Abstract
Argumentation mining aims at automatically extracting structured arguments from unstructured textual documents. It has recently become a hot topic also due to its potential in processing information originating from the Web, and in particular from social media, in innovative ways. Recent advances in machine learning methods promise to enable breakthrough applications to social and economic sciences, policy making, and information technology: something that only a few years ago was unthinkable. In this survey article, we introduce argumentation models and methods, review existing systems and applications, and discuss challenges and perspectives of this exciting new research area.
Marco Lippi
Associate Professor
He is an expert in machine learning and deep learning, with applications in many domains including natural language processing.
Paolo Torroni
Associate Professor
Head of the Language Technologies lab. His main research focus is in artificial intelligence, and in particular natural language processing, multi-agent systems, and computational logics.