Network structure inference, a survey: Motivations, methods, and applications
Networks represent relationships between entities in many complex systems, spanning from
online social interactions to biological cell development and brain connectivity. In many …
online social interactions to biological cell development and brain connectivity. In many …
Influence maximization on social graphs: A survey
Influence Maximization (IM), which selects a set of k users (called seed set) from a social
network to maximize the expected number of influenced users (called influence spread), is a …
network to maximize the expected number of influenced users (called influence spread), is a …
Game-theoretic frameworks for epidemic spreading and human decision-making: A review
This review presents and reviews various solved and open problems in develo**,
analyzing, and mitigating epidemic spreading processes under human decision-making. We …
analyzing, and mitigating epidemic spreading processes under human decision-making. We …
Structure and dynamics of information pathways in online media
Diffusion of information, spread of rumors and infectious diseases are all instances of
stochastic processes that occur over the edges of an underlying network. Many times …
stochastic processes that occur over the edges of an underlying network. Many times …
Scalable influence estimation in continuous-time diffusion networks
If a piece of information is released from a media site, can it spread, in 1 month, to a million
web pages? This influence estimation problem is very challenging since both the time …
web pages? This influence estimation problem is very challenging since both the time …
Robust influence maximization
In this paper, we address the important issue of uncertainty in the edge influence probability
estimates for the well studied influence maximization problem---the task of finding k seed …
estimates for the well studied influence maximization problem---the task of finding k seed …
Network reconstruction and community detection from dynamics
We present a scalable nonparametric Bayesian method to perform network reconstruction
from observed functional behavior that at the same time infers the communities present in …
from observed functional behavior that at the same time infers the communities present in …
Influence estimation and maximization in continuous-time diffusion networks
If a piece of information is released from a set of media sites, can it spread, in 1 month, to a
million web pages? Can we efficiently find a small set of media sites among millions that can …
million web pages? Can we efficiently find a small set of media sites among millions that can …
Using humans as sensors: an estimation-theoretic perspective
The explosive growth in social network content suggests that the largest “sensor network”
yet might be human. Extending the participatory sensing model, this paper explores the …
yet might be human. Extending the participatory sensing model, this paper explores the …
Representation learning for information diffusion through social networks: an embedded cascade model
In this paper, we focus on information diffusion through social networks. Based on the well-
known Independent Cascade model, we embed users of the social network in a latent space …
known Independent Cascade model, we embed users of the social network in a latent space …