Towards an Automatic Generation of Persuasive Messages

Lipa-Urbina E.; Condori-Fernandez N.; Suni-Lopez F. · Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2021) · DOI: 10.1007/978-3-030-79460-6_5

Resumen

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.

Instituciones: Universidad Nacional de San Agustín de Arequipa