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This book compiles the proceedings of the 16th International Conference on Complex Networks (CompleNet 2025), a distinguished gathering that has united researchers and practitioners from diverse fields since 2009. CompleNet's interdisciplinary approach highlights the pervasive applications of complex networks across various domains, including biological, technical, informational, economic, and social systems. Known for its plenary sessions and balanced participation, CompleNet 2025 offered a platform for engaging with the latest advancements in Network Science.
The chapters in this volume cover a wide array of topics, such as Computational Social Science, Dynamics on and of Networks, Ecological Networks, Epidemic Modelling, Network Algorithms, and Networked Medicine. These contributions reflect the extensive range of discussions at the conference, advancing our understanding of Network Science and its applications. A notable highlight was the panel discussion on Network Science and Responsible Artificial Intelligence, emphasizing the importance of ethical considerations in technological development.
CompleNet 2025 also introduced a dedicated session for students from Ceará, fostering inclusivity and providing young researchers with invaluable exposure to international scientific discourse. This initiative aligns with CompleNet's mission to democratize access to scientific knowledge and nurture the next generation of network scientists.
This proceedings is an invaluable resource for researchers, scholars, and practitioners in Network Science, Data Science, and Complex Systems. It offers a comprehensive overview of current research trends and innovations, making it essential reading for anyone interested in understanding the complexities of interconnected systems. Whether you are a seasoned researcher or a newcomer to the field, CompleNet 2025 provides insights and inspiration for exploring the dynamic world of complex networks.
Sommario
A simple and flexible algorithm to generate real world networks.- A framework for efficient estimation of closeness centrality and eccentricity in large networks.- Network Centric Analysis of Memetic Operators and Communication Topologies for Swarm Intelligence Algorithms.- A Hybrid Framework for Quantifying and Analyzing the Structural Properties of Human Retinal Vessel Networks.- An approach based on Networks and Machine Learning for gastric cancer treatment recommendation.- Population dynamics in the global coral symbiont network under temperature variations.- Dengue serotypes cyclicity evidenced by the impact frequency histogram of the visibility graph.- The Brazilian Maritime Network during the COVID 19 pandemic: Analysis of Topologies and Impacts on Connectivity.- Understanding the Structure and Resilience of the Brazilian Federal Road Network Through Network Science.- Improving flocking behaviors in street networks with vision.- Social circles impact on opinion dynamics.
