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NLAS-multi: A Multilingual Corpus of Automatically Generated Natural Language Argumentation Schemes
Some of the major limitations identified in the areas of argument mining, argument generation, and natural language argument analysis are related to the complexity of annotating argumentatively rich data, the limited size of these corpora, and the constraints that represent the different languages and domains in which these data is annotated.
Argument Mining: A Survey
Argument mining is the automatic identification and extraction of the structure of inference and reasoning expressed as arguments presented in natural language.
An Online Annotation Assistant for Argument Schemes
Understanding the inferential principles underpinning an argument is essential to the proper interpretation and evaluation of persuasive discourse.
Using Complex Argumentative Interactions to Reconstruct the Argumentative Structure of Large-Scale Debates
In this paper we consider the insights that can be gained by considering large scale argument networks and the complex interactions between their constituent propositions.
Mining Argumentative Structure from Natural Language text using Automatically Generated Premise-Conclusion Topic Models
These statements are then used to produce a matrix representing the inferential relationship between different aspects of the topic.
Multi-level computational methods for interdisciplinary research in the HathiTrust Digital Library
We show how faceted search using a combination of traditional classification systems and mixed-membership topic models can go beyond keyword search to inform resource discovery, hypothesis formulation, and argument extraction for interdisciplinary research.
A Corpus of Argument Networks: Using Graph Properties to Analyse Divisive Issues
Governments are increasingly utilising online platforms in order to engage with, and ascertain the opinions of, their citizens.
