pretty name: PoliStance Affect
task_categories:
- zero-shot-classification
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: hypothesis
dtype: string
- name: stance
dtype: int32
- name: label
dtype: int64
splits:
- name: train
num_bytes: 5392570
num_examples: 17164
- name: validation
num_bytes: 1327661
num_examples: 4291
- name: test
num_bytes: 1633230
num_examples: 5383
download_size: 4211025
dataset_size: 8353461
Dataset for training an entailment classifier to recognize approval/disapproval of politicians. Documents are Tweets from Kawintiranon (2022), the MTSD dataset, as well as Tweets and sentences taken weekly newsletters for select politicians from the 115th, 116th, and 117th congress. Documents are triple coded -- once from the original compilers of the dataset, once from GPT-4, and a third time to adjudicate discrepancies between the two.
Twitter handles from politicians in the dataset have been replaced by their name.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
In addition to 1,000 documents about targets in the training set, the test set contains documents about 6 politicians not included in the training or validation data:
- Ted Cruz
- Hakeem Jeffries
- Madison Cawthorn
- Alexandria Ocasio-Cortez
- Mitt Romney
- Kyrsten Sinema