Argumentation Mining

The main goal of argumentation mining is to analyze argumentative structures within an argument-rich document, and reason about their composition. Recently, there is also in- terest in the task of …...

Analyzing arguments in user-generated Web discourse has recently gained atten- tion in argumentation mining, an evolving field of NLP. Current approaches, which employ fully-supervised machine learn- ing, are usually domain …...

Argumentation mining and stance classifica- tion were recently introduced as interesting tasks in text mining. In this paper, a novel framework for argument tagging based on topic modeling is proposed. …...

We introduce a new approach to argumen- tation mining that we applied to a parallel German/English corpus of short texts an- notated with argumentation structure. We focus on structure prediction, …...

Argumentation mining obviously involves finding support relations between statements, but many interesting instances of argumen- tation also contain counter-considerations, which the author mentions in order to preempt possible objections by …...

We advocate a relation based approach to Ar- gumentation Mining. Our focus lies on the extraction of argumentative relations instead of the identification of arguments, themselves. By classifying pairs of …...

AbstractSeveral tasks in argumentation mining and debating, question-answering, and natural language inference involve classifying a sequence in the context of another sequence (referred as bi-sequence classification). For several single sequence …...

Argumentation mining is considered as a key technology for future search engines and au- tomated decision making. In such applica- tions, argumentative text segments have to be mined from large …...

AbstractThe goal of argumentation mining, an evolving research field in computational linguistics, is to design methods capable of analyzing people’s argumentation. In this article, we go beyond the state of …...

AbstractGRASP (GReedy Augmented Sequential Patterns) is an algorithm for automatically extracting patterns that characterize subtle linguistic phenomena. To that end, GRASP augments each term of input text with multiple layers …...

We present a multi-layer annotated corpus of 112 argumentative microtexts encompassing not only argument structure and discourse relations (Stede et al., 2016), but also argument schemes — the inferential relations …...

AbstractArgumentation mining (AM) requires the identification of complex discourse structures and has lately been applied with success monolingually. In this work, we show that the existing resources are, however, not …...

AbstractArgumentation mining on essays is a new challenging task in natural language processing, which aims to identify the types and locations of argumentation components. Recent research mainly models the task …...

AbstractState-of-the-art systems for argumentation mining are supervised, thus relying on training data containing manually annotated argument components and the relationships between them. To eliminate the reliance on annotated data, we …...

AbstractThe goal of argumentation mining is to automatically extract argumentation structures from argumentative texts. Most existing methods determine argumentative relations by exhaustively enumerating all possible pairs of argument components, which …...

AbstractExpressive text encoders such as RNNs and Transformer Networks have been at the center of NLP models in recent work. Most of the effort has focused on sentence-level tasks, capturing …...

AbstractArgumentation mining is a growing area of research and has several interesting practical applications of mining legal arguments. Support and Attack relations are the backbone of any legal argument. However, …...

AbstractThe integration of multimodality in natural language processing (NLP) tasks seeks to exploit the complementary information contained in two or more modalities, such as text, audio and video. This paper …...