Panacea: Visual exploration system for analyzing trends in annual recruitment using time-varying graphs

Area of Science:

• Data Visualization
• Human Resources Management
• Network Analysis

Background:

• Manual analysis of annual graduate recruitment data by HR specialists is time-consuming and prone to errors.
• Unnormalized applicant attributes complicate trend analysis and comparison across years.
• Existing methods lack effective tools for visualizing recruitment trends over time.

Purpose of the Study:

• To develop a visual exploration system for analyzing graduate recruitment trends.
• To enable HR specialists to inspect relationships between applicant attributes across multiple years.
• To address the need for better insight into recruitment data.

Main Methods:

• Proposed the Polarizing Attributes for Network Analysis of Correlation on Entities Association (Panacea) visualization system.
• Integrated a time-varying graph model with dynamic graph visualization for heterogeneous tabular data.
• Enabled interactive inspection of relationships between prospective employee attributes.

Main Results:

• Demonstrated Panacea's usability with real-world datasets.
• Identified hidden trends in annual recruitment data.
• Gathered feedback from HR specialists during development.

Conclusions:

• Panacea provides HR specialists with a powerful tool for visually exploring graduate recruitment.
• The system facilitates a deeper understanding of recruitment dynamics and applicant qualifications.
• Interactive visualization enhances the evaluation of recruitment strategies.