| --- |
| 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") |
| ``` |
|
|
