---
license: mit
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
dataset_info:
  features:
  - name: premise
    dtype: string
  - name: target
    dtype: string
  - name: stance
    dtype: int64
  - name: hypothesis
    dtype: string
  - name: label
    dtype: int64
  splits:
  - name: train
    num_bytes: 869570
    num_examples: 1935
  - name: validation
    num_bytes: 288178
    num_examples: 645
  - name: test
    num_bytes: 293856
    num_examples: 645
  download_size: 464770
  dataset_size: 1451604
---

This dataset contains quote tweets that have been hand labeled for stance towards a politician. Quote tweets are a particularly challenging classification task because they contain multiple (often contradictory) expressions from multiple authors.

Twitter handles from politicians in the dataset have been replaced by their name. Be aware that "rt @realdonaldtrump You're a liar!" has been replaced with "rt trump You're a liar!",
And means the author is retweeting Trump calling someone else a liar, not the author calling Trump a liar.

Stance:  
  -1: Against: The document is critical of the target.  
   0: Neutral: The document doesn't express an opinion about the target or it can't be determined what the expressed opinion is with the given context.  
   1: Support: The document expresses support for the target. Expressing collaboration on bills or letters is considered support.  
 
Label:  
  0: Entail  
  1: Not Entail  

The test set contains 645 documents, ~400 of which are were randomly sampled from the entire data set and the rest are about 6 politicians not included in the training or validation data. These politicians are:
  - Ted Cruz
  - Hakeem Jeffries
  - Madison Cawthorn
  - Alexandria Ocasio-Cortez
  - Mitt Romney
  - Kyrsten Sinema