activity
20122024
most citedDEMON: a Local-First Discovery Method for Overlapping Communities

41 citations · 44 across the 6 of their papers we have counts for

collaborators

6 papers

physics.soc-ph2024

"A network of mutualities of being": socio-material archaeological networks and biological ties at Çatalhöyük

Camilla Mazzucato, Michele Coscia, Ayça Küçükakdağ Doğu +4

Recent advances in archaeogenomics have granted access to previously unavailable biological information with the potential to further our understanding of past social dynamics at a…

cs.SI2024

Pearson Correlations on Networks: Corrigendum

Michele Coscia, Karel Devriendt

Recently, the first author proposed a measure to calculate Pearson correlations for node values expressed in a network, by taking into account distances or metrics defined on the n…

cs.SI2023

Fast Node Vector Distance Computations using Laplacian Solvers

Michele Coscia, Karel Devriendt

Complex networks are a useful tool to investigate various phenomena in social science, economics, and logistics. Node Vector Distance (NVD) is an emerging set of techniques allowin…

cs.LG20232 cited

Unsupervised Learning via Network-Aware Embeddings

Anne Sophie Riis Damstrup, Sofie Tosti Madsen, Michele Coscia

Data clustering, the task of grouping observations according to their similarity, is a key component of unsupervised learning -- with real world applications in diverse fields such…

q-fin.GN20161 cited

Exploring the Uncharted Export: an Analysis of Tourism-Related Foreign Expenditure with International Spend Data

Michele Coscia, Ricardo Hausmann, Frank Neffke

Tourism is one of the most important economic activities in the world: for many countries it represents the single largest product in their export basket. However, it is a product…

cs.DS201241 cited

DEMON: a Local-First Discovery Method for Overlapping Communities

Michele Coscia, Giulio Rossetti, Fosca Giannotti +1

Community discovery in complex networks is an interesting problem with a number of applications, especially in the knowledge extraction task in social and information networks. How…