Complex Networks X [electronic resource] : Proceedings of the 10th Conference on Complex Networks CompleNet 2019 /
Cornelius, Sean P.editor.
Granell Martorell, Clara.editor.
Gómez-Gardeñes, Jesús.editor.
Gonçalves, Bruno.editor.
This book aims to bring together researchers and practitioners working across domains and research disciplines to measure, model, and visualize complex networks. It collects the works presented at the 10th International Conference on Complex Networks (CompleNet) in Tarragona, Spain, March, 2019. With roots in physical, information and social science, the study of complex networks provides a formal set of mathematical methods, computational tools and theories to describe, prescribe and predict dynamics and behaviors of complex systems. Despite their diversity, whether the systems are made up of physical, technological, informational, or social networks, they share many common organizing principles and thus can be studied with similar approaches. This book provides a view of the state-of-the-art in this dynamic field and covers topics such as group decision-making, brain and cellular connectivity, network controllability and resiliency, online activism, recommendation systems, and cyber security. This text will appeal to students and researchers in the field.
Observability of dynamical networks from graphic and symbolic approaches -- Exploratory factor analysis of graphical features for link prediction in social networks -- An efficient approach for counting occurring induced subgraphs -- A Generalized Configuration Model with Degree Correlations -- Missing Data Augmentation for Bayesian Exponential Random Multi-Graph Models -- Spread and control of misinformation with heterogeneous agents -- Long-Term Behavior in Evolutionary Dynamics from Ergodicity Breaking -- Combining path-constrained random walks to recover link weights in heterogeneous information networks -- The Structure and Evolution of an Offline Peer-to-Peer Financial Network -- Modelling students' thematically associated knowledge: Networked knowledge from affinity statistics -- Graph Convolutional Networks on Customer/Supplier Graph Data to Improve Default Prediction -- Multidimensional Outlier Detection in Interaction Data: Application to Political Communication on Twitter -- Social Media Vocabulary Reveals Education Attainment of Populations -- Exploring the role and nature of interactions between Institutes in a Local Affiliation Network.
This book aims to bring together researchers and practitioners working across domains and research disciplines to measure, model, and visualize complex networks. It collects the works presented at the 10th International Conference on Complex Networks (CompleNet) in Tarragona, Spain, March, 2019. With roots in physical, information and social science, the study of complex networks provides a formal set of mathematical methods, computational tools and theories to describe, prescribe and predict dynamics and behaviors of complex systems. Despite their diversity, whether the systems are made up of physical, technological, informational, or social networks, they share many common organizing principles and thus can be studied with similar approaches. This book provides a view of the state-of-the-art in this dynamic field and covers topics such as group decision-making, brain and cellular connectivity, network controllability and resiliency, online activism, recommendation systems, and cyber security. This text will appeal to students and researchers in the field.
Physics.
Social sciences-Data processing.
Social sciences-Computer programs.
Computational intelligence.
Artificial intelligence.
Computational complexity.
Applications of Graph Theory and Complex Networks.
Computational Social Sciences.
Computational Intelligence.
Artificial Intelligence.
Complexity.