Computational Argumentation and Argument Mining

Computational argumentation is an interdisciplinary research field that emerged in the early 1990s as a paradigm for knowledge representation and reasoning. It currently has applications in various AI fields, such as decision-making, multi-agent systems, and natural language processing, as well as specific application domains like the automatic analysis of debates and opinion articles, detection and analysis of misinformation, automated negotiations, healthcare, and legal reasoning. Argumentation also plays an important role in designing and developing interactive technologies capable of maintaining or changing human thought and behavior using persuasive techniques.
Given its close relationship with natural language processing and the rise of AI-based generative language models, the area faces multiple challenges. Computational argumentation offers a way to critically examine both the training data and the outputs of these models, helping to identify, explain, and correct gender biases, which is crucial for developing fair and responsible AI technologies.
At VRAIN of UPV, work is being done on the development of argumentation technologies from different perspectives, such as their application in recommendation systems and decision-making aids in educational and healthcare contexts; their application in virtual societies of humans and agents, where agents act as virtual assistants for humans; their use in social networks; their ability to persuade users and provoke changes in their thinking and behavior through argumentation techniques; and their ability to analyze text and detect underlying patterns and lines of reasoning that identify misinformation and biases.