---
multilinguality:
  - multilingual
size_categories:
  - 100K<n<1M
source_datasets:
  - kaggle
task_categories:
  - text-classification
task_ids:
  - sentiment-classification
tags:
- datasets
- bitcoin
- text-classification
- sentiment-analysis
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
  - split: eval
    path: data/eval-*
dataset_info:
  features:
  - name: Date
    dtype: string
  - name: text
    dtype: string
  - name: Sentiment
    dtype: string
  splits:
  - name: train
    num_bytes: 12842246
    num_examples: 77791
  - name: test
    num_bytes: 1609120
    num_examples: 9724
  - name: eval
    num_bytes: 1598297
    num_examples: 9724
  download_size: 9868625
  dataset_size: 16049663
---
# Dataset Card for "Bitcoin Tweets"

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
- [Dataset Distribution](#dataset-distribution)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)


### Dataset Summary

This dataset contains a collection of 16 million tweets related to Bitcoin, collected from Twitter. Each tweet is tagged with sentiment (positive, negative, neutral). The dataset was originally created and uploaded to Kaggle by user gauravduttakiit. It is a valuable resource for training and evaluating models for sentiment analysis within the context of cryptocurrency discussions.

### Supported Tasks and Leaderboards

- `text-classification`: This dataset can be used to train a model for sentiment analysis. The performance of the model can be evaluated using standard metrics like accuracy, F1 score, precision, and recall.

### Languages

The text data is primarily in English.

## Dataset Structure

### Data Instances

Each instance in the dataset contains the following fields:
- `tweet`: the text of the tweet.
- `sentiment`: the sentiment of the tweet, labeled as either "positive", "negative", or "neutral".

### Data Fields

- `tweet`: a string containing the text of the tweet.
- `sentiment`: a string indicating the sentiment of the tweet.

### Data Splits

The dataset is not explicitly split into training, validation, and test sets. Users will need to create these splits as per their requirements.

## Dataset Creation

### Curation Rationale

The dataset was curated to analyze the sentiment within the cryptocurrency community, specifically focusing on Bitcoin.

### Source Data

#### Initial Data Collection and Normalization

The data was collected from Twitter using specific keywords related to Bitcoin. For more details regarding data collection, one can refer to the [original Kaggle dataset](https://www.kaggle.com/datasets/gauravduttakiit/bitcoin-tweets-16m-tweets-with-sentiment-tagged).

#### Who are the source data providers?

The data was provided by Kaggle user gauravduttakiit.

### Annotations

The sentiment labels were generated using automated sentiment analysis tools. For more details, refer to the [original Kaggle dataset](https://www.kaggle.com/datasets/gauravduttakiit/bitcoin-tweets-16m-tweets-with-sentiment-tagged).

## Dataset Distribution

### Dataset Curators

The dataset was curated by gauravduttakiit and uploaded to Kaggle.

### Licensing Information

Refer to the [original Kaggle dataset](https://www.kaggle.com/datasets/gauravduttakiit/bitcoin-tweets-16m-tweets-with-sentiment-tagged) for licensing information.