metadata
dataset_info:
features:
- name: id
dtype: int64
- name: text
dtype: string
- name: label
dtype: string
splits:
- name: train
num_bytes: 95263
num_examples: 696
- name: validation
num_bytes: 20394
num_examples: 149
- name: test
num_bytes: 20531
num_examples: 150
download_size: 100947
dataset_size: 136188
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
Dataset Card for BilTweetNews-Sentiment-Analysis
Table of Contents
Dataset Description
BilTweetNews sentiment analysis dataset is originally released.
Dataset Structure
The original dataset only had train split. We applied the following splitting methodology to obtain validation and test splits:
- If a train-val-test split is available, we use the existing divisions as provided.
- For datasets with a train-test split only, we create a val split from the training set, sized to match the test set, and apply this across all models.
- In cases with a train-val split, we reassign the val set as the test split, then generate a new val split from the training data following the approach above.
- In cases with a val-test split, we split validation into train and vad sets in 80% and 20% proportions, respectively.
- When only a single combined split is present, we partition the data into train, val, and test sets in 70%, 15%, and 15% proportions, respectively.
Data Fields
- text(string) : Contains tweets related to Turkish news
- level(string) : one of 5 categories: Positive, Negative, Neutral, Sarcastic, Multi