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 91–100 of 284 papers

TitleStatusHype
Cross-topic Argument Mining from Heterogeneous Sources Using Attention-based Neural Networks—0
Cross-topic Argument Mining from Heterogeneous Sources—0
CRST: a Claim Retrieval System in Twitter—0
DART: a Dataset of Arguments and their Relations on Twitter—0
Argumentation Quality Assessment: Theory vs. Practice—0
A Joint Sentiment-Target-Stance Model for Stance Classification in Tweets—0
Dave the debater: a retrieval-based and generative argumentative dialogue agent—0
Argument Mining on Twitter: Arguments, Facts and Sources—0
200K+ Crowdsourced Political Arguments for a New Chilean Constitution—0
Argumentation: Content, Structure, and Relationship with Essay Quality—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TACOmacro F185.06—Unverified