| language: en | |
| license: mit | |
| dataset_info: | |
| features: | |
| - name: _id | |
| dtype: string | |
| - name: sentence | |
| dtype: string | |
| - name: target | |
| dtype: string | |
| - name: aspect | |
| dtype: string | |
| - name: score | |
| dtype: float64 | |
| - name: type | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 119567 | |
| num_examples: 822 | |
| - name: valid | |
| num_bytes: 17184 | |
| num_examples: 117 | |
| - name: test | |
| num_bytes: 33728 | |
| num_examples: 234 | |
| download_size: 102225 | |
| dataset_size: 170479 | |
| # Dataset Name | |
| ## Dataset Description | |
| This dataset is based on the task 1 of the Financial Sentiment Analysis in the Wild (FiQA) challenge. It follows the same settings as described in the paper 'A Baseline for Aspect-Based Sentiment Analysis in Financial Microblogs and News'. The dataset is split into three subsets: train, valid, test with sizes 822, 117, 234 respectively. | |
| ## Dataset Structure | |
| - `_id`: ID of the data point | |
| - `sentence`: The sentence | |
| - `target`: The target of the sentiment | |
| - `aspect`: The aspect of the sentiment | |
| - `score`: The sentiment score | |
| - `type`: The type of the data point (headline or post) | |
| ## Additional Information | |
| - Homepage: [FiQA Challenge](https://sites.google.com/view/fiqa/home) | |
| - Citation: [A Baseline for Aspect-Based Sentiment Analysis in Financial Microblogs and News](https://arxiv.org/pdf/2211.00083.pdf) | |
| ## Downloading CSV | |
| ```python | |
| from datasets import load_dataset | |
| # Load the dataset from the hub | |
| dataset = load_dataset("ChanceFocus/fiqa-sentiment-classification") | |
| # Save the dataset to a CSV file | |
| dataset["train"].to_csv("train.csv") | |
| dataset["valid"].to_csv("valid.csv") | |
| dataset["test"].to_csv("test.csv") | |
| ``` | |