The rise of bots and their influence on social networks is a hot topic that has aroused the
interest of many researchers. Despite the efforts to detect social bots, it is still difficult to …

Only a subset of infections is actually observed in an outbreak, due to multiple reasons such
as asymptomatic cases and under-reporting. Therefore, reconstructing an epidemic cascade …

Temporal graphs represent interactions between entities over the time. These interactions
may be direct (a contact between two nodes at some time instant), or indirect, through …

This paper studies the problem of detecting asymptomatic cases in a temporal contact
network in which multiple outbreaks have occurred. For many infections, asymptomatic …

Undetected infections fuel the dissemination of many infectious agents. However,
identification of unobserved infectious individuals remains challenging due to limited …

This paper studies the problem of detecting asymptomatic cases in a temporal contact
network in which multiple outbreaks have occurred. We show that the key to detecting …

Influencing others through social networks is fundamental to all human societies. Whether
this happens through the diffusion of rumors, opinions, or viruses, identifying the diffusion …

Low-dimensional vector representations of network nodes have proven successful to feed
graph data to machine learning algorithms and to improve performance across diverse …

This paper studies the problem of detecting asymptomatic cases in epidemic outbreaks
within healthcare facilities. Asymptomatic cases pose a significant obstacle in our fight …

Finding hidden infected nodes is extremely important when information or diseases spread
rapidly in a network because hints regarding the global properties of the diffusion dynamics …