Information processing in homophilic and heterophilic social networks: simple vs. complex contagion

Complex networks are the skeleton upon which many social interactions occur. It is well known that the structure of the network strongly influences the dynamics on it. In this Master’s thesis, one particular class of dynamical processes will be studied; namely, conta- gion processes. These processes share many similarities with disease spreading through networks, so many mathematical tools developed for the latter can be applied to the former. This Master thesis will focus on the effects that homophily (the tendency of nodes to connect with other nodes similar to them) and heterophily (the tendency of nodes to connect with others different from them) has on contagion processes. To study this, so-called Barabasi- Albert-homophily networks (BAh networks) will be simulated and compared to random and scale-free networks. As opposed to Erdos-Renyi and Barabasi-Albert networks, in BAh networks, two classes of nodes are present and an homophily parameter h determines the probability of homophilic and heterophilic interactions. An important point of this work will be to determine if and how the novel structural properties of BAh networks affect the contagion process and its transition points.….

Master Thesis Defense

Advisors: Maxi San Miguel and Sandro Meloni

Jury: Raúl Toral, Jose Ramasco, Sandro Meloni


Detalles de contacto:

Sandro Meloni

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