metadata
dataset_info:
features:
- name: text
dtype: string
- name: sentiment
dtype: float64
splits:
- name: train
num_bytes: 163565
num_examples: 1464
download_size: 96001
dataset_size: 163565
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: apache-2.0
task_categories:
- text-classification
language:
- en
size_categories:
- 1K<n<10K
Compare Models
Overview
This dataset is a reduced version of Tweets Dataset. Which in turn is a reduced version of the original dataset:Crowdflower's Data for Everyone library. 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
This version contains whether the sentiment of the tweets in this set was positive, neutral, or negative. The dataset was used in this notebook model_extraction_nlp.
- Dataset Name: compare-models
- Language: English
- Total Size: 1,464
Contents
The dataset consists of a data frame with the following column:
- text
- sentiment
{
"text": "usairways how is it that my flt to ewr was cancelled flightled yet flts to nyc from usairways are still flying",
"sentiment:" 0,
"text: " "jetblue do they have to depart from washington dc",
"sentiment:" 1,
"text: " "southwestair youre my early frontrunner for best airline oscars2016",
"sentiment:" 2,
}
How to use
from datasets import load_dataset
dataset = load_dataset('AiresPucrs/compare-models', split='train')
License
This dataset is licensed under the Apache License, version 2.0.