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20092026
most citedOpinion fluctuations and disagreement in social networks

378 citations · 576 across the 50 of their papers we have counts for

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13 papers · 1 filter

eess.SY2025

Optimal Control of Behavioral-Feedback SIR Epidemic Model

Martina Alutto, Leonardo Cianfanelli, Giacomo Como +2

We consider a behavioral-feedback SIR epidemic model, in which the infection rate depends in feedback on the fractions of susceptible and infected agents. Contrary to the classic S…

eess.SY2025

Continuous-Time Distributed Learning for Collective Wisdom Maximization

Luka Baković, Giacomo Como, Fabio Fagnani +2

Motivated by the well established idea that collective wisdom is greater than that of an individual, we propose a novel learning dynamics as a sort of companion to the Abelson mode…

eess.SY2025★ 1 cited

Controlling a Social Network of Individuals with Coevolving Actions and Opinions

Roberta Raineri, Mengbin Ye, Lorenzo Zino

In this paper, we consider a population of individuals who have actions and opinions, which coevolve, mutually influencing one another on a complex network structure. In particular…

eess.SY2024

An invariance principle based concentration result for large-scale stochastic pairwise interaction network systems

Giacomo Como, Fabio Fagnani, Sandro Zampieri

We study stochastic pairwise interaction network systems whereby a finite population of agents, identified with the nodes of a graph, update their states in response to both indivi…

eess.SY2023

Nash equilibria of the pay-as-bid auction with K-Lipschitz supply functions

Martina Vanelli, Giacomo Como, Fabio Fagnani

We model a system of n asymmetric firms selling a homogeneous good in a common market through a pay-as-bid auction. Every producer chooses as its strategy a supply function returni…

eess.SY2020★ 48 cited

Imitation dynamics in population games on community networks

Giacomo Como, Fabio Fagnani, Lorenzo Zino

We study the asymptotic behavior of deterministic, continuous-time imitation dynamics for population games over networks. The basic assumption of this learning mechanism -- encompa…

eess.SY2019

Fast Spread in Controlled Evolutionary Dynamics

Lorenzo Zino, Giacomo Como, Fabio Fagnani

We study the spread of a novel state in a network, in the presence of an exogenous control. The considered controlled evolutionary dynamics is a non-homogeneous Markov process that…

eess.SY2019

Finite-time influence systems and the Wisdom of Crowd effect

Francesco Bullo, Fabio Fagnani, Barbara Franci

Recent contributions have studied how an influence system may affect the wisdom of crowd phenomenon. In the so-called naive learning setting, a crowd of individuals holds opinions…

eess.SY2018★ 3 cited

On stochastic imitation dynamics in large-scale networks

Lorenzo Zino, Giacomo Como, Fabio Fagnani

We consider a broad class of stochastic imitation dynamics over networks, encompassing several well known learning models such as the replicator dynamics. In the considered models,…

eess.SY2017★ 16 cited

On imitation dynamics in potential population games

Lorenzo Zino, Giacomo Como, Fabio Fagnani

Imitation dynamics for population games are studied and their asymptotic properties analyzed. In the considered class of imitation dynamics - that encompass the replicator equation…

eess.SY2015★ 32 cited

From local averaging to emergent global behaviors: the fundamental role of network interconnections

Giacomo Como, Fabio Fagnani

Distributed averaging is one of the simplest and most studied network dynamics. Its applications range from cooperative inference in sensor networks, to robot formation, to opinion…

eess.SY2015★ 3 cited

The robustness of democratic consensus

Fabio Fagnani, Jean-Charles Delvenne

In linear models of consensus dynamics, the state of the various agents converges to a value which is a convex combination of the agents' initial states. We call it democratic if i…

eess.SY2013

Limited benefit of cooperation in distributed relative localization

Wilbert Samuel Rossi, Paolo Frasca, Fabio Fagnani

Important applications in robotic and sensor networks require distributed algorithms to solve the so-called relative localization problem: a node-indexed vector has to be reconstru…