This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the VI International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2017), which took place in Lyon on November 29 December 1, 2017. The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and ecological networks and technological networks.

Presents recent research on complex networks and their applications

Gathers the edited proceedings of the sixth International Workshop on Complex Networks and their Applications (COMPLEX NETWORKS 2017) conference which took place in Lyon, France on November 29 December 1, 2017

Presents state-of-the-art research on complex networks, including various research directions

Includes supplementary material: sn.pub/extras

Autorentext

Klappentext

Inhalt
Part I: Network measures.- A comparison of approaches to computing betweenness centrality for large graphs.- Cycle-centrality in economic and biological networks.- A game theoretic neighbourhood-based relevance index.- The impact of partially missing communities on the reliability of centrality measures.- Consistent estimation of mixed memberships with successive projections.- Reducing pivots of approximated betweenness computation by hierarchically clustering complex networks.- Power network equivalents: a network science based k-means clustering method integrated with silhouette analysis.- Part II: Link Analysis and Ranking.- Newton's gravitational law for link prediction in social networks.- Efcient outlier detection in hyperedge streams using minHash and locality-sensitive hashing.- Layer-wise model stacking for link prediction in multilayer networks. Case of scientic collaboration networks.- Evolutionary community mining for link prediction in dynamic networks.- Rank aggregation for course sequence discovery.- Part III: Community Structure.- Community-based feature selection for credit card default prediction.- Tracking bitcoin users activity using community detection on a network of weak signals.