Languages: en

Dataset Card for "sentiment140"

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


More Information Needed

Dataset Structure

We show detailed information for up to 5 configurations of the dataset.

Data Instances


  • Size of downloaded dataset files: 77.59 MB
  • Size of the generated dataset: 215.36 MB
  • Total amount of disk used: 292.95 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.


  • 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


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

  title={Twitter sentiment classification using distant supervision},
  author={Go, Alec and Bhayani, Richa and Huang, Lei},
  journal={CS224N project report, Stanford},


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

Models trained or fine-tuned on sentiment140

None yet