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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.

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Social Medical Capital: How Patients and Caregivers Can Benefit From Online Social Interactions.

TL;DR: In this paper, the authors outline a new network-based theory of social medical capital that will open up new avenues for conducting large-scale network studies of online health communities and devising effective policy interventions aimed at improving patients' self-care and health.
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Social influence, negotiation and cognition

TL;DR: An agent-based computational model of negotiation in which social influence plays a key role in the attainment of social and cognitive integration is developed, which provides insights into the trade-offs typically involved in the exercise of social influence.
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The bridging and bonding structures of place-centric networks: Evidence from a developing country.

TL;DR: This article constructs place-centric communication and mobility networks in the city of Abidjan in Côte d’Ivoire, and suggests that both closed and open structures can serve as wellsprings of social capital.
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Quantifying the Alignment of Graph and Features in Deep Learning.

TL;DR: It is shown that the classification performance of graph convolutional networks (GCNs) is related to the alignment between features, graph, and ground truth, which is quantified using a subspace alignment measure corresponding to the Frobenius norm of the matrix of pairwise chordal distances between three subspaces.
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Emergence of long-range correlations and bursty activity patterns in online communication.

TL;DR: Analysis of patterns of human activity within an online forum in which communication can be assessed at three intertwined levels indicates that, when users are solipsistic, their bursty behavior is not sufficient for generating heavy-tailed interevent time distributions at a higher level, but when users is socially interdependent, the power spectra and intereven time distributions are remarkably similar at all levels of analysis.