Text

Argument Mining is a relatively new research area which involves the automatic detection in text of arguments, argument components, and relations between arguments.

We have developed a novel classification methodology that incorporates reasoning through argumentation with corpus-based computational linguistics and have worked on the automatic extraction of arguments and the relations between these arguments from text using deep learning approaches.

Papers

• Lucas Carstens, Francesca Toni: Using Argumentation to Improve Classification in Natural Language Problems. Transactions on Internet Technology 2017
• Oana Cocarascu, Francesca Toni: Identifying Attack and Support Argumentative Relations Using Deep Learning. EMNLP 2017