Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
csv
Sub-tasks:
multi-class-classification
Languages:
English
Size:
10K - 100K
License:
| annotations_creators: | |
| - other | |
| language: | |
| - en | |
| language_creators: | |
| - other | |
| license: | |
| - mit | |
| multilinguality: | |
| - monolingual | |
| pretty_name: twitter financial news | |
| size_categories: | |
| - 10K<n<100K | |
| source_datasets: | |
| - original | |
| tags: | |
| - finance | |
| - markets | |
| - stocks | |
| - wallstreet | |
| - quant | |
| - hedgefunds | |
| - markets | |
| task_categories: | |
| - text-classification | |
| task_ids: | |
| - multi-class-classification | |
| ### Dataset Description | |
| The Twitter Financial News dataset is an English-language dataset containing an annotated corpus of finance-related tweets. This dataset is used to classify finance-related tweets for their sentiment. | |
| 1. The dataset holds 11,932 documents annotated with 3 labels: | |
| ```python | |
| sentiments = { | |
| "LABEL_0": "Bearish", | |
| "LABEL_1": "Bullish", | |
| "LABEL_2": "Neutral" | |
| } | |
| ``` | |
| The data was collected using the Twitter API. The current dataset supports the multi-class classification task. | |
| ### Task: Sentiment Analysis | |
| # Data Splits | |
| There are 2 splits: train and validation. Below are the statistics: | |
| | Dataset Split | Number of Instances in Split | | |
| | ------------- | ------------------------------------------- | | |
| | Train | 9,938 | | |
| | Validation | 2,486 | | |
| # Licensing Information | |
| The Twitter Financial Dataset (sentiment) version 1.0.0 is released under the MIT License. |