The world of network science is fascinating and filled with complex phenomena that we
aspire to understand. One of them is the dynamics of spreading processes over complex …

Influence maximization is a well-studied problem that asks for a small set of influential users
from a social network, such that by targeting them as early adopters, the expected total …

Controlling the dissemination of an entity (eg, meme, virus, etc) on a large graph is an
interesting problem in many disciplines. Examples include epidemiology, computer security …

As social network services connect people across the world, influence maximization, ie,
finding the most influential nodes (or individuals) in the network, is being actively researched …

Viral marketing has attracted considerable concerns in recent years due to its novel idea of
leveraging the social network to propagate the awareness of products. Specifically, viral …

In this paper, we study the problem of allocating ads to users through the viral-marketing
lens. Advertisers approach the host with a budget in return for the marketing campaign …

Large graphs are prevalent in many applications and enable a variety of information
dissemination processes, eg, meme, virus, and influence propagation. How can we optimize …

Viral marketing has attracted considerable concerns in recent years due to its novel idea of
leveraging the social network to propagate the awareness of products. Specifically, viral …

A typical viral marketing model identifies influential users in a social network to maximize a
single product adoption assuming unlimited user attention, campaign budgets, and time. In …

Social media has created new ways for citizens to stay informed on societal matters and
participate in political discourse. However, with its algorithmically-curated and virally …