Luís Ramada Pereira
Community detection and evolution in temporal networks
Networks are all around us: computer, telecommunication, biological and social systems are just a few examples of networks of entities that interact and relate to one another in some specifiable way, producing identifiable phenomena. Network science is concerned with understanding networked systems, describing their micro, meso and macro scale attributes and helping us predict their behavior.
Many networks exhibit groups of nodes that are more closely interconnected amongst themselves than with the rest of the network. These groups, referred to as clusters in graph theory or communities in network science, are usually of interest to network researchers. They usually have an over-sized impact on the network behavior and their identification is often highly useful.
More specifically, we research answers to key questions, such as:
We are currently applying the methods we have developed to the analysis of real-life complex systems in sports science, by studying sport modalities whose practice can be expressed as a temporal network.