Computational Human Dynamics

TL;DR

This thesis presents comprehensive research on human dynamics, temporal networks, and social phenomena, integrating insights from multiple disciplines to advance understanding of time-varying social interactions and collective behaviors.

Contribution

It offers a synthesis of novel methods and findings across human activity patterns, temporal network modeling, and social contagion, providing an up-to-date perspective in computational social science.

Findings

Analysis of heterogeneous temporal patterns in human actions

Development of models for time-varying social networks

Insights into socioeconomic inequalities and social contagion dynamics

Abstract

This thesis summarises my scientific contributions in the domain of network science, human dynamics and computational social science. These contributions are associated to computer science, physics, statistics, and applied mathematics. The goal of this thesis is twofold, on one hand to write a concise summary of my most interesting scientific contributions, and on the other hand to provide an up-to-date view and perspective about my field. I start my dissertation with an introduction to position the reader on the landscape of my field and to put in perspective my contributions. In the second chapter I concentrate on my works on bursty human dynamics, addressing heterogeneous temporal characters of human actions and interactions. Next, I discuss my contributions to the field of temporal networks and give a synthesises of my works on various methods of the representation, characterisation, and modelling of time-varying structures. Finally, I discuss my works on the data-driven observations and modelling of collective social phenomena. There, I summarise studies on the static observations of emergent patterns of socioeconomic inequalities and their correlations with social-communication networks, and with linguistic patterns. I also discuss dynamic observations and modelling of social contagion processes.