README.md

metadata

language:
  - en
license: cc
size_categories:
  - 10K<n<100K
task_categories:
  - text-classification
pretty_name: Tweets
tags:
  - toxicity
dataset_info:
  features:
    - name: label
      dtype: int64
    - name: text
      dtype: string
  splits:
    - name: train
      num_bytes: 1621836
      num_examples: 14640
  download_size: 894257
  dataset_size: 1621836
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

Tweets

Overview

This dataset contains texts from customers posted on Twitter regarding their air travel experiences, whether they were upset, neutral, or satisfied with the trip and the airline's service.

Dataset Details

The dataset is a smaller version of the original dataset. This data originally came from Crowdflower's Data for Everyone library The original Twitter data was scraped from February 2015, and contributors were asked first to classify positive, negative, and neutral tweets, followed by categorizing negative reasons (such as "late flight" or "rude service"). This version contains whether the sentiment of the tweets in this set was positive (16%), neutral (21%), or negative (63%) for six US airlines.

• Dataset Name: Twitter US Airline Sentiment
• Language: English
• Total Size: 14,640 demonstrations

Contents

The dataset consists of a data frame with the following columns:

• label
• text

{
  "label": 0,
  "text": "virginamerica why are your first fares in may over three times more than other carriers when all seats are available to select.",
}

How to use

from datasets import load_dataset

dataset = load_dataset("AiresPucrs/tweets", split='train')

License

The Twitter US Airline Sentiment is licensed under the Creative Commons(CC) License CC BY-NC-SA 4.0.