metadata

language:
  - en
license:
  - unknown
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - text-classification
task_ids:
  - sentiment-classification
  - sentiment-analysis
dataset_info:
  features:
    - name: text
      dtype: string
    - name: inputs
      struct:
        - name: text
          dtype: string
    - name: prediction
      list:
        - name: label
          dtype: string
        - name: score
          dtype: float64
    - name: prediction_agent
      dtype: string
    - name: annotation
      dtype: 'null'
    - name: annotation_agent
      dtype: 'null'
    - name: multi_label
      dtype: bool
    - name: explanation
      dtype: 'null'
    - name: id
      dtype: string
    - name: metadata
      struct:
        - name: location
          dtype: string
        - name: screen_name
          dtype: int64
        - name: split
          dtype: string
        - name: user_name
          dtype: int64
    - name: status
      dtype: string
    - name: event_timestamp
      dtype: timestamp[us]
    - name: metrics
      struct:
        - name: text_length
          dtype: int64
  splits:
    - name: train
      num_bytes: 25394534
      num_examples: 44955
  download_size: 15712627
  dataset_size: 25394534

Dataset Card for "twitter-coronavirus"

Dataset Description

Homepage: Kaggle Challenge
Repository: https://www.kaggle.com/datasets/datatattle/covid-19-nlp-text-classification
Paper: N.A.
Leaderboard: N.A.
Point of Contact: N.A.

Dataset Summary

Perform Text Classification on the data. The tweets have been pulled from Twitter and manual tagging has been done then. The names and usernames have been given codes to avoid any privacy concerns.

Columns:

Location
Tweet At
Original Tweet
Label

Extremely Negative
Negative
Neutral
Positive
Extremely Positive

Languages

english

Citation Information

https://www.kaggle.com/datasets/datatattle/covid-19-nlp-text-classification

Contributions

Thanks to @davidberenstein1957 for adding this dataset.