README.md

metadata

language:
  - en
paperswithcode_id: sentiment140
pretty_name: Sentiment140
dataset_info:
  config_name: sentiment140
  features:
    - name: text
      dtype: string
    - name: date
      dtype: string
    - name: user
      dtype: string
    - name: sentiment
      dtype: int32
    - name: query
      dtype: string
  splits:
    - name: train
      num_bytes: 224542690
      num_examples: 1600000
    - name: test
      num_bytes: 72971
      num_examples: 498
  download_size: 81363704
  dataset_size: 224615661
train-eval-index:
  - config: sentiment140
    task: text-classification
    task_id: multi_class_classification
    splits:
      train_split: train
      eval_split: test
    col_mapping:
      text: text
      sentiment: target
    metrics:
      - type: accuracy
        name: Accuracy
      - type: f1
        name: F1 macro
        args:
          average: macro
      - type: f1
        name: F1 micro
        args:
          average: micro
      - type: f1
        name: F1 weighted
        args:
          average: weighted
      - type: precision
        name: Precision macro
        args:
          average: macro
      - type: precision
        name: Precision micro
        args:
          average: micro
      - type: precision
        name: Precision weighted
        args:
          average: weighted
      - type: recall
        name: Recall macro
        args:
          average: macro
      - type: recall
        name: Recall micro
        args:
          average: micro
      - type: recall
        name: Recall weighted
        args:
          average: weighted

Dataset Card for "sentiment140"

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: http://help.sentiment140.com/home
• Repository: More Information Needed
• Paper: More Information Needed
• Point of Contact: More Information Needed
• Size of downloaded dataset files: 81.36 MB
• Size of the generated dataset: 225.82 MB
• Total amount of disk used: 307.18 MB

Dataset Summary

Sentiment140 consists of Twitter messages with emoticons, which are used as noisy labels for sentiment classification. For more detailed information please refer to the paper.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

sentiment140

• Size of downloaded dataset files: 81.36 MB
• Size of the generated dataset: 225.82 MB
• Total amount of disk used: 307.18 MB

An example of 'train' looks as follows.

{
    "date": "23-04-2010",
    "query": "NO_QUERY",
    "sentiment": 3,
    "text": "train message",
    "user": "train user"
}

Data Fields

The data fields are the same among all splits.

sentiment140

• text: a string feature.
• date: a string feature.
• user: a string feature.
• sentiment: a int32 feature.
• query: a string feature.

Data Splits

name	train	test
sentiment140	1600000	498

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Annotation process

More Information Needed

Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

More Information Needed

Citation Information

@article{go2009twitter,
  title={Twitter sentiment classification using distant supervision},
  author={Go, Alec and Bhayani, Richa and Huang, Lei},
  journal={CS224N project report, Stanford},
  volume={1},
  number={12},
  pages={2009},
  year={2009}
}

Contributions

Thanks to @patrickvonplaten, @thomwolf for adding this dataset.