About

Argument Mining is a field of corpus-based discourse analysis that involves the automatic identification of argumentative structures in text.

Source: AMPERSAND: Argument Mining for PERSuAsive oNline Discussions

Benchmarks

You can find evaluation results in the subtasks. You can also submitting evaluation metrics for this task.

Subtasks

Datasets

Greatest papers with code

TARGER: Neural Argument Mining at Your Fingertips

ACL 2019 achernodub/targer

We present TARGER, an open source neural argument mining framework for tagging arguments in free input texts and for keyword-based retrieval of arguments from an argument-tagged web-scale corpus.

ARGUMENT MINING

Classification and Clustering of Arguments with Contextualized Word Embeddings

ACL 2019 UKPLab/acl2019-BERT-argument-classification-and-clustering

We experiment with two recent contextualized word embedding methods (ELMo and BERT) in the context of open-domain argument search.

ARGUMENT MINING WORD EMBEDDINGS

Argument Mining with Structured SVMs and RNNs

ACL 2017 vene/marseille

We propose a novel factor graph model for argument mining, designed for settings in which the argumentative relations in a document do not necessarily form a tree structure.

ARGUMENT MINING

Where is Your Evidence: Improving Fact-checking by Justification Modeling

WS 2018 Tariq60/LIAR-PLUS

Fact-checking is a journalistic practice that compares a claim made publicly against trusted sources of facts.

ARGUMENT MINING EMOTION RECOGNITION

AMPERSAND: Argument Mining for PERSuAsive oNline Discussions

IJCNLP 2019 tuhinjubcse/AMPERSAND-EMNLP2019

Our approach for relation prediction uses contextual information in terms of fine-tuning a pre-trained language model and leveraging discourse relations based on Rhetorical Structure Theory.

ARGUMENT MINING LANGUAGE MODELLING

A Bayesian Approach for Sequence Tagging with Crowds

IJCNLP 2019 UKPLab/arxiv2018-bayesian-ensembles

Current methods for sequence tagging, a core task in NLP, are data hungry, which motivates the use of crowdsourcing as a cheap way to obtain labelled data.

ACTIVE LEARNING ARGUMENT MINING NAMED ENTITY RECOGNITION

Fine-Grained Argument Unit Recognition and Classification

22 Apr 2019trtm/AURC

In this work, we argue that the task should be performed on a more fine-grained level of sequence labeling.

ARGUMENT MINING SENTENCE SEGMENTATION