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Control of Preferences in Social Networks

Chasparis, Georgios LU and Shamma, Jeff S. (2012) In Operations Research
Abstract
We consider the problem of deriving optimal marketing policies for the spread of innovations in a social network. We seek to compute policies that account for i) endogenous network influences, ii) the presence of competitive firms, that also wish to influence the network, and iii) possible uncertainties in the network model. Contrary to prior work in optimal advertising, which also accounts for network influences, we assume a dynamical model of preferences

and we compute optimal policies for either a finite or infinite horizon. The optimal policies are related to and extend priorly introduced notions of centrality measures usually considered in sociology. We also compute robust optimal policies for the case of misspecified... (More)
We consider the problem of deriving optimal marketing policies for the spread of innovations in a social network. We seek to compute policies that account for i) endogenous network influences, ii) the presence of competitive firms, that also wish to influence the network, and iii) possible uncertainties in the network model. Contrary to prior work in optimal advertising, which also accounts for network influences, we assume a dynamical model of preferences

and we compute optimal policies for either a finite or infinite horizon. The optimal policies are related to and extend priorly introduced notions of centrality measures usually considered in sociology. We also compute robust optimal policies for the case of misspecified dynamics or uncertainties which can be modeled as external disturbances of the nominal dynamics. We show that the optimization exhibits a certainty equivalence property, i.e., the optimal values of the control variables are the same as if there were no uncertainty. Finally, we investigate the scenario where a competitive firm also tries to influence the network. In this case, robust optimal solutions are computed in the form of i) Nash and Stackelberg solutions, and ii) max-min solutions. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
submitted
subject
keywords
Dynamic programming/optimal control: Applications, Marketing: Advertising and media, Games/group decisions: Differential, Networks/graphs: Applications
in
Operations Research
publisher
Inst Operations Research Management Sciences
ISSN
0030-364X
language
English
LU publication?
yes
id
35388062-33c5-4ea5-b0f4-741a936f274c (old id 2857097)
date added to LUP
2012-07-09 09:14:11
date last changed
2016-07-05 07:13:28
@article{35388062-33c5-4ea5-b0f4-741a936f274c,
  abstract     = {We consider the problem of deriving optimal marketing policies for the spread of innovations in a social network. We seek to compute policies that account for i) endogenous network influences, ii) the presence of competitive firms, that also wish to influence the network, and iii) possible uncertainties in the network model. Contrary to prior work in optimal advertising, which also accounts for network influences, we assume a dynamical model of preferences<br/><br>
and we compute optimal policies for either a finite or infinite horizon. The optimal policies are related to and extend priorly introduced notions of centrality measures usually considered in sociology. We also compute robust optimal policies for the case of misspecified dynamics or uncertainties which can be modeled as external disturbances of the nominal dynamics. We show that the optimization exhibits a certainty equivalence property, i.e., the optimal values of the control variables are the same as if there were no uncertainty. Finally, we investigate the scenario where a competitive firm also tries to influence the network. In this case, robust optimal solutions are computed in the form of i) Nash and Stackelberg solutions, and ii) max-min solutions.},
  author       = {Chasparis, Georgios and Shamma, Jeff S.},
  issn         = {0030-364X},
  keyword      = {Dynamic programming/optimal control: Applications,Marketing: Advertising and media,Games/group decisions: Differential,Networks/graphs: Applications},
  language     = {eng},
  publisher    = {Inst Operations Research Management Sciences},
  series       = {Operations Research},
  title        = {Control of Preferences in Social Networks},
  year         = {2012},
}