Towards an Automatic Generation of Persuasive Messages

Descripción del Articulo

Acknowledgments. This work has been supported by CONCYTEC - FONDECYT within the framework of the call E038-01 contract 014-2019. N. Condori Fernandez wish also to thank Datos 4.0 (TIN2016-78011-C4-1-R) funded by MINECO-AEI/FEDER-UE.
Detalles Bibliográficos
Autores: Lipa-Urbina E., Condori-Fernandez N., Suni-Lopez F.
Formato: objeto de conferencia
Fecha de Publicación:2021
Institución:Consejo Nacional de Ciencia Tecnología e Innovación
Repositorio:CONCYTEC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.concytec.gob.pe:20.500.12390/3071
Enlace del recurso:https://hdl.handle.net/20.500.12390/3071
https://doi.org/10.1007/978-3-030-79460-6_5
Nivel de acceso:acceso abierto
Materia:Text generation
Persuasive message
SentiGAN
https://purl.org/pe-repo/ocde/ford#2.02.02
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spelling Publicationrp08862600rp02079600rp06523600Lipa-Urbina E.Condori-Fernandez N.Suni-Lopez F.2024-05-30T23:13:38Z2024-05-30T23:13:38Z2021https://hdl.handle.net/20.500.12390/3071https://doi.org/10.1007/978-3-030-79460-6_52-s2.0-85111997254Acknowledgments. This work has been supported by CONCYTEC - FONDECYT within the framework of the call E038-01 contract 014-2019. N. Condori Fernandez wish also to thank Datos 4.0 (TIN2016-78011-C4-1-R) funded by MINECO-AEI/FEDER-UE.In the last decades, the Natural Language Generation (NLG) methods have been improved to generate text automatically. However, based on the literature review, there are not works on generating text for persuading people. In this paper, we propose to use the SentiGAN framework to generate messages that are classified into levels of persuasiveness. And, we run an experiment using the Microtext dataset for the training phase. Our preliminary results show 0.78 of novelty on average, and 0.57 of diversity in the generated messages. © 2021, Springer Nature Switzerland AG.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - ConcytecengSpringer Science and Business Media Deutschland GmbHLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)info:eu-repo/semantics/openAccessText generationPersuasive message-1SentiGAN-1https://purl.org/pe-repo/ocde/ford#2.02.02-1Towards an Automatic Generation of Persuasive Messagesinfo:eu-repo/semantics/conferenceObjectreponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC20.500.12390/3071oai:repositorio.concytec.gob.pe:20.500.12390/30712024-05-30 16:13:44.316http://purl.org/coar/access_right/c_14cbinfo:eu-repo/semantics/closedAccessmetadata only accesshttps://repositorio.concytec.gob.peRepositorio Institucional CONCYTECrepositorio@concytec.gob.pe#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="0fa22533-30fa-4812-bd4a-838c1149779c"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Towards an Automatic Generation of Persuasive Messages</Title> <PublishedIn> <Publication> <Title>Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)</Title> </Publication> </PublishedIn> <PublicationDate>2021</PublicationDate> <DOI>https://doi.org/10.1007/978-3-030-79460-6_5</DOI> <SCP-Number>2-s2.0-85111997254</SCP-Number> <Authors> <Author> <DisplayName>Lipa-Urbina E.</DisplayName> <Person id="rp08862" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Condori-Fernandez N.</DisplayName> <Person id="rp02079" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Suni-Lopez F.</DisplayName> <Person id="rp06523" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Springer Science and Business Media Deutschland GmbH</DisplayName> <OrgUnit /> </Publisher> </Publishers> <Keyword>Text generation</Keyword> <Keyword>Persuasive message</Keyword> <Keyword>SentiGAN</Keyword> <Abstract>In the last decades, the Natural Language Generation (NLG) methods have been improved to generate text automatically. However, based on the literature review, there are not works on generating text for persuading people. In this paper, we propose to use the SentiGAN framework to generate messages that are classified into levels of persuasiveness. And, we run an experiment using the Microtext dataset for the training phase. Our preliminary results show 0.78 of novelty on average, and 0.57 of diversity in the generated messages. © 2021, Springer Nature Switzerland AG.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication> -1
dc.title.none.fl_str_mv Towards an Automatic Generation of Persuasive Messages
title Towards an Automatic Generation of Persuasive Messages
spellingShingle Towards an Automatic Generation of Persuasive Messages
Lipa-Urbina E.
Text generation
Persuasive message
SentiGAN
https://purl.org/pe-repo/ocde/ford#2.02.02
title_short Towards an Automatic Generation of Persuasive Messages
title_full Towards an Automatic Generation of Persuasive Messages
title_fullStr Towards an Automatic Generation of Persuasive Messages
title_full_unstemmed Towards an Automatic Generation of Persuasive Messages
title_sort Towards an Automatic Generation of Persuasive Messages
author Lipa-Urbina E.
author_facet Lipa-Urbina E.
Condori-Fernandez N.
Suni-Lopez F.
author_role author
author2 Condori-Fernandez N.
Suni-Lopez F.
author2_role author
author
dc.contributor.author.fl_str_mv Lipa-Urbina E.
Condori-Fernandez N.
Suni-Lopez F.
dc.subject.none.fl_str_mv Text generation
topic Text generation
Persuasive message
SentiGAN
https://purl.org/pe-repo/ocde/ford#2.02.02
dc.subject.es_PE.fl_str_mv Persuasive message
SentiGAN
dc.subject.ocde.none.fl_str_mv https://purl.org/pe-repo/ocde/ford#2.02.02
description Acknowledgments. This work has been supported by CONCYTEC - FONDECYT within the framework of the call E038-01 contract 014-2019. N. Condori Fernandez wish also to thank Datos 4.0 (TIN2016-78011-C4-1-R) funded by MINECO-AEI/FEDER-UE.
publishDate 2021
dc.date.accessioned.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.available.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.issued.fl_str_mv 2021
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12390/3071
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1007/978-3-030-79460-6_5
dc.identifier.scopus.none.fl_str_mv 2-s2.0-85111997254
url https://hdl.handle.net/20.500.12390/3071
https://doi.org/10.1007/978-3-030-79460-6_5
identifier_str_mv 2-s2.0-85111997254
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer Science and Business Media Deutschland GmbH
publisher.none.fl_str_mv Springer Science and Business Media Deutschland GmbH
dc.source.none.fl_str_mv reponame:CONCYTEC-Institucional
instname:Consejo Nacional de Ciencia Tecnología e Innovación
instacron:CONCYTEC
instname_str Consejo Nacional de Ciencia Tecnología e Innovación
instacron_str CONCYTEC
institution CONCYTEC
reponame_str CONCYTEC-Institucional
collection CONCYTEC-Institucional
repository.name.fl_str_mv Repositorio Institucional CONCYTEC
repository.mail.fl_str_mv repositorio@concytec.gob.pe
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Towards an Automatic Generation of Persuasive Messages
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