argumentationmining
Argumentation mining, or argument mining, is a subfield of natural language processing and computational linguistics that aims to automatically identify and analyze argumentative structures in text. It seeks to extract arguments, their components, and the relations among them to support reasoning tasks such as assessment, retrieval, or synthesis.
Core tasks include identifying argument components such as claims and premises, determining their boundaries within documents,
Methodologically, AM blends supervised learning with linguistic annotation, rule-based approaches, and, more recently, deep learning. Techniques
Evaluation uses metrics for component labeling (precision, recall, F1), relation prediction, and overall argumentative structure quality.
Applications span political communication analysis, misinformation detection, educational tools for critical thinking, and legal argumentation support.
Ongoing challenges include domain and language adaptation, annotation standardization, handling long-range structures, and building interpretable models.