Existing approaches to summarizing multi-party argumentative conversations in reader
comment are extractive and fail to capture the argumentative nature of these conversations …

In this paper we examine the application of an unsupervised extractive summarisation
algorithm, TextRank, on a different task, the identification of argumentative components. Our …

Argumentation mining, a relatively new area of discourse analysis, involves automatically
identifying and structuring arguments. Following a basic introduction to argumentation, we …

Argument extraction is the task of identifying arguments, along with their components in text.
Arguments can be usually decomposed into a claim and one or more premises justifying it …

Scholarly Argumentation Mining (SAM) has recently gained attention due to its potential to
help scholars with the rapid growth of published scientific literature. It comprises two …

Online communities host growing numbers of discussions amongst large groups of
participants on all manner of topics. This user-generated content contains millions of …

Argument mining targets structures in natural language related to interpretation and
persuasion which are central to scientific communication. Most scholarly discourse involves …

Many argumentative texts, and news editorials in particular, follow a specific strategy to
persuade their readers of some opinion or attitude. This includes decisions such as when to …

This paper proposes a shared task for the identification of the argumentative structure in
newspaper editorials. By the term “argumentative structure” we refer to the sequence of …

Identifying the main claims occurring across texts is important for large-scale argumentation
mining from social media. However, the claims that users make are often unclear and build …