Search Results for author: John Lawrence

Found 10 papers, 0 papers with code

Argument Mining: A Survey

no code implementations CL 2019 John Lawrence, Chris Reed

Argument mining is the automatic identification and extraction of the structure of inference and reasoning expressed as arguments presented in natural language.

Argument Mining Language understanding +1

An Online Annotation Assistant for Argument Schemes

no code implementations WS 2019 John Lawrence, Jacky Visser, Chris Reed

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

no code implementations WS 2017 John Lawrence, Chris Reed

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.

Argument Mining Decision Making

Multi-level computational methods for interdisciplinary research in the HathiTrust Digital Library

no code implementations3 Feb 2017 Jaimie Murdock, Colin Allen, Katy Börner, Robert Light, Simon McAlister, Andrew Ravenscroft, Robert Rose, Doori Rose, Jun Otsuka, David Bourget, John Lawrence, Chris Reed

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.

General Classification Topic Models

A Corpus of Argument Networks: Using Graph Properties to Analyse Divisive Issues

no code implementations LREC 2016 Barbara Konat, John Lawrence, Joonsuk Park, Katarzyna Budzynska, Chris Reed

Governments are increasingly utilising online platforms in order to engage with, and ascertain the opinions of, their citizens.

Argument Mining

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