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
The RumourEval 2017 dataset has been used for stance detection in English (subtask A). It features multiple stories and thousands of reply:response pairs, with train, test and evaluation splits each containing a distinct set of over-arching narratives.
This dataset subsumes the large PHEME collection of rumors and stance, which includes German.
| Model | Accuracy | Paper / Source |
|---|---|---|
| Kochkina et al. 2017 | 0.784 | Turing at SemEval-2017 Task 8: Sequential Approach to Rumour Stance Classification with Branch-LSTM |
| Bahuleyan and Vechtomova 2017 | 0.780 | UWaterloo at SemEval-2017 Task 8: Detecting Stance towards Rumours with Topic Independent Features |