SOTAVerified

Argument Mining

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 171–180 of 284 papers

TitleStatusHype
TACAM: Topic And Context Aware Argument Mining—0
Neural-Symbolic Argumentation Mining: an Argument in Favor of Deep Learning and Reasoning—0
Fine-Grained Argument Unit Recognition and ClassificationCode0
Argument Mining for Understanding Peer Reviews—0
Combining Deep Learning and Argumentative Reasoning for the Analysis of Social Media Textual Content Using Small Data Sets—0
A Bayesian Approach for Sequence Tagging with CrowdsCode0
Where is Your Evidence: Improving Fact-checking by Justification ModelingCode0
Proposed Method for Annotation of Scientific Arguments in Terms of Semantic Relations and Argument Schemes—0
More or less controlled elicitation of argumentative text: Enlarging a microtext corpus via crowdsourcing—0
Feasible Annotation Scheme for Capturing Policy Argument Reasoning using Argument TemplatesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified