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

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Showing 81–90 of 284 papers

TitleStatusHype
Combining Deep Learning and Argumentative Reasoning for the Analysis of Social Media Textual Content Using Small Data Sets—0
Context-aware Argumentative Relation Mining—0
Contextual Argument Component Classification for Class Discussions—0
Contextual stance classification of opinions: A step towards enthymeme reconstruction in online reviews—0
Budget Argument Mining Dataset Using Japanese Minutes from the National Diet and Local Assemblies—0
Argumentation Quality Assessment: Theory vs. Practice—0
Corpus Wide Argument Mining -- a Working Solution—0
Cross-Genre Argument Mining: Can Language Models Automatically Fill in Missing Discourse Markers?—0
Argument Mining for Scholarly Document Processing: Taking Stock and Looking Ahead—0
A Joint Sentiment-Target-Stance Model for Stance Classification in Tweets—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified