Towards an Automatic Generation of Persuasive Messages

Edson Lipa-Urbina, Nelly Condori-Fernandez, Franci Suni-Lopez

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva


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.

Idioma originalInglés
Título de la publicación alojadaPersuasive Technology - 16th International Conference, PERSUASIVE 2021, Proceedings
EditoresRaian Ali, Birgit Lugrin, Fred Charles
EditorialSpringer Science and Business Media Deutschland GmbH
Número de páginas8
ISBN (versión impresa)9783030794590
EstadoPublicada - 2021
Evento16th International Conference on Persuasive Technology, PERSUASIVE 2021 - Virtual, Online
Duración: 12 abr. 202114 abr. 2021

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen12684 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349


Conferencia16th International Conference on Persuasive Technology, PERSUASIVE 2021
CiudadVirtual, Online

Nota bibliográfica

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.


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