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 221–230 of 284 papers

TitleStatusHype
Argument Relation Classification Using a Joint Inference Model—0
Annotation of argument structure in Japanese legal documents—0
Improving Claim Stance Classification with Lexical Knowledge Expansion and Context Utilization—0
Patterns of Argumentation Strategies across Topics—0
Proceedings of the 4th Workshop on Argument Mining—0
Identifying attack and support argumentative relations using deep learning—0
Analyzing the Semantic Types of Claims and Premises in an Online Persuasive Forum—0
Building an Argument Search Engine for the Web—0
200K+ Crowdsourced Political Arguments for a New Chilean Constitution—0
What works and what does not: Classifier and feature analysis for argument mining—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified