Influential Node Detection on Graph on Event Sequence

Numerous research efforts have centered on identifying the most influential players in networked social systems. This problem is immensely crucial in the research of complex networks. Most existing techniques either model social dynamics on static networks only and ignore the underlying time-serial nature or model the social interactions as...

The role of epidemic spreading in seizure dynamics and epilepsy surgery

Epilepsy surgery is the treatment of choice for drug-resistant epilepsy patients, but only leads to seizure freedom for roughly two in three patients. To address this problem, we designed a patient-specific epilepsy surgery model combining large-scale magnetoencephalography (MEG) brain networks with an epidemic spreading model. This simple...

Performance of complex networks: Efficiency and Robustness

Network performance is determined by the interplay of underlying structures and overlying dynamic processes on networks. This thesis mainly considers two types of collective dynamics on networks, spread and transport, which are ubiquitous in our daily lives, ranging from information propagation, disease spreading, to molecular motors on...

Modeling Airport Congestion Contagion by SIS Epidemic Spreading on Airline Networks

We model airport congestion contagion as an SIS spreading process on an airport transportation network to explain airport vulnerability. The vulnerability of each airport is derived from the US Airport Network data as its congestion probability. We construct three types of airline networks to capture diverse features such as the frequency and...

Information Propagation in Complex Networks: Structures and Dynamics

This thesis is a contribution to a deeper understanding of how information propagates and what this process entails. At its very core is the concept of the network: a collection of nodes and links, which describes the structure of the systems under investigation. The network is a mathematical model which allows to focus on a very fundamental...

Coupling dynamics of epidemic spreading and information diffusion on complex networks

The interaction between disease and disease information on complex networks has facilitated an interdisciplinary research area. When a disease begins to spread in the population, the corresponding information would also be transmitted among individuals, which in turn influence the spreading pattern of the disease. In this paper, firstly, we...

Epidemic dynamics on information-driven adaptive networks

Research on the interplay between the dynamics on the network and the dynamics of the network has attracted much attention in recent years. In this work, we propose an information-driven adaptive model, where disease and disease information can evolve simultaneously. For the information-driven adaptive process, susceptible (infected)...

The Relation Between Structure and Function in Brain Networks: A network science perspective

Over the last two decades the field of network science has been evolving fast. Many useful applications in a wide variety of disciplines have been found. The application of network science to the brain initiated the interdisciplinary field of complex brain networks. On a macroscopic level, brain regions are taken as nodes in a network. The...

Epidemic mitigation via awareness propagation in communication networks: The role of time scales

The participation of individuals in multi-layer networks allows for feedback between network layers, opening new possibilities to mitigate epidemic spreading. For instance, the spread of a biological disease such as Ebola in a physical contact network may trigger the propagation of the information related to this disease in a communication...

Applying the epidemic spreading model on the brain network to explain effective connectivity

Network science studies a complex system as a network to capture the connectivity patterns and topological features. Different network topologies have been observed to shape dynamic spread- ing processes on the network in various ways, while the exact relationship is complicated and not yet fully understood. Epidemic models are often applied to...

Epidemics in Networks: Modeling, Optimization and Security Games

Epidemic theory has wide range of applications in computer networks, from spreading of malware to the information dissemination algorithms. Our society depends more strongly than ever on such computer networks. Many of these networks rely to a large extent on decentralization and self-organization. While decentralization removes obvious...