Argument Mining
Linguistic Foundations
1st Edition
Published on 15. October 2019
208 pages
978-1-119-67116-9 (ISBN)
Description
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.
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.
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11/2019
1st Edition
Wiley-ISTE
€164.50
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Persons
Mathilde Janier has co-authored over 15 publications, principally dealing with the annotation and modeling of argumentative dynamics in debate and dispute mediation. Her work mainly focuses on argumentation in dialogical contexts.
Patrick Saint-Dizier is Senior Researcher at CNRS ? IRIT Toulouse, France. His work is based on logic, language, argumentation, natural language processing and logic programming. He is the author and co-author of 11 books on these topics.
Patrick Saint-Dizier is Senior Researcher at CNRS ? IRIT Toulouse, France. His work is based on logic, language, argumentation, natural language processing and logic programming. He is the author and co-author of 11 books on these topics.
Content
- Cover
- Half-Title Page
- Title Page
- Copyright Page
- Contents
- Preface
- 1. Introduction and Challenges
- 1.1. What is argumentation?
- 1.2. Argumentation and argument mining
- 1.3. The origins of argumentation
- 1.4. The argumentative discourse
- 1.5. Contemporary trends
- 2. The Structure of Argumentation
- 2.1. The argument-conclusion pair
- 2.2. The elementary argumentative schema
- 2.2.1. Toulmin's argumentative model
- 2.2.2. Some elaborations and refinements of Toulmin's model
- 2.2.3. The geometry of arguments
- 2.3. Modeling agreement and disagreement
- 2.3.1. Agreeing versus disagreeing
- 2.3.2. The art of resolving divergences
- 2.4. The structure of an argumentation: argumentation graphs
- 2.5. The role of argument schemes in argumentation
- 2.5.1. Argument schemes: main concepts
- 2.5.2. A few simple illustrations
- 2.5.3. Argument schemes based on analogy
- 2.5.4. Argument schemes based on causality
- 2.6. Relations between Toulmin's model and argumentation schemes
- 2.6.1. Warrants as a popular opinion
- 2.6.2. Argument schemes based on rules, explanations or hypothesis
- 2.6.3. Argument schemes based on multiple supports or attacks
- 2.6.4. Causality and warrants
- 3. The Linguistics of Argumentation
- 3.1. The structure of claims
- 3.2. The linguistics of justifications
- 3.3. Evaluating the strength of claims, justifications and arguments
- 3.3.1. Strength factors within a proposition
- 3.3.2. Structuring expressions of strength by semantic category
- 3.3.3. A simple representation of strength when combining several factors
- 3.3.4. Pragmatic factors of strength expression
- 3.4. Rhetoric and argumentation
- 3.4.1. Rhetoric and communication
- 3.4.2. Logos: the art of reasoning and of constructing demonstrations
- 3.4.3. Ethos: the orator profile
- 3.4.4. Pathos: how to persuade an audience
- 4. Advanced Features of Argumentation for Argument Mining
- 4.1. Managing incoherent claims and justifications
- 4.1.1. The case of justifications supporting opposite claims
- 4.1.2. The case of opposite justifications justifying the same claim
- 4.2. Relating claims and justifications: the need for knowledge and reasoning
- 4.2.1. Investigating relatedness via corpus analysis
- 4.2.2. A corpus analysis of the knowledge involved
- 4.2.3. Observation synthesis
- 4.3. Argument synthesis in natural language
- 4.3.1. Features of a synthesis
- 4.3.2. Structure of an argumentation synthesis
- 5. From Argumentation to Argument Mining
- 5.1. Some facets of argument mining
- 5.2. Designing annotation guidelines: some methodological elements
- 5.3. What results can be expected from an argument mining system?
- 5.4. Architecture of an argument mining system
- 5.5. The next chapters
- 6. Annotation Frameworks and Principles of Argument Analysis
- 6.1. Principles of argument analysis
- 6.1.1. Argumentative discourse units
- 6.1.2. Conclusions and premises
- 6.1.3. Warrants and backings
- 6.1.4. Qualifiers
- 6.1.5. Argument schemes
- 6.1.6. Attack relations: rebuttals, refutations, undercutters
- 6.1.7. Illocutionary forces, speech acts
- 6.1.8. Argument relations
- 6.1.9. Implicit argument components and tailored annotation frameworks
- 6.2. Examples of argument analysis frameworks
- 6.2.1. Rhetorical Structure Theory
- 6.2.2. Toulmin's model
- 6.2.3. Inference Anchoring Theory
- 6.2.4. Summary
- 6.3. Guidelines for argument analysis
- 6.3.1. Principles of annotation guidelines
- 6.3.2. Inter-annotator agreements
- 6.3.3. Interpretation of IAA measures
- 6.3.4. Some examples of IAAs
- 6.3.5. Summary
- 6.4. Annotation tools
- 6.4.1. Brat
- 6.4.2. RST tool
- 6.4.3. AGORA-net
- 6.4.4. Araucaria
- 6.4.5. Rationale
- 6.4.6. OVA+
- 6.4.7. Summary
- 6.5. Argument corpora
- 6.5.1. COMARG
- 6.5.2. A news editorial corpus
- 6.5.3. THF Airport ArgMining corpus
- 6.5.4. A Wikipedia articles corpus
- 6.5.5. AraucariaDB
- 6.5.6. An annotated essays corpus
- 6.5.7. A written dialogs corpus
- 6.5.8. A web discourse corpus
- 6.5.9. Argument Interchange Format Database
- 6.5.10. Summary
- 6.6. Conclusion
- 7. Argument Mining Applications and Systems
- 7.1. Application domains for argument mining
- 7.1.1. Opinion analysis augmented by argument mining
- 7.1.2. Summarization
- 7.1.3. Essays
- 7.1.4. Dialogues
- 7.1.5. Scientific and news articles
- 7.1.6. The Web
- 7.1.7. Legal field
- 7.1.8. Medical field
- 7.1.9. Education
- 7.2. Principles of argument mining systems
- 7.2.1. Argumentative discourse units detection
- 7.2.2. Units labeling
- 7.2.3. Argument structure detection
- 7.2.4. Argument completion
- 7.2.5. Argument structure representation
- 7.3. Some existing systems for argument mining
- 7.3.1. Automatic detection of rhetorical relations
- 7.3.2. Argument zoning
- 7.3.3. Stance detection
- 7.3.4. Argument mining for persuasive essays
- 7.3.5. Argument mining for web discourse
- 7.3.6. Argument mining for social media
- 7.3.7. Argument scheme classification and enthymemes reconstruction
- 7.3.8. Argument classes and argument strength classification
- 7.3.9. Textcoop
- 7.3.10. IBM debating technologies
- 7.3.11. Argument mining for legal texts
- 7.4. Efficiency and limitations of existing argument mining systems
- 7.5. Conclusion
- 8. A Computational Model and a Simple Grammar-Based Implementation
- 8.1. Identification of argumentative units
- 8.1.1. Challenges raised by the identification of argumentative units
- 8.1.2. Some linguistic techniques to identify ADUs
- 8.2. Mining for claims
- 8.2.1. The grammar formalisms
- 8.2.2. Lexical issues
- 8.2.3. Grammatical issues
- 8.2.4. Templates for claim analysis
- 8.3. Mining for supports and attacks
- 8.3.1. Structures introduced by connectors
- 8.3.2. Structures introduced by propositional attitudes
- 8.3.3. Other linguistic forms to express supports or attacks
- 8.4. Evaluating strength
- 8.5. Epilogue
- 9. Non-Verbal Dimensions of Argumentation: a Challenge for Argument Mining
- 9.1. The text and its additions
- 9.1.1. Text, pictures and icons
- 9.1.2. Transcriptions of oral debates
- 9.2. Argumentation and visual aspects
- 9.3. Argumentation and sound aspects
- 9.3.1. Music and rationality
- 9.3.2. Main features of musical structure: musical knowledge representation
- 9.4. Impact of non-verbal aspects on argument strength and on argument schemes
- 9.5. Ethical aspects
- Bibliography
- Index
- Other titles from iSTE in Information Systems, Web and Pervasive Computing
- EULA
