Visualizing the Demand and Supply of Skills in the Industry using Signed Network Analysis

Abstract

Since the skills possessed by engineers do not always match the skills required for a job, visualization of the demand and supply of skills is significant for both macro resource allocation and career advancement of engineers. In this study, we construct a signed network that integrates the demand and supply of skills, and use network analysis techniques to clarify the multi-scale relationships among skills. We classify and visualize skills by extracting skill sets that focus on the largest clique in the signed network, applying a community extraction method hierarchically. We interpret the results and findings with considerable suggestions. Finally, we compare signed skill networks by industry to identify field-specific skill sets and provide insights for crossdisciplinary human resource development.