Members of the NOVA Applied Economics & Analytics Lab participated in the Complex Networks 2025 conference, contributing to international discussions on network science, complex systems, and applied network methodologies.
Location: Binghamton, New York (USA)
Date: December 2025
Conference website: https://www.complexnetworks.org
Carolina Shaul
“Mapping Mobility Networks between Government Roles in Portugal”
Proceedings paper - Complex Networks 2025
🏆 Best Oral Presentation Award
This paper examines career mobility within Portuguese governments (2011-2025), focusing on both formal government members (Ministers and Secretaries of State) and their private office staff. Using data from official government records, the study constructs mobility networks based on shared career trajectories across governmental positions and policy domains.
The analysis of network structure and centrality measures reveals distinct patterns of cross-portfolio mobility and career progression, highlighting the central role of advisory staff in connecting otherwise fragmented networks. In contrast, top political offices such as Ministers and Prime Ministers appear structurally peripheral. The results also show that certain policy domains, such as Presidency and Modernization, play a key bridging role across government portfolios, while highly specialized domains remain largely isolated.
Luís Semedo
Niclas Sturm
Two research contributions at Complex Networks 2025, highlighting both published and ongoing work developed within the Lab:
“The Structure of Firm Networks in Public Procurement Markets”
Presentation based on the published article:
“High Earnings through Firm Influence: The Role of Hierarchical Structures in Public Procurement”
“Augmenting Firm Diversification Behavior Prediction with Graph Embeddings”
Research focusing on the use of network representations and graph embeddings to enhance predictive performance in firm-level analysis.
This work was presented as ongoing research and is expected to be included in the conference proceedings.
These presentations reinforced the Lab’s expertise in network-based analysis of public procurement markets and advanced graph-based machine learning methods.