Home Mathematics 2. Opportunities and challenges of utilizing personality traits for personalization in HCI
Chapter
Licensed
Unlicensed Requires Authentication

2. Opportunities and challenges of utilizing personality traits for personalization in HCI

  • Sarah Theres Völkel , Ramona Schödel , Daniel Buschek , Clemens Stachl , Quay Au , Bernd Bischl , Markus Bühner and Heinrich Hussmann
Become an author with De Gruyter Brill
Explore this Subject How to publish with us
Personalized Human-Computer Interaction
This chapter is in the book Personalized Human-Computer Interaction

Abstract

This chapter discusses main opportunities and challenges of assessing and utilizing personality traits in personalized interactive systems and services. This unique perspective arises from our long-term collaboration on research projects involving three groups on human-computer interaction (HCI), psychology, and statistics. Currently, personalization in HCI is often based on past user behavior, preferences, and interaction context. We argue that personality traits provide a promising additional source of information for personalization, which goes beyond context- and device-specific behavior and preferences. We first give an overview of the well-established Big Five personality trait model from psychology. We then present previous findings on the influence of personality in HCI associated with the benefits and challenges of personalization. These findings include the preference for interactive systems, filtering of information to increase personal relevance, communication behavior, and the impact on trust and acceptance. Moreover, we present first approaches of personality-based recommender systems. We then identify several opportunities and use cases for personality-aware personalization: (i) personal communication between users, (ii) recommendations upon first use, (iii) persuasive technology, (iv) trust and comfort in autonomous vehicles, and (v) empathic intelligent systems. Furthermore, we highlight main challenges. First, we point out technological challenges of personality computing. To benefit from personality awareness, systems need to automatically assess the user’s personality. To create empathic intelligent agents (e. g., voice assistants), a consistent personality has to be synthesized. Second, personality-aware personalization raises questions about user concerns and views, particularly privacy and data control. Another challenge is acceptance and trust in personality-aware systems due to the sensitivity of the data. Moreover, the importance of an accurate mental model for users’ trust in a system was recently underlined by the right for explanations in the EU’s General Data Protection Regulation. Such considerations seem particularly relevant for systems that assess and utilize personality. Finally, we examine methodological requirements such as the need for large sample sizes and appropriate measurements. We conclude with a summary of opportunities and challenges of personality-aware personalization and discuss future research questions.

Abstract

This chapter discusses main opportunities and challenges of assessing and utilizing personality traits in personalized interactive systems and services. This unique perspective arises from our long-term collaboration on research projects involving three groups on human-computer interaction (HCI), psychology, and statistics. Currently, personalization in HCI is often based on past user behavior, preferences, and interaction context. We argue that personality traits provide a promising additional source of information for personalization, which goes beyond context- and device-specific behavior and preferences. We first give an overview of the well-established Big Five personality trait model from psychology. We then present previous findings on the influence of personality in HCI associated with the benefits and challenges of personalization. These findings include the preference for interactive systems, filtering of information to increase personal relevance, communication behavior, and the impact on trust and acceptance. Moreover, we present first approaches of personality-based recommender systems. We then identify several opportunities and use cases for personality-aware personalization: (i) personal communication between users, (ii) recommendations upon first use, (iii) persuasive technology, (iv) trust and comfort in autonomous vehicles, and (v) empathic intelligent systems. Furthermore, we highlight main challenges. First, we point out technological challenges of personality computing. To benefit from personality awareness, systems need to automatically assess the user’s personality. To create empathic intelligent agents (e. g., voice assistants), a consistent personality has to be synthesized. Second, personality-aware personalization raises questions about user concerns and views, particularly privacy and data control. Another challenge is acceptance and trust in personality-aware systems due to the sensitivity of the data. Moreover, the importance of an accurate mental model for users’ trust in a system was recently underlined by the right for explanations in the EU’s General Data Protection Regulation. Such considerations seem particularly relevant for systems that assess and utilize personality. Finally, we examine methodological requirements such as the need for large sample sizes and appropriate measurements. We conclude with a summary of opportunities and challenges of personality-aware personalization and discuss future research questions.

Chapters in this book

  1. Frontmatter I
  2. Introduction V
  3. Contents IX
  4. List of Contributing Authors XI
  5. Part I: Foundations of user modeling
  6. 1. Theory-grounded user modeling for personalized HCI 1
  7. 2. Opportunities and challenges of utilizing personality traits for personalization in HCI 31
  8. Part II: User input and feedback
  9. 3. Automated personalization of input methods and processes 67
  10. 4. How to use socio-emotional signals for adaptive training 103
  11. 5. Explanations and user control in recommender systems 133
  12. Part III: Personalization approaches
  13. 6. Tourist trip recommendations – foundations, state of the art, and challenges 159
  14. 7. Pictures as a tool for matching tourist preferences with destinations 183
  15. 8. Towards personalized virtual reality touring through cross-object user interfaces 201
  16. 9. User awareness in music recommender systems 223
  17. 10. Personalizing the user interface for people with disabilities 253
  18. 11. Adaptive workplace learning assistance 283
  19. Index 303
https://doi.org/10.1515/9783110552485-002

Chapters in this book

  1. Frontmatter I
  2. Introduction V
  3. Contents IX
  4. List of Contributing Authors XI
  5. Part I: Foundations of user modeling
  6. 1. Theory-grounded user modeling for personalized HCI 1
  7. 2. Opportunities and challenges of utilizing personality traits for personalization in HCI 31
  8. Part II: User input and feedback
  9. 3. Automated personalization of input methods and processes 67
  10. 4. How to use socio-emotional signals for adaptive training 103
  11. 5. Explanations and user control in recommender systems 133
  12. Part III: Personalization approaches
  13. 6. Tourist trip recommendations – foundations, state of the art, and challenges 159
  14. 7. Pictures as a tool for matching tourist preferences with destinations 183
  15. 8. Towards personalized virtual reality touring through cross-object user interfaces 201
  16. 9. User awareness in music recommender systems 223
  17. 10. Personalizing the user interface for people with disabilities 253
  18. 11. Adaptive workplace learning assistance 283
  19. Index 303
Sign up now to receive a 20% welcome discount
Institutional Access
How does access work?
Have an idea on how to improve our website?
Please write us.
© 2025 De Gruyter Brill
Downloaded on 7.11.2025 from https://www.degruyterbrill.com/document/doi/10.1515/9783110552485-002/html
Scroll to top button