.1145/2522848.2522862

  17. Larsen, R.J., Shackelford, T.K.: Gaze avoidance: personality and social judgments of people who avoid direct face-to-face contact. Pers. Individ. Differ. 21(6), 907–917 (1996). http://www.sciencedirect.com/science/article/pii/S0191886996001481

    Article  Google Scholar 

  18. Riggio, R.E., Friedman, H.S.: Impression formation: the role of expressive behavior. J. Pers. Soc. Psychol. 50(2), 421–427 (1986)

    Article  Google Scholar 

  19. Vinciarelli, A., Mohammadi, G.: A survey of personality computing. IEEE Trans. Affect. Comput. 5(3), 273–291 (2014)

    Article  Google Scholar 

  20. Mehta, Y., Majumder, N., Gelbukh, A., Cambria, E.: Recent trends in deep learning based personality detection. Artif. Intell. Rev. 53(4), 2313–2339 (2019). https://doi.org/10.1007/s10462-019-09770-z

    Article  Google Scholar 

  21. Ponce-López, V., et al.: ChaLearn LAP 2016: first round challenge on first impressions - dataset and results. In: Hua, G., Jégou, H. (eds.) ECCV 2016. LNCS, vol. 9915, pp. 400–418. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-49409-8_32

    Chapter  Google Scholar 

  22. Jokinen, K.: The AICO multimodal corpus. In: Proceedings of the Twelfth International Conference on Language Resources and Evaluation (LREC-2020). European Languages Resources Association (ELRA) (2020)

    Google Scholar 

  23. Mori, T., Jokinen, K., Den, Y.: Analysis of body behaviours in human-human and human-robot interactions. In: Proceedings of the LREC Workshop on People in Language, Vision and the Mind (2020)

    Google Scholar 

  24. Rammstedt, B., John, O.P.: Measuring personality in one minute or less: a 10-item short version of the big five inventory in English and German. J. Res. Pers. 41(1), 203–212 (2007). http://www.sciencedirect.com/science/article/pii/S0092656606000195

    Article  Google Scholar 

Download references

Acknowledgement

This paper is based on results obtained from a project commissioned by the New Energy and Industrial Technology Development Organization (NEDO).

Author information

Authors and Affiliations

  1. AI Research Center, National Institute of Advanced Industrial Science and Technology (AIST), 2-3-26 Aomi, Koto-Ku, Tokyo, Japan

    Koki Ijuin & Kristiina Jokinen

Authors
  1. Koki Ijuin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kristiina Jokinen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Koki Ijuin .

Editor information

Editors and Affiliations

  1. Towson University, Towson, MD, USA

    Gabriele Meiselwitz

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ijuin, K., Jokinen, K. (2020). Exploring Gaze Behaviour and Perceived Personality Traits. In: Meiselwitz, G. (eds) Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis. HCII 2020. Lecture Notes in Computer Science(), vol 12194. Springer, Cham. https://doi.org/10.1007/978-3-030-49570-1_35

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-49570-1_35

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-49569-5

  • Online ISBN: 978-3-030-49570-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation