메뉴 건너뛰기
Library Notice
Institutional Access
If you certify, you can access the articles for free.
Check out your institutions.
ex)Hankuk University, Nuri Motors
Log in Register Help KOR
Subject

A Study on the Development of Interaction Design Framework Based on Personality of Customized Chatbot Design
Recommendations
Search
Questions

맞춤형 챗봇 디자인을 위한 성격(Personality) 중심의 인터랙션 디자인 프레임워크 개발에 관한 연구

논문 기본 정보

Type
Academic journal
Author
Yoo, Hanna (서울여자대학교) Lee, Jihyun (서울여자대학교)
Journal
Design Institute, Inje University Journal of Integrated Design Research Vol.18 No.1(Wn.45) KCI Accredited Journals
Published
2019.3
Pages
77 - 94 (18page)

Usage

cover
📌
Topic
📖
Background
🔬
Method
🏆
Result
A Study on the Development of Interaction Design Framework Based on Personality of Customized Chatbot Design
Ask AI
Recommendations
Search
Questions

Research history (4)

  • Are you curious about the follow-up research of this article?
  • You can check more advanced research results through related academic papers or academic presentations.
  • Check the research history of this article

Abstract· Keywords

Report Errors
Background : There is a growing interest in chatbot with excellent usability and convenience. Users perceive chatbot as a person with personality that helps people to interact more naturally. The personality of chatbot determines not only the tone and manner of conversation but also the information and form, and it is important to give a consistency suitable for characteristics of service and user because user`s perception and response are different according to personality. However, there is not much studies that is clear criteria for chatbots and interaction design suitable for personality.
Methods : In this study, it is proposed the new personality types classification framework of chatbot focusing on overall interaction based on literature research and limitations of previous research. The framework is based on DISC model that can apply interaction effectively by extroverted behavioral standard, so 9 kinds of personality types are derived by converting standards to personality of task and information providing method. And based on the interaction elements of chatbot, it developed the interaction design framework based on the personality for the customized chatbot design that is derived the interaction design guidelines and principles. The UI is created by applying the actual service as a customized chatbot with multiple personality types. Finally, the validity of the framework and the suitability of the interaction based on the personality were verified through the expert evaluation.
Result : As a result of the verification, it was evaluated that the framework created in this study has high value in developing chatbot. It could easily design chatbot with multiple personality and would be useful to suggest new interactions. However, it has received a low rating for delicate interactions such as microinteractions. So it is necessary to secure the interaction design framework in the future.
Conclusion : As a result, interaction design framework focused on personality of customized chatbot design will make designer easy to design a chatbot systematically by selecting the personality of chatbot according to the purpose of service and user`s needs. In addition, the user can use the chatbot service having the most suitable personality by developing multiple personality types that meet the various needs of user. This will make users and chatbots to build intimate relationships, and deliver information to users through appropriate interactions to personality.

Contents

요약
Abstract
1. 서론
2. 챗봇의 디자인과 성격(Personality) 관련 연구
3. 챗봇의 성격 유형(Personality Types) 분류 및 분석
4. 맞춤형 챗봇 디자인을 위한 성격(Personality) 중심의 인터랙션 디자인 프레임워크 개발
5. 챗봇의 성격을 중심으로 한 UI 프로토타이핑 적용 및 검증
6. 결론 및 향후 연구과제
참고문헌

References (12)

Add References

Recommendations

It is an article recommended by DBpia according to the article similarity. Check out the related articles!

Related Authors

Frequently Viewed Together

Recently viewed articles

Comments(0)

0

Write first comments.