Boudoua Bahdja is a second year PhD student at the UMR TETIS. She received a veterinary medicine training from the higher school of veterinary medicine (ENSV) of Algiers, and holds a master’s degree in Epidemiology from Paul-Sabatier University, Toulouse, France. Her work is part of the MOOD project H2020 and focuses on The Identification, qualification and integration of epidemiological indicators from multi-source textual data. The work she presented was conducted during her Master’s degree Internship. Its context and purpose are described below: Epidemic intelligence (EI) has been adopted by several countries to reach fast detection of new and emerging infectious diseases. EI collects information from two types of sources: official sources (i.e. health reports from OIE or FAO) and unofficial sources (i.e. online media outlets, scientific publications, etc.). In France, the EI system PADI-web (Platform for Automated extraction of Disease Information from the Web) is used since 2014 to detect signals of animal health events with risk of introduction to France. The objective of this work was to understand how health information (signal) is disseminated from a primary source (transmitter) to a final source (EI system) through quantitative and qualitative network analysis methods.