Towards an Automatic Generation of Persuasive Messages

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

    Producción científica: Capítulo del libro/informe/acta de congresoArticulo (Contribución a conferencia)revisión exhaustiva

    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.

    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
    Páginas55-62
    Número de páginas8
    Volumen12684
    ISBN (versión impresa)9783030794590
    DOI
    EstadoPublicada - 23 jun. 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

    Conferencia

    Conferencia16th International Conference on Persuasive Technology, PERSUASIVE 2021
    CiudadVirtual, Online
    Período12/04/2114/04/21

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