Standard Susceptible-Infected-Susceptible (SIS) epidemic models assume that a message spreads from the infected to the susceptible nodes due to only susceptible-infected epidemic contact. We modify the standard SIS epidemic model to include direct recruitment of susceptible individuals to the infected class at a constant rate (independent of epidemic contacts), to accelerate information spreading in a social network. Such recruitment can be carried out by placing advertisements in the media. We provide a closed form analytical solution for system evolution in the proposed model and use it to study campaigning in two different scenarios. In the first, the net cost function is a linear combination of the reward due to extent of information di...
Abstract Modeling influence diffusion in social networks is an important challenge. We investigate i...
This thesis explores the problem of tracking the diffusion of contagion processes on social networks...
The participation of individuals in multi-layer networks allows for feedback between network layers,...
Standard Susceptible-Infected-Susceptible (SIS) epidemic models assume that a message spreads from t...
We study the optimal control problem of maximizing the spread of an information epidemic on a social...
The process of diffusing viral marketing campaigns through social networks can be modeled under conc...
Information spreading in a population can be modeled as an epidemic. Campaigners (e.g., election cam...
2018-08-05The study of information diffusion on social networks has gained significant importance wi...
We model information dissemination as a susceptible-infected epidemic process and formulate a proble...
In epidemic modeling, the Susceptible-Alert-Infected-Susceptible (SAIS) model extends the ...
We survey the recent literature on theoretical models of diffusion in social networks and the applic...
There is currently growing interest in modeling the information diffusion on social networks across ...
So far, in some standard rumor spreading models, the transition probability from ignorants to spread...
ISBN 978-1-4503-0880-9International audienceSocial networks now play a central role for sharing info...
The spread of diseases and opinions has profoundly affected the development of human societies. The ...
Abstract Modeling influence diffusion in social networks is an important challenge. We investigate i...
This thesis explores the problem of tracking the diffusion of contagion processes on social networks...
The participation of individuals in multi-layer networks allows for feedback between network layers,...
Standard Susceptible-Infected-Susceptible (SIS) epidemic models assume that a message spreads from t...
We study the optimal control problem of maximizing the spread of an information epidemic on a social...
The process of diffusing viral marketing campaigns through social networks can be modeled under conc...
Information spreading in a population can be modeled as an epidemic. Campaigners (e.g., election cam...
2018-08-05The study of information diffusion on social networks has gained significant importance wi...
We model information dissemination as a susceptible-infected epidemic process and formulate a proble...
In epidemic modeling, the Susceptible-Alert-Infected-Susceptible (SAIS) model extends the ...
We survey the recent literature on theoretical models of diffusion in social networks and the applic...
There is currently growing interest in modeling the information diffusion on social networks across ...
So far, in some standard rumor spreading models, the transition probability from ignorants to spread...
ISBN 978-1-4503-0880-9International audienceSocial networks now play a central role for sharing info...
The spread of diseases and opinions has profoundly affected the development of human societies. The ...
Abstract Modeling influence diffusion in social networks is an important challenge. We investigate i...
This thesis explores the problem of tracking the diffusion of contagion processes on social networks...
The participation of individuals in multi-layer networks allows for feedback between network layers,...