Argument Mining

Beschreibung

This Open Access book provides an essential overview of the topic of argumentation mining, an active research area of Natural Language Processing (NLP). Argument mining can automatically find and collect arguments published in newspapers, social media, or elsewhere. Argument mining can be also used to give a precise account of the argumentative structure of a single text or dialogue such as a legal or scientific document, a student essay, or an online conversation. Increasingly, computational approaches provide synopses of arguments and compare the relative strength of arguments. In this book, the authors start with basic argumentation concepts and describe the NLP methods for mining arguments automatically from natural language text. The authors then show how NLP is used for assessing the quality of arguments and generating new arguments. This Second Edition presents an updated survey of the state of the art of argument mining, providing increased depth and insights into many more NLP tasks than the prior edition. This new edition discusses the disruptive changes that have come with large language models and highlights potential future developments. The authors also update the treatment of the common steps in argument mining, argument generation tasks and methods, and computational argumentation applications. Completely new chapters cover perspective assessment, argument quality assessment, and argument reasoning. 

In addition, this book:

• Summarizes the topic for readers of varying familiarity with it, from both linguistic and technical perspectives
• Teaches readers about the various technical methods, how they are utilized, and how they compare to each other
• Presents an up-to-date survey that incorporates the recent significant changes in NLP and argument mining

This Open Access book provides an essential overview of the topic of argumentation mining, an active research area of Natural Language Processing (NLP). Argument mining can automatically find and collect arguments published in newspapers, social media, or elsewhere. Argument mining can be also used to give a precise account of the argumentative structure of a single text or dialogue such as a legal or scientific document, a student essay, or an online conversation. Increasingly, computational approaches provide synopses of arguments and compare the relative strength of arguments. In this book, the authors start with basic argumentation concepts and describe the NLP methods for mining arguments automatically from natural language text. The authors then show how NLP is used for assessing the quality of arguments and generating new arguments. This Second Edition presents an updated survey of the state of the art of argument mining, providing increased depth and insights into many more NLP tasks than the prior edition. This new edition discusses the disruptive changes that have come with large language models and highlights potential future developments. The authors also update the treatment of the common steps in argument mining, argument generation tasks and methods, and computational argumentation applications. Completely new chapters cover perspective assessment, argument quality assessment, and argument reasoning. 

Autor*in

Manfred Stede

Themen in »Argument Mining«

Open Access Argumentation Mining Argumentation Text Mining Argument Structure Argument Analysis Computational Argumentation

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