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Computational argumentation for the automatic analysis of argumentative discourse and human persuasion

  • Autores: Ramon Ruiz Dolz
  • Directores de la Tesis: Stella María Heras Barberá (dir. tes.) Árbol académico, Ana García Fornés (dir. tes.) Árbol académico
  • Lectura: En la Universitat Politècnica de València ( España ) en 2023
  • Idioma: español
  • Enlaces
    • Tesis en acceso abierto en: RiuNet
  • Resumen
    • Computational argumentation is the area of research that studies and analyses the use of different techniques and algorithms that approximate human argumentative reasoning from a computational viewpoint. In this doctoral thesis we study the use of different techniques proposed under the framework of computational argumentation to perform an automatic analysis of argumentative discourse, and to develop argument-based computational persuasion techniques. With these objectives in mind, we first present a complete review of the state of the art and propose a classification of existing works in the area of computational argumentation. This review allows us to contextualise and understand the previous research more clearly from the human perspective of argumentative reasoning, and to identify the main limitations and future trends of the research done in computational argumentation. Secondly, to overcome some of these limitations, we create and describe a new corpus that allows us to address new challenges and investigate on previously unexplored problems (e.g., automatic evaluation of spoken debates). In conjunction with this data, a new system for argument mining is proposed and a comparative analysis of different techniques for this same task is carried out. In addition, we propose a new algorithm for the automatic evaluation of argumentative debates and we evaluate it with real human debates. Thirdly, a series of studies and proposals are presented to improve the persuasiveness of computational argumentation systems in the interaction with human users. In this way, this thesis presents advances in each of the main parts of the computational argumentation process (i.e., argument mining, argument-based knowledge representation and reasoning, and argument-based human-computer interaction), and proposes some of the essential foundations for the complete automatic analysis of natural language argumentative discourses.


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