Towards an Automatic Generation of Persuasive Messages

E. Lipa-Urbina, N. Condori-Fernandez, F. Suni-Lopez

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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.
Original languageEnglish
Title of host publicationPersuasive Technology
Subtitle of host publication16th International Conference, PERSUASIVE 2021, Virtual Event, April 12–14, 2021, Proceedings
EditorsRaian Ali, Birgit Lugrin, Fred Charles
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages8
ISBN (Electronic)9783030794606
ISBN (Print)9783030794590
Publication statusPublished - 2021
Event16th International Conference on Persuasive Technology, PERSUASIVE 2021 - Virtual, Online
Duration: 12 Apr 202114 Apr 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12684 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference16th International Conference on Persuasive Technology, PERSUASIVE 2021
CityVirtual, Online


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