
Read this [BLOG](https://neuralmagic.com/blog/classifying-finance-tweets-in-real-time-with-sparse-transformers/) to see how I fine-tuned a sparse transformer on this dataset.

### 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.
task_categories:text-classification task_ids:multi-class-classification annotations_creators:other language_creators:other multilinguality:monolingual size_categories:10K<n<100K source_datasets:original language:en license:mit twitter finance markets stocks wallstreet quant hedgefunds region:us
{"annotations_creators": ["other"], "language_creators": ["other"], "language": ["en"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["multi-class-classification"], "pretty_name": "twitter financial news", "tags": ["twitter", "finance", "markets", "stocks", "wallstreet", "quant", "hedgefunds", "markets"]}
TAGS
#task_categories-text-classification #task_ids-multi-class-classification #annotations_creators-other #language_creators-other #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-mit #twitter #finance #markets #stocks #wallstreet #quant #hedgefunds #region-us 

Read this BLOG to see how I fine-tuned a sparse transformer on this dataset.


### 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:


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:



Licensing Information
=====================


The Twitter Financial Dataset (sentiment) version 1.0.0 is released under the MIT License.



### 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:


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:



Licensing Information
=====================


The Twitter Financial Dataset (sentiment) version 1.0.0 is released under the MIT License.
TAGS
#task_categories-text-classification #task_ids-multi-class-classification #annotations_creators-other #language_creators-other #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-mit #twitter #finance #markets #stocks #wallstreet #quant #hedgefunds #region-us 
 ### 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:


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:



Licensing Information
=====================


The Twitter Financial Dataset (sentiment) version 1.0.0 is released under the MIT License.