The aim of this thesis is to advance our ability to model the decision making-process in social systems, with the overarching goal of helping policymakers and government bodies take mathematically backed decisions. Toward this aim, we adapted a complex network approach, leveraging tools from network science, control theory, and social science which altogether offers a powerful and multidisciplinary approach to tackle the complexity that pervades social dynamics. We explored the conditions under which we can confer given controllability and observability properties to complex networks of dynamical systems, so to have an insight on our ability to steer or monitor their collective behaviors in the presence of realistic constraints. Then, we studied the opinion dynamics in groups of interconnected individuals discussing on a given topic, that is, we analyzed the evolution over time of their opinions under the effect of social ties and other psychological traits, such as stubbornness or the tendency to conform. Opinions dynamics models enable us to describe the collective behaviors that occur in real world social groups and to unveil how the social interactions, namely the peer pressure and other biases, shape our opinion formation and result in the group exhibiting behaviors such as consensus, disagreement, or polarization of opinions. In particular, we analyzed how external influences, such as the ones exerted by opinion leaders (the so-called influencers) can steer the opinion profile of a social group towards a desired state at steady state. To this aim, we borrowed a tool from network control, namely pinning control, to show how agents with relatively few connections can exploit the structure of the social interconnections to diffuse their influence throughout the social group. Using heuristic approaches and leveraging theoretical and graphical knowledge of the network dynamical systems under investigation, we showed that a smart selection of the individuals to directly influence allows to maximize the effect of persuading actions of opinion leaders. Finally, we illustrated how the model we proposed can provide quantitative predictions on opinions' distribution in a given population, which in turn can be used to gauge the effectiveness of different awareness campaigns strategies aimed at mitigating vaccine hesitancy.

L'obiettivo di questa tesi è quello di migliorare la nostra abilità di modellare i processi decisionali nei sistemi sociali, con l'obiettivo ultimo di supportare i decisori e gli enti governativi a prendere decisioni supportate da studi quantitativi. In questa direzione, abbiamo adattato l'approccio delle reti complesse, combinando diverse tecniche tipiche della teoria del controllo di sistemi dinamici e dalle scienze sociali per fornire uno strumento efficace e multidisciplinare per affrontare la complessità che caratterizza le dinamiche sociali. Per farlo, in questa tesi esploriamo innanzitutto le condizioni in cui è possibile conferire determinate proprietà di controllabilità e osservabilità a reti complesse di sistemi dinamici, al fine di quantificare la nostra capacità di guidare o monitorare i loro comportamenti collettivi in presenza di vincoli quanto più realistici possibili. Successivamente, dedichiamo la nostra attenzione a determinate reti complesse e cioè i sistemi sociali, in particolare allo studio della dinamica delle opinioni in gruppi di individui interconnessi che discutono su un certo argomento, ossia all'analisi dell'evoluzione nel tempo delle loro opinioni sotto l'effetto dell'influenza dei legami sociali e di altri meccanismi psicologici. Modellare la dinamica delle opinioni ci consente di descrivere i comportamenti collettivi che si verificano nei gruppi sociali del mondo reale e di svelare come le interazioni sociali, vale a dire la pressione dei pari e altri pregiudizi, plasmino la formazione delle opinioni e portino il gruppo a manifestare comportamenti colletivi quali il consenso, il disaccordo o la polarizzazione delle opinioni. In questo contesto, abbiamo analizzato come influenze esterne, come quelle esercitate da personaggi che godono di una certa visibilità, i cosiddetti influencer, possano indirizzare il profilo delle opinioni di un gruppo sociale verso uno stato desiderato di regime. Ciò è stato fatto attraverso l'utilizzo di strumenti di controllo delle reti, ovvero il controllo pinning, che ci consente di comprendere come agenti con relativamente poche connessioni siano in grado di sfruttare la struttura delle interconnessioni sociali per persuadere il gruppo sociale.

(2024). Modelli dinamici di processi decisionali in reti sociali: un approccio ai sistemi complessi . Retrieved from https://hdl.handle.net/10446/265073 Retrieved from http://dx.doi.org/10.13122/ancona-camilla_phd2024-02-20

Modelli dinamici di processi decisionali in reti sociali: un approccio ai sistemi complessi

ANCONA, Camilla
2024-02-20

Abstract

The aim of this thesis is to advance our ability to model the decision making-process in social systems, with the overarching goal of helping policymakers and government bodies take mathematically backed decisions. Toward this aim, we adapted a complex network approach, leveraging tools from network science, control theory, and social science which altogether offers a powerful and multidisciplinary approach to tackle the complexity that pervades social dynamics. We explored the conditions under which we can confer given controllability and observability properties to complex networks of dynamical systems, so to have an insight on our ability to steer or monitor their collective behaviors in the presence of realistic constraints. Then, we studied the opinion dynamics in groups of interconnected individuals discussing on a given topic, that is, we analyzed the evolution over time of their opinions under the effect of social ties and other psychological traits, such as stubbornness or the tendency to conform. Opinions dynamics models enable us to describe the collective behaviors that occur in real world social groups and to unveil how the social interactions, namely the peer pressure and other biases, shape our opinion formation and result in the group exhibiting behaviors such as consensus, disagreement, or polarization of opinions. In particular, we analyzed how external influences, such as the ones exerted by opinion leaders (the so-called influencers) can steer the opinion profile of a social group towards a desired state at steady state. To this aim, we borrowed a tool from network control, namely pinning control, to show how agents with relatively few connections can exploit the structure of the social interconnections to diffuse their influence throughout the social group. Using heuristic approaches and leveraging theoretical and graphical knowledge of the network dynamical systems under investigation, we showed that a smart selection of the individuals to directly influence allows to maximize the effect of persuading actions of opinion leaders. Finally, we illustrated how the model we proposed can provide quantitative predictions on opinions' distribution in a given population, which in turn can be used to gauge the effectiveness of different awareness campaigns strategies aimed at mitigating vaccine hesitancy.
20-feb-2024
36
2022/2023
TECHNOLOGY, INNOVATION AND MANAGEMENT
DE LELLIS, Pietro
Ancona, Camilla
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/265073
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