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This study uses graph representation learning techniques to study the organizational inter-connections established through labor mobility flows in Friuli Venezia Giulia, a medium-sized region in northern Italy ranked as one of the leading regions for innovation. The regional labor flow network is constructed from regional data on the commencement or termination of employment contract. The methods employed, Node2Vec and Role2Vec, allow for a visualization of the community structures and the centrality of universities and research institutions in the network. The study demonstrates the potential of such techniques for analyzing complex networks and uncovering hidden structures by identifying the role of specific firms/organizations, which can be of interest to public decision-makers.

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Visualization of Proximity and Role-Based Embeddings in a Regional Labor Flow Network

  • 会议论文

  • 发表日期：

    2025年

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  • Sara Geremia,
  • Fabio Morea,
  • Domenico De Stefano

摘要

This study uses graph representation learning techniques to study the organizational inter-connections established through labor mobility flows in Friuli Venezia Giulia, a medium-sized region in northern Italy ranked as one of the leading regions for innovation. The regional labor flow network is constructed from regional data on the commencement or termination of employment contract. The methods employed, Node2Vec and Role2Vec, allow for a visualization of the community structures and the centrality of universities and research institutions in the network. The study demonstrates the potential of such techniques for analyzing complex networks and uncovering hidden structures by identifying the role of specific firms/organizations, which can be of interest to public decision-makers.