Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
sentiment-classification
Languages:
English
Size:
10K - 100K
ArXiv:
License:
metadata
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 1k<10K
task_categories:
- text-classification
task_ids:
- sentiment-classification
pretty_name: TweetTopicSingle
Dataset Card for "cardiff_nlp/tweet_topic_single"
Dataset Description
- Paper: TBA
- Dataset: Tweet Topic Dataset
- Domain: Twitter
- Number of Class: 6
Dataset Summary
Topic classification dataset on Twitter with single label per tweet.
- Label Types:
arts_&_culture
,business_&_entrepreneurs
,pop_culture
,daily_life
,sports_&_gaming
,science_&_technology
Dataset Structure
Data Instances
An example of train
looks as follows.
{
"text": "Game day for {{USERNAME}} U18\u2019s against {{USERNAME}} U18\u2019s. Even though it\u2019s a \u2018home\u2019 game for the people that have settled in Mid Wales it\u2019s still a 4 hour round trip for us up to Colwyn Bay. Still enjoy it though!",
"date": "2019-09-08",
"label": 4,
"id": 1170606779568463874,
"label_name": "sports_&_gaming"
}
Label ID
The label2id dictionary can be found at here.
{
"arts_&_culture": 0,
"business_&_entrepreneurs": 1,
"pop_culture": 2,
"daily_life": 3,
"sports_&_gaming": 4,
"science_&_technology": 5
}
Data Splits
Citation Information
TBA