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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..

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Autor(es)

Ben Chaouch, Zied - 

Id.: 69702363

Idioma: eng  - 

Versión: 1.0

Estado: Final

Tipo:  132 pages - 

Palabras claveElectrical Engineering and Computer Science. - 

Tipo de recurso: Thesis  - 

Tipo de Interactividad: Expositivo

Nivel de Interactividad: muy bajo

Audiencia: Estudiante  -  Profesor  -  Autor  - 

Estructura: Atomic

Coste: no

Copyright: sí

: MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Formatos:  132 pages - 

Requerimientos técnicos:  Browser: Any - 

Fecha de contribución: 12-mar-2017

Contacto:

Localización:
* 973722726

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Otros recursos de la mismacolección

  1. Emotion recognition using wireless signals This thesis demonstrates a new technology that can infer a person's emotions from RF signals reflect...
  2. Private sequential search and optimization We propose and analyze two models to study an intrinsic trade-off between privacy and query complexi...
  3. On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment with rebalancing On-demand ride-sharing systems with autonomous vehicles have the potential to enhance the efficiency...
  4. Faster algorithms for matrix scaling and balancing via convex optimization In this thesis, we study matrix scaling and balancing, which are fundamental problems in scientific ...
  5. Machine-learning models for predicting drug approvals and clinical-phase transitions We apply machine-learning techniques to predict drug approvals and phase transitions using drug-deve...

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