Journal of Visualization

, Volume 21, Issue 5, pp 885–901 | Cite as

VisUPI: visual analytics for University Personality Inventory data

  • Zhiguang Zhou
  • Xiangjun Zhu
  • Yuhua Liu
  • Qianqian Ren
  • Changbo Wang
  • Tianlong GuEmail author
Regular Paper


It is a feasible way to investigate the mental health status of college students through University Personality Inventory (UPI). However, the analysis of original UPI data is a difficult and tedious task, because the traditional software always requires the users to select and reload slices of data by hand. Also, the limited constant functions provided by the software cannot meet the various requirements of domain experts. In this paper, we propose VisUPI, a specialized visualization framework for UPI datasets, aiming at an in-depth analysis of the mental health status of college students. A circular view is firstly designed to layout the questionnaires and visualize the answers of individuals. Then, a decision tree model is employed to classify the investigated students, and a radial hierarchy chart is designed to present the relationship of different groups of students. According to the prior knowledge of UPI, we restructure the network relationship of specified questionnaires, and use the force-directed model to layout the questionnaires, enabling users to better perceive the answers of those students with serious mental health problems. Furthermore, multi-dimensional scaling is used to visualize the dissimilarity between different questionnaires, and the statistical answers are presented through bar charts in detail. Finally, the effectiveness and scalability of VisUPI are demonstrated through case studies with the real-world datasets and the domain-expert interviews.

Graphical Abstract


Visual analytics UPI Visual design Mental health Hierarchy visualization 



This work was supported by NFS of China Project Nos. 61303133, U1501252, U1711263, the Natural Science Foundation of Zhejiang Province No. LY18F020024, the National Statistical Scientific Research Project No. 2015LD03 and the First Class Discipline of Zhejiang—A (Zhejiang University of Finance and Economics-Statistics).

Supplementary material

Supplementary material 1 (mp4 8554 KB)


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Copyright information

© The Visualization Society of Japan 2018

Authors and Affiliations

  • Zhiguang Zhou
    • 1
  • Xiangjun Zhu
    • 1
  • Yuhua Liu
    • 1
  • Qianqian Ren
    • 2
  • Changbo Wang
    • 3
  • Tianlong Gu
    • 4
    Email author
  1. 1.Zhejiang University of Finance and EconomicsHangzhouChina
  2. 2.Zhejiang University of Water Resources and Electric PowerHangzhouChina
  3. 3.East China Normal UniversityShanghaiChina
  4. 4.Guilin University of Electronic TechnologyGuilinChina

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