Natural Language Processing, Contracting Networks, and Linked Company Data

This webinar is the second seminar in our series exploring innovative approaches to analysing corruption risks in public procurement through data-driven methods.

The session will review the latest developments in proxying corruption risks in public procurement and present recent advances in three major areas of scientific research:

• Natural language processing (NLP) applied to large volumes of tender announcement texts
• Network science methods used to analyse contracting networks of suppliers and buyers
• Machine learning techniques applied to linked company data to identify potential political connections

By combining these approaches, the seminar will illustrate how emerging computational tools can improve transparency and strengthen the detection of corruption risks in public procurement systems.

Presenter

Mihály Fazekas (Central European University – CEU)
Mihály Fazekas is a Professor at the Central European University, Department of Public Policy. His research focuses on applying data science methods to understand and measure the quality of government worldwide, particularly in the areas of corruption, public procurement, and governance analytics.

Event details

📅 20 April 2026
🕒 15:00 (CET)
Organised by the Central European University (CEU) with the support of University of Bologna and S-Com AISBL

Registration

Please register via the following link: https://forms.gle/2wLNKjmprQpkrXUTA