Influence maximization over a network : static and dynamic policies
Name
973722726-MIT.pdf
Description
Full printable version
Size
10.27 MB
Format
Adobe PDF
Checksum (MD5)
9ecf1e7a479cfcd88b2ea806000340c4
Author(s)
Ben Chaouch, Zied
Advisor(s)
John N. Tsitsiklis.
Date Issued
2016
Publisher
Massachusetts Institute of Technology
Abstract
The problem of maximizing the spread of an opinion inside a social network has been investigated extensively during the past decade. The importance of this problem in applications such as marketing has been amplified by the major expansion of online social networks. In this thesis, we study opinion control policies, first under a broad class of deterministic dynamics governing the interactions inside a network, and then under the classical "Voter Model". In the former case, we design a policy that a controller can follow in order to spread an opinion inside a network with the smallest possible cost. In the latter case, we consider networks whose underlying graph is the d-dimensional integer torus Zd/n, and we design policies that minimize the expected time until the network reaches a consensus. We also show that, in dimension d >/= 2, dynamic policies do not perform significantly better than static policies, while, in dimension d = 1, optimal dynamic policies perform much better than optimal static policies..
Description
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 131-132).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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