On Distributed Maximization of Influence in Social Networks
(2017)Department of Automatic Control
- Abstract
- This thesis studies the problem of finding the optimal placement of a directed link in a graph representation of a social network in order to maximize the induced gain of the opinion equilibrium. The model assumes the presence of a set of stubborn nodes and applies a standard DeGroot opinion dynamics model. First we show that an added directed link should point to a stubborn node in order to maximize the impact of the link. The resulting problem reduction then allows for explicit solutions of where the directed link should origin in a few common network topographies such as the line graph and the barbell graph. A formula for the optimal tail placement for general graphs is then presented along with a distributed algorithm. Implementation... (More)
- This thesis studies the problem of finding the optimal placement of a directed link in a graph representation of a social network in order to maximize the induced gain of the opinion equilibrium. The model assumes the presence of a set of stubborn nodes and applies a standard DeGroot opinion dynamics model. First we show that an added directed link should point to a stubborn node in order to maximize the impact of the link. The resulting problem reduction then allows for explicit solutions of where the directed link should origin in a few common network topographies such as the line graph and the barbell graph. A formula for the optimal tail placement for general graphs is then presented along with a distributed algorithm. Implementation and simulation are then performed again first on a few common network types and then on a small sub-network of Facebook. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8927868
- author
- Guth, Joakim
- supervisor
-
- Gustav Nilsson LU
- Giacomo Como LU
- Anders Rantzer LU
- organization
- year
- 2017
- type
- H3 - Professional qualifications (4 Years - )
- subject
- report number
- TFRT-6045
- ISSN
- 0280-5316
- language
- English
- id
- 8927868
- date added to LUP
- 2017-11-17 10:25:45
- date last changed
- 2017-11-17 10:25:45
@misc{8927868,
abstract = {{This thesis studies the problem of finding the optimal placement of a directed link in a graph representation of a social network in order to maximize the induced gain of the opinion equilibrium. The model assumes the presence of a set of stubborn nodes and applies a standard DeGroot opinion dynamics model. First we show that an added directed link should point to a stubborn node in order to maximize the impact of the link. The resulting problem reduction then allows for explicit solutions of where the directed link should origin in a few common network topographies such as the line graph and the barbell graph. A formula for the optimal tail placement for general graphs is then presented along with a distributed algorithm. Implementation and simulation are then performed again first on a few common network types and then on a small sub-network of Facebook.}},
author = {{Guth, Joakim}},
issn = {{0280-5316}},
language = {{eng}},
note = {{Student Paper}},
title = {{On Distributed Maximization of Influence in Social Networks}},
year = {{2017}},
}