Datasets:
Tasks:
Text Classification
Sub-tasks:
multi-class-classification
Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
other
Annotations Creators:
other
Source Datasets:
original
License:
File size: 1,390 Bytes
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---
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:
- twitter
- 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. |