Title
Towards an Automatic Generation of Persuasive Messages
Date Issued
01 January 2021
Access level
open access
Resource Type
conference paper
Publisher(s)
Springer Science and Business Media Deutschland GmbH
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.
Start page
55
End page
62
Volume
12684 LNCS
Language
English
OCDE Knowledge area
Bioinformática
Ciencias de la computación
Subjects
Scopus EID
2-s2.0-85111997254
Source
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Resource of which it is part
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN of the container
03029743
ISBN of the container
9783030794590
Conference
16th International Conference on Persuasive Technology, PERSUASIVE 2021
Sponsor(s)
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.
Sources of information:
Directorio de Producción Científica
Scopus