Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
English
Size:
10K - 100K
License:
metadata
language:
- en
license:
- cc-by-nc-4.0
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
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
dtype: 'null'
- name: status
dtype: string
- name: event_timestamp
dtype: timestamp[us]
- name: metrics
struct:
- name: text_length
dtype: int64
splits:
- name: train
num_bytes: 31840239
num_examples: 20491
download_size: 19678149
dataset_size: 31840239
Dataset Card for "tripadvisor-hotel-reviews"
Dataset Description
- Homepage: Kaggle Challenge
- Repository: https://www.kaggle.com/datasets/andrewmvd/trip-advisor-hotel-reviews
- Paper: https://zenodo.org/record/1219899
- Leaderboard: N.A.
- Point of Contact: N.A.
Dataset Summary
Hotels play a crucial role in traveling and with the increased access to information new pathways of selecting the best ones emerged. With this dataset, consisting of 20k reviews crawled from Tripadvisor, you can explore what makes a great hotel and maybe even use this model in your travels! Citations on a scale from 1 to 5.
Languages
english
Citation Information
If you use this dataset in your research, please credit the authors. Citation Alam, M. H., Ryu, W.-J., Lee, S., 2016. Joint multi-grain topic sentiment: modeling semantic aspects for online reviews. Information Sciences 339, 206–223. DOI License CC BY NC 4.0 Splash banner
Contributions
Thanks to @davidberenstein1957 for adding this dataset.