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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
Efficient outlier detection in hyperedge streams using minHash and locality-sensitive hashing
Layer-wise model stacking for link prediction in multilayer networks. Case of scientific 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.

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