Please use this identifier to cite or link to this item:
http://hdl.handle.net/10773/26039
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Gonçalves, João N. C. | pt_PT |
dc.contributor.author | Rodrigues, Helena Sofia | pt_PT |
dc.contributor.author | Monteiro, M. Teresa T. | pt_PT |
dc.date.accessioned | 2019-05-13T14:08:31Z | - |
dc.date.available | 2019-05-13T14:08:31Z | - |
dc.date.issued | 2018 | - |
dc.identifier.isbn | 978-3-319-71582-7 | pt_PT |
dc.identifier.uri | http://hdl.handle.net/10773/26039 | - |
dc.description.abstract | The process of diffusing viral marketing campaigns through social networks can be modeled under concepts of mathematical epidemiology. Based on a Susceptible-Infected-Recovered (SIR) epidemiological model, the benefits of optimal control theory on the diffusion of a real viral advertisement are studied. Two optimal control strategies that could help marketers to maximize the spread of information and minimize the costs associated to it in optimal time windows are analyzed and compared. The uniqueness of optimality system is proved. Numerical simulations show that high investment costs in publicity strategies do not imply high overall levels of information diffusion. This paper contributes to the current literature by studying a viral marketing campaign using real numerical data. | pt_PT |
dc.language.iso | eng | pt_PT |
dc.publisher | Springer Verlag | pt_PT |
dc.relation | info:eu-repo/grantAgreement/FCT/5876/147206/PT | pt_PT |
dc.relation | info:eu-repo/grantAgreement/FCT/5876/147280/PT | pt_PT |
dc.rights | restrictedAccess | pt_PT |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | pt_PT |
dc.subject | Optimal control theory | pt_PT |
dc.subject | Viral marketing | pt_PT |
dc.subject | SIR epidemiological model | pt_PT |
dc.subject | Information diffusion strategies | pt_PT |
dc.title | Optimal control strategies for an advertisement viral diffusion | pt_PT |
dc.type | bookPart | pt_PT |
dc.description.version | published | pt_PT |
dc.peerreviewed | yes | pt_PT |
degois.publication.firstPage | 135 | pt_PT |
degois.publication.lastPage | 149 | pt_PT |
degois.publication.title | Operational Research. APDIO 2017. Springer Proceedings in Mathematics & Statistics | pt_PT |
dc.relation.publisherversion | https://link.springer.com/chapter/10.1007/978-3-319-71583-4_10#citeas | pt_PT |
dc.identifier.doi | 10.1007/978-3-319-71583-4_10 | pt_PT |
dc.identifier.esbn | 978-3-319-71583-4 | pt_PT |
Appears in Collections: | CIDMA - Capítulo de livro SCG - Capítulo de livro |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
2018_Chapter10_joao_tm_indexed_scopus.pdf | 3.59 MB | Adobe PDF |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.