P
Pietro Panzarasa
Researcher at Queen Mary University of London
Publications - 71
Citations - 3504
Pietro Panzarasa is an academic researcher from Queen Mary University of London. The author has contributed to research in topics: Complex network & Centrality. The author has an hindex of 22, co-authored 70 publications receiving 2962 citations. Previous affiliations of Pietro Panzarasa include University of London & London School of Business and Management.
Papers
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Journal ArticleDOI
Clustering in weighted networks
Tore Opsahl,Pietro Panzarasa +1 more
TL;DR: This paper focuses on a measure originally defined for unweighted networks: the global clustering coefficient, and proposes a generalization of this coefficient that retains the information encoded in the weights of ties.
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Prominence and Control: The Weighted Rich-Club Effect
TL;DR: A new general framework for studying the tendency of prominent elements to form clubs with exclusive control over the majority of a system's resources is proposed and associations between prominence and control in the fields of transportation, scientific collaboration, and online communication are explored.
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Patterns and dynamics of users' behavior and interaction: Network analysis of an online community
TL;DR: This research draws on longitudinal network data from an online community to examine patterns of users' behavior and social interaction, and infer the processes underpinning dynamics of system use and for a host of applications, including information diffusion, communities of practice, and the security and robustness of information systems.
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Multiplex PageRank
TL;DR: Taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer, and provides support in favor of the salience of multiplex centrality measures, like Multiplex PageRank.
Journal ArticleDOI
Weighted Multiplex Networks
TL;DR: A theoretical framework based on the entropy of multiplex ensembles is introduced to quantify the information stored in multiplex networks that would remain undetected if the single layers were analyzed in isolation.