natural-language-processing-3
Stance Detection
3260 papers • 126 benchmarks • 313 datasets
Stance detection is the extraction of a subject's reaction to a claim made by a primary actor. It is a core part of a set of approaches to fake news assessment. Example: Source: "Apples are the most delicious fruit in existence" Reply: "Obviously not, because that is a reuben from Katz's" Stance: deny
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Benchmarks
These leaderboards are used to track progress in stance-detection-3
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MGTAB
MGTAB
RumourEval
RumourEval
FNC-1
FNC-1
Libraries
iUse these libraries to find stance-detection-3 models and implementations
2 papers 99
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Most implemented papers
A simple but tough-to-beat baseline for the Fake News Challenge stance detection task
Isabelle Augenstein, Sebastian Riedel, Georgios P. Spithourakis, B. Riedel•Mon Jul 10 2017
This paper presents their stance detection system, which claimed third place in Stage 1 of the Fake News Challenge, and proposes it as the 'simple but tough-to-beat baseline' for the FakeNews Challenge stance detection task.
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