Argumentative Discourse Units

Computational Models of Argument

This book presents the proceedings of COMMA 2024, the 10th biennial International Conference on Computational Models of Argument, held from 18 to 20 September 2024 in Hagen, Germany. The COMMA conference series provides a dedicated forum for the presentation and discussion of the latest advancements in this interdisciplinary field, covering basic research, systems and innovative applications and nurturing the steady growth of interest in computational-argumentation research worldwide. A total of 63 submissions was received for the conference, and after a thorough review process 26 were accepted as full papers, with a further 12 accepted as demos accompanied by an extended abstract, and 2 as full papers with accompanying demo, resulting in an acceptance rate of 53% for full papers and 63% for papers and demo abstracts combined. In addition to these 40 papers, extended abstracts of the 3 invited talks are also included here: Semantics in Argumentation: Classifications and Challenges, by Leila Amgoud; Expanding the Scope of Bayesian Argumentation, by Ulrike Hahn; and The Long Road to Trustworthy Natural Language Argumentation, by Serena Villata. The book provides a fascinating overview of current research and innovations, and will be of interest to all those working in the field.

Argument Mining

This book is an introduction to the linguistic concepts of argumentation relevant for argument mining, an important research and development activity which can be viewed as a highly complex form of information retrieval, requiring high-level natural language processing technology. While the first four chapters develop the linguistic and conceptual aspects of argument expression, the last four are devoted to their application to argument mining. These chapters investigate the facets of argument annotation, as well as argument mining system architectures and evaluation. How annotations may be used to develop linguistic data and how to train learning algorithms is outlined. A simple implementation is then proposed. The book ends with an analysis of non-verbal argumentative discourse. Argument Mining is an introductory book for engineers or students of linguistics, artificial intelligence and natural language processing. Most, if not all, the concepts of argumentation crucial for argument mining are carefully introduced and illustrated in a simple manner.

Pseudo-argument